Search results for: identification of a nonstationary stochastic system
-
On noncausal identification of nonstationary stochastic systems
PublicationIn 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 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 its smoothing...
-
On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn 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...
-
Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublicationThe problem of identification of a linear nonsta-tionary stochastic process is considered and solved using theapproach based on functional series approximation of time-varying parameter trajectories. The proposed fast basis func-tion estimators are computationally attractive and yield resultsthat are better than those provided by the local least squaresalgorithms. It is shown that two...
-
Locally-adaptive Kalman smoothing approach to identification of nonstationary stochastic systems
Publication -
Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublicationOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
-
New approach to noncausal identification of nonstationary stochastic systems subject to both smooth and abrupt parameter changes
PublicationIn this paper we consider the problem of finiteintervalparameter smoothing for a class of nonstationary linearstochastic systems subject to both smooth and abrupt parameterchanges. The proposed parallel estimation scheme combines theestimates yielded by several exponentially weighted basis functionalgorithms. The resulting smoother automatically adjustsits smoothing bandwidth to the type and rate of nonstationarityof the identified...
-
New Approach to Noncasual Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
PublicationIn 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...
-
Local basis function estimators for identification of nonstationary systems
PublicationThe problem of identification of a nonstationary stochastic system is considered and solved using local basis function approximation of system parameter trajectories. Unlike the classical basis function approach, which yields parameter estimates in the entire analysis interval, the proposed new identification procedure is operated in a sliding window mode and provides a sequence of point (rather than interval) estimates. It is...
-
A new look at the statistical identification of nonstationary systems
PublicationThe paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...
-
Towards Robust Identification of Nonstationary Systems
PublicationThe article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement noise and against the numerical errors that may occur at the first stage of identification. We also propose an adaptive algorithm to optimize the values of the hyperparameters that are crucial for this new method.
-
On the preestimation technique and its application to identification of nonstationary systems
PublicationThe problem of noncausal identification of a nonstationary stochastic FIR (finite impulse response) sys- tem is reformulated, and solved, as a problem of smoothing of preestimated parameter trajectories. Three approaches to preestimation are critically analyzed and compared. It is shown that optimization of the smoothing operation can be performed adaptively using the parallel estimation technique. The new approach is computationally...
-
Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublicationThe 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...
-
On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
-
Generalized Savitzky–Golay filters for identification of nonstationary systems
PublicationThe 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...
-
Local basis function method for identification of nonstationary systems
PublicationThis thesis is focused on the basis function method for the identification of nonstationary processes. The first chapter describes a group of models that can be identified using the basis function method. The next chapter describes the basic version of the basis function method, including its algebraic and statistical properties. The following section introduces the local basis function (LBF) method: its properties are described...
-
Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublicationThe 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...
-
On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
-
Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe 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,...
-
Generalized adaptive comb filters/smoothers and their application to the identification of quasi-periodically varying systems and signals
PublicationThe problem of both causal and noncausal identification of linear stochastic systems with quasiharmonically varying parameters is considered. The quasi-harmonic description allows one to model nonsinusoidal quasi-periodic parameter changes. The proposed identification algorithms are called generalized adaptive comb filters/smoothers because in the special signal case they reduce down to adaptive comb algorithms used to enhance...
-
System identification 2023/24 - project
e-Learning CoursesThis is the project part of the System Identification subject.
-
System identification
e-Learning CoursesThe course focusses on the problem of identification of dynamic systems.
-
System identification - new
e-Learning CoursesThe course focusses on the problem of identification of dynamic systems.
-
System identification 2021/22 - project
e-Learning Courses -
System identification 2022/23 - project
e-Learning Courses -
Asynchronous Networked Estimation System for Continuous Time Stochastic Processes
PublicationIn this paper we examine an asynchronous networked estimation system for state estimation of continuous time stochastic processes. Such a system is comprised of several estimation nodes connected using a possibly incomplete communication graph. Each of the nodes uses a Kalman filter algorithm and data from a local sensor to compute local state estimates of the process under observation. It also performs data fusion of local estimates...
-
Mathematical model to assess energy consumption using water inflow-drainage system of iron-ore mines in terms of a stochastic process
PublicationPurpose is to develop a unified mathematical model to assess energy efficiency of a water inflow-drainage process as the real variant of stochastic method for water pumping from underground workings of iron-ore mines. Methods. The research process was based upon the methods of probability theory as well as stochastic modelling methods. The stochastic function integration has been reduced to summation of its ordinates and further...
-
An automatic system for identification of random telegraph signal (RTS) noise in noise