Wyniki wyszukiwania dla: ESTIMATION ALGORITHMS
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Sonar Pulse Detection Using Chirp Rate Estimation and CFAR Algorithms
PublikacjaThis paper presents a new approach to sonar pulse detection. The method uses chirp rate estimators and algorithms for the adaptive threshold, commonly used in radiolocation. The proposed approach allows detection of pulses of unknown parameters, which may be used in passive hydrolocation or jamming detection in underwater communication. Such an analysis is possible thanks to a new kind of imaging, which presents signal energy in...
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Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with moving measurment window
PublikacjaW artykule rozważana jest łączna estymacja przedziałowa zmiennych i parametrów w złożonej sieci dynamicznej w oparciu niepewne modele parametryczne i ograniczoną liczbę pomiarów. Opracowany został rekursywny algorytm estymacji z przesuwnym oknem pomiarowym, odpowiedni dla monitorowania sieci on-line. Okno pomiarowe pozwala na stabilizowanie klasycznego algorytmu rekurencyjnego estymacji i znacznie poprawienie obcisłości estymat....
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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New Algorithms for Adaptive Notch Smoothing
PublikacjaThe problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed...
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Probe signal processing for channel estimation in underwater acoustic communication system
PublikacjaUnderwater acoustic communication channels are characterized by a large variety of propagation conditions. Designing a reliable communication system requires knowledge of the transmission parameters of the channel, namely multipath delay spread, Doppler spread, coherence time, and coherence bandwidth. However, the possibilities of its estimation in a realtime underwater communication system are limited, mainly due to the computational...
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Research and Analysis of Accuracy of Location Estimation in Inertial Navigation System
PublikacjaIn the article the research and analysis of digital signal processing and its influence on accuracy of location estimation in developed inertial navigation system was presented. The purpose of the system is to localize moving people in indoor environment. During research a measuring unit for recording selected movement parameters was made. In the article were also described author’s inertial navigation algorithms.
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Hyperbolic position location estimation in the multipath propagation environment
PublikacjaThe efficiency analysis a hyperbolic position location estimation in the multipath propagation environment in the wideband code division multiple access (WCDMA) interface was presented. Four, the most popular methods: Chan's, Foy's, Fang's and Friedlander's were considered. These algorithms enable the calculation of the geographical position of a mobile station (MS) using the time differences of arrival (TDOA) between several base...
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Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublikacjaNoncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothingis based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman filter-based parameter trackers can...
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Parameter and delay estimation of linear continuous-time systems
PublikacjaIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous identification...
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Parameter and delay estimation of linear continuous-time systems
PublikacjaIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is usually described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous...
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Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublikacjaThe problem of noncausal identification of a time-varying linear system subject to both smooth and occasional jump-type changes is considered and solved using the preestimation technique combined with the basis function approach to modeling the variability of system parameters. The proposed estimation algorithms yield very good parameter tracking results and are computationally attractive.
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublikacjaIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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On–line Parameter and Delay Estimation of Continuous–Time Dynamic Systems
PublikacjaThe problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous...
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Optimised Allocation of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised placement of the hard quality sensors in Drinking Water Distribution Systems for robust quality monitoring is formulated. Two numerical algorithms to solve the problem are derived. The optimality is meant as achieving a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm. The robust estimation algorithm recently developed...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublikacjaIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Direction-of-Arrival Estimation Methods in Interferometric Echo Sounding
PublikacjaNowadays, there are two leading sea sounding technologies: the multibeam echo sounder and the multiphase echo sounder (also known as phase-dierence side scan sonar or bathymetric side scan sonar). Both solutions have their advantages and disadvantages, and they can be perceived as complementary to each other. The article reviews the development of interferometric echo sounding array configurations and the various methods applied...
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APPLICATION OF SATELLITE IMAGERY AND GIS TOOLS FOR LAND SURFACE TEMPERATURE ESTIMATION AND VERIFICATION
PublikacjaLand surface temperature (LST) plays an important role in many land-surface processes on regional as well on global scales. It is also a good indicator of energy flux phenomena and is used as a parameter in various Earth observation related studies. However, LST estimation based on processing and utilisation of satellite derived data constitutes several problems in terms of time limitations, accessibility, atmospheric influence...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublikacjaCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Validation of Interpolation Algorithms for Multiscale UV-VIS Imaging Using UAV Spectrometer
PublikacjaIn this study, we present a comparison of popular methods for the interpolation of irregular spatial data in order to determine the applicability of each algorithm for hyperspectral reflectance estimation. The algorithms were benchmarked against a very high-resolution orthoimage from an RGB camera and medium-resolution satellite imagery from Sentinel-2A. We tested five interpolation algorithms: Triangulated Irregular Network (TIN),...
