Wyniki wyszukiwania dla: ESTIMATION ALGORITHMS
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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...