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Generalized adaptive notch smoothers for real-valued signals and systems
PublikacjaSystems with quasi-periodically varying coefficients can be tracked using the algorithms known as generalized adaptive notch filters (GANFs). GANF algorithms can be considered an extension, to the system case, of classical adaptive notch filters (ANFs). We show that estimation accuracy of the existing algorithms, as well as their robustness to the choice of design parameters, can be considerably improved by means of compensating...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublikacjaThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublikacjaThe problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublikacjaNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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Optimised Robust Placement of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised robust placement of the hard quality sensors in Drinking Water Distribution Systems under several water demand scenarios for robust quality monitoring is formulated. Numerical algorithms to solve the problem are derived. The optimality is meant as achieving at the same time a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm...
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Decoupled Kalman filter based identification of time-varying FIR systems
PublikacjaWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublikacjaWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
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On bidirectional preestimates and their application to identification of fast time-varying systems
PublikacjaWhen applied to the identification of time-varying systems, such as rapidly fading telecommunication channels, adaptive estimation algorithms built on the local basis function (LBF) principle yield excellent tracking performance but are computationally demanding. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a substantial reduction in complexity without significant performance...
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Stereo vision with Equal Baseline Multiple Camera Set (EBMCS) for obtaining depth maps of plants
PublikacjaThis paper presents a method of improving the estimation of distances between an autonomous harvesting robot and plants with ripe fruits by using the vision system based on five cameras. The system is called Equal Baseline Multiple Camera Set (EBMCS). EBMCS has some features of a camera matrix and a camera array. EBMCS is regarded as a set of stereo cameras for estimating distances by obtaining disparity maps and depth maps. This...
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Identification of models and signals robust to occasional outliers
PublikacjaIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublikacjaIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Porównanie algorytmów lokalizacji wewnątrzbudynkowej bazujących na radiowych pomiarach odległości
PublikacjaNiniejszy artykuł ma na celu ocenę wybranych algorytmów estymacji położenia, które mogą być zastosowane w systemach lokalizacji w środowiskach zamkniętych. Przedstawiono pięć algorytmów bazujących na pomiarach odległości. Następnie porównano ich dokładności estymacji w warunkach statycznych oraz dla scenariusza dynamicznego przy ustalonym rozmieszczeniu trzech stacji referencyjnych. Dokonano również porównania czasu estymacji pojedynczej...
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The hybrid estimation algorithm for wastewater treatment plant robust model predictive control purposes at medium time scale
PublikacjaThe paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters...
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Bezczujnikowe sterowanie trakcyjnym silnikiem IPMSM małej mocy
PublikacjaThis paper describes an algorithm for estimation of IPMSM angular rotor position. The algorithm uses derivatives of motor phase currents resulting from PWM modulation to obtain the rotor position. Control of the IPMSM electromagnetic torque requires a precise estimation of the rotor angular position throughout the wide speed range. This involves using a set of estimation methods switched with the dependence on the actual rotor...
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublikacjaIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Identification of quasi-periodically varying systems with quasi-linear frequency changes
PublikacjaThe problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of system parameter estimation can be increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithms can...
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Sensorless induction motor drive with voltage inverter and sine-wave filter
PublikacjaThis paper presents a speed sensorless control system of an induction motor with an output LC filter. It is known that the parameters design of the filter gives sine wave motor supply voltage but complicates control and estimation process. The reason is that the voltage drop and phase shift between filter input and output signals are imposed, and hence the motor voltages and currents differ from the inverter output waveforms. To...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Optimally regularized local basis function approach to identification of time-varying systems
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state of the art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Superresolution algorithm to video surveillance system
PublikacjaAn application of a multiframe SR (superresolution) algorithm applied to video monitoring is described. The video signal generated by various types of video cameras with different parameters and signal distortions which may be very problematic for superresolution algorithms. The paper focuses on disadvantages in video signal which occur in video surveillance systems. Especially motion estimation and its influence on superresolution...
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An optimised placement of the hard quality sensors for a robust monitoring of the chlorine concentration in drinking water distribution systems
PublikacjaThe problem of an optimised placement of the hard quality sensors in drinking water distribution systemsunder several water demand scenarios for a robust monitoring of the chlorine concentration is formulatedin this paper. The optimality is understood as achieving a desired trade off between the sensors and theirmaintenance costs and the accuracy of estimation of the chlorine concentration. The contribution of thiswork is a comprehensive...
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New Approach to Noncasual Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
PublikacjaIn this technical note, we consider the problem of finite-interval parameter smoothing for a class of nonstationary linear stochastic systems subject to both smooth and abrupt parameter changes. The proposed parallel estimation scheme combines the estimates yielded by several exponentially weighted basis function algorithms. The resulting smoother automatically adjusts its smoothing bandwidth to the type and rate of nonstationarity...
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Indirect Measurement of Motor Current Derivatives in PMSM Sensorless Drives
PublikacjaMotor current derivatives contain useful information for control algorithms, especially in sensorless electric drives. The measurement of motor current derivatives in electric motors supplied by voltage source inverter can be performed using di/dt transducers. However, in such a solution additional sensors have to be installed, e.g. Rogowski coils. Another approach is to measure current derivatives indirectly – by oversampling...
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublikacjaThe problem of identification of nonstationary systems using noncausal estimation schemes is consid-ered and a new class of identification algorithms, combining the basis functions approach with localestimationtechnique,isdescribed.Unliketheclassicalbasisfunctionestimationschemes,theproposedlocal basis function estimators are not used to obtain interval approximations of the parametertrajectory, but provide a sequence of point...
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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublikacjaThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublikacjaGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can...
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Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive
PublikacjaThis paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations...
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On the instantaneous frequency smoothing for signals with quasi-linear frequency changes
PublikacjaThe problem of estimation of the slowly-varying instantaneous frequency of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using frequency tracking algorithms. It is shown that the accuracy of frequency estimates can be considerably increased if the results yielded by the frequency tracker are further processed using the appropriately designed filters. The resulting frequency...
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New First - Path Detector for LTE Positioning Reference Signals
PublikacjaIn today's world, where positioning applications reached a huge popularity and became virtually ubiquitous, there is a strong need for determining a device location as accurately as possible. A particularly important role in positioning play cellular networks, such as Long Term Evolution (LTE). In the LTE Observed Time Difference of Arrival (OTDOA) positioning method, precision of device location estimation depends on accuracy...
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublikacjaIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Application of dynamic time warping and cepstrograms to text-dependent speaker verification
PublikacjaThis work provides a description of an automatic speaker verification (ASV) system. In particular, it documents the evolution of all individual stages of the proposed ASV system design from the phase of preprocessing to an operational decision making system. The aim of this research was to achieve the system of the best safety and ease of use in view of users. The objective estimation of this target has been accomplished by assessing...
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublikacjaThe paper provides comparison of three different approaches to on-line tuning of generalized adaptive notch filters (GANFs) the algorithms used for identification/tracking of quasi-periodically varying dynamic systems. Tuning is needed to adjust adaptation gains, which control tracking performance of ANF algorithms, to the unknown and/or time time-varying rate of system nonstationarity. Two out ofthree compared approaches are classical...
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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublikacjaThe paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....
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Five-phase induction motor drive with sine-wave filter
PublikacjaThe paper presents closed loop ac drive with 5 phase induction motor operating with voltage source inverter and sine wave filter. The motor supply voltages and currents have sinusoidal shape. For well known adjustable electric drives the field oriented control method with flux and speed co ntrol can be applied. In the presence of output filter both control and estimation algorithms should be modified due to sine wave filter installation....
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Signal conditioning for examination of shallow-water acoustic noise correlation properties
PublikacjaThe article describes the process of signal conditioning for examination of acoustic noise correlation properties in shallow water. Knowledge of these properties is very important for the design processes of passive and active hydroacoustic systems. This paper focuses on the above issue from the point of view of passive sonar. In sonar systems, signal processing algorithms operate on both useful acoustic signals, and accompanying...
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Automatic Optimization Of Adaptive Notch Filter’s Frequency Tracking
PublikacjaEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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AUTOMATIC OPTIMIZATION OF ADAPTIVE NOTCH FILTER’S FREQUEN CY TRACKING
PublikacjaEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Speech codec enhancements utilizing time compression and perceptual coding
PublikacjaA method for encoding wideband speech signal employing standardized narrowband speech codecs is presented as well as experimental results concerning detection of tonal spectral components. The speech signal sampled with a higher sampling rate than it is suitable for narrowband coding algorithm is compressed in order to decrease the amount of samples. Next, the time-compressed representation of a signal is encoded using a narrowband...
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Analiza i badania systemu antyspoofingowego GPS
PublikacjaArtykuł dotyczy problemu spoofingu w systemie GPS, polegającego na niepowołanej transmisji sygnałów imitujących sygnały odbierane z satelitów GPS. Takie działanie prowadzi do wyznaczenia przez odbiornik nawigacyjny nieprawidłowego położenia, prędkości i czasu. Zostały opisane metody przeciwdziałania spoofingowi, w szczególności poprzez przestrzenne przetwarzanie sygnałów. Przedstawiono wyniki badań symulacyjnych efektywności tych...
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Determination of API content in a pilot-scale blending by near-infrared spectroscopy as a first step method to process line implementation
PublikacjaNear infrared (NIR) spectroscopy was used for estimation of powder blend homogeneity and manufacturing control of a medicinal product powder mixture containing active pharmaceutical ingredient (API). Aiming at initiating a Process Analytical Technology (PAT) activity, the first step was a stationary mode atline evaluation. In this, the content of pharmaceutical active compound in the powder mixtures intended to the direct tabletting...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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A new diagnostic method for evaluation of cardiosurgery wound healing
PublikacjaOne of important and still unsolved problems in medicine is the question of objective and quantitative evaluation of post-surgery wound healing. The aim of this research is to analyse possibility and value of using the newly elaborated infrared imaging procedure – Active Dynamic Thermography (ADT) – for quantitative description of wound healing processes in cardiosurgery. Both, classical thermal figures of merit as well as ADT...
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From the multiple frequency tracker to the multiple frequency smoother
PublikacjaThe problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Sensor Position Estimation Method for IoT Using Mobile Reference Node
PublikacjaThe paper proposes an innovative method of locating objects for the Internet of Things (IoT). The proposed method allows the position of a fixed measuring sensor (MS) to be estimated using one mobile base station with a known position moving around the MS. The mathematical analysis of the method, and three algorithms — Newton’s (NA), gradient descent (GD) and genetic (GA) — for solving the system of non-linear positional equations...
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Application of the Msplitmethod for filtering airborne laser scanning data-sets to estimate digital terrain models
PublikacjaALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublikacjaALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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A simple way of increasing estimation accuracy of generalized adaptive notch filters
PublikacjaGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. It is shown that frequency biases, which arisein generalized adaptive notch filtering algorithms, can be significantly reduced by incorporating in the adaptive loop an appropriately chosen decision delay. The resulting performance...
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Backscattering properties of southern Baltic herring
PublikacjaReliable TS(L) relationship is required to improve acoustic algorithms of abundanceestimation of Baltic herring. The relationships, empirically obtained in different parts of theBaltic Sea, produce up to 8 dB – difference in the herring TS. In order to develop an accurateTS(L) relationship, it is important to analyze factors controlling the TS variability. Thepossible impact of the regional difference...
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Speed sensorless induction motor drive with predictive current controller
PublikacjaToday, speed sensorless modes of operation are becoming standard solutions in the area of electric drives. This paper presents a speed sensorless control system of an induction motor with a predictive current controller. A closed-loop estimation system with robustness against motor parameter variation is used for the control approach. The proposed algorithm has been implemented using field-programmable gate arrays (FPGAs) and a...
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Analysis of data fusion algorithms for the vessel with the dynamic positioning system
PublikacjaThe dynamic positioning (DP) system on the vessel is operated to control the position and heading of the vessel with the use of propellers and thrusters installed on the board. On DP vessels redundant measurement systems of position, heading and the magnitude and direction of environmental forces are required for safety at sea. In this case, a fusion of data is needed from individual measurement devices. The article proposes a...
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Survey on fuzzy logic methods in control systems of electromechanical plants
PublikacjaРассмотрены алгоритмы управления электромеханическими системами с использованием теории нечеткой логики, приводятся основные положения их синтеза, рассматриваются методы анализа их устойчивости на основе нечетких функций Ляпунова. Эти алгоритмы чаще всего реализуются в виде различных регуляторов, применение которых целесообразно в системах, математическая модель которых не известна, не детерминирована или является строго нелинейной,...
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Compact global association based adaptive routing framework for personnel behavior understanding
PublikacjaPersonnel behavior understanding under complex scenarios is a challenging task for computer vision. This paper proposes a novel Compact model, which we refer to as CGARPN that incorporates with Global Association relevance and Adaptive Routing Pose estimation Network. Our framework firstly introduces CGAN backbone to facilitate the feature representation by compressing the kernel parameter space compared with typical algorithms,...
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Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?
PublikacjaThe estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...
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IEEE Information Theory Workshop on Detection, Estimation, Classification and Imaging
Konferencje -
Remote measurement of building usable floor area - Algorithms fusion
PublikacjaRapid changes that are taking place in the urban environment have significant impact on urban growth. Most cities and urban regions all over the world compete to increase resident and visitor satisfaction. The growing requirements and rapidity of introducing new technologies to all aspects of residents' lives force cities and urban regions to implement "smart cities" concepts in their activities. Real estate is one of the principal...
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Hierarchical predictive control of integrated wastewater treatment systems
PublikacjaThe paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater...
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublikacjaW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublikacjaPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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Time-frequency analysis in optical coherence tomography for technical objects examination
PublikacjaOptical coherence tomography (OCT) is one of the most advanced optical measurement techniques for complex structure visualization. The advantages of OCT have been used for surface and subsurface defect detection in composite materials, polymers, ceramics, non-metallic protective coatings, and many more. Our research activity has been focused on timefrequency spectroscopic analysis in OCT. It is based on time resolved spectral analysis...
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Rapid Yield Optimization of Miniaturized Microwave Passives by Response Features and Variable-Fidelity EM Simulations
PublikacjaThe operation of high-frequency devices, including microwave passive components, can be impaired by fabrication tolerances but also incomplete knowledge concerning operating conditions (temperature, input power levels) and material parameters (e.g., substrate permittivity). Although the accuracy of manufacturing processes is always limited, the effects of parameter deviations can be accounted for in advance at the design phase...
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Zintegrowane sterowanie systemami zaopatrzenia w wodę pitną
PublikacjaOptymalne ekonomicznie zaspokojenie w miastach bieżącego zapotrzebowania na wodę pitną tak, aby spełnione były wymagania jakości dostaw oraz jakości samej wody jest złożonym zadaniem. Zarówno aspekty aplikacyjne jak i teoretyczne tego problemu są przedmiotem intensywnych prac prowadzanych w sektorach naukowych i przemysłowych na całym świecie. Prace te finansowane są przez przemysł, komitety naukowe oraz Programy Ramowe Unii Europejskiej....
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A system for Direction-Of-Arrival estimation in ISM 2.4 GHz frequency band based on ESPAR antenna and SDR technology
PublikacjaDetermination of the direction of the signal arrival (DOA) finds many applications in various areas of science and industry. Knowledge of DOA is used, among others to determine the position of a satellite with a low Earth orbit (LEO), localization of people and things as well as in research of wireless communication systems, for instance the determination of the number of...
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SkinDepth - synthetic 3D skin lesion database
Dane BadawczeSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Broken Rotor Symptons in the Sensorless Control of Induction Machine
PublikacjaInverter fed sensorless controlled variable speed drives with induction machine are widely used in the industry applications, also in wind power generation and electric vehicles. On-line self diagnostic systems implementation is needed for early stage fault detection and avoiding a critical fault. Diagnostic algorithms in modern DSP-based controllers can operate simultaneously with control system functions. In the closed-loop controlled...
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Computer controlled systems - 2022/2023
Kursy Onlinemateriały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution...
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CCS-lecture-2023-2024
Kursy Onlinemateriały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution optimization...
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Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublikacjaGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient...
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Multistage generalized adaptive notch filter with improved accuracy
PublikacjaGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of the coefficient estimates. The paper proposes a novel multistage GANF with accuracy improved in this aspect. The processing pipeline consists of three stages. The preliminary...
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Paweł Burdziakowski dr inż.
Osobydr inż. Paweł Burdziakowski jest specjalista w zakresie fotogrametrii i teledetekcji lotniczej niskiego pułapu, nawigacji morskiej i lotniczej. Jest również licencjonowanym instruktorem lotniczym oraz programistą. Głównymi obszarami zainteresowania jest fotogrametria cyfrowa, nawigacja platform bezzałogowych oraz systemy bezzałogowe, w tym lotnicze, nawodne, podwodne. Prowadzi badania w zakresie algorytmów i metod poprawiających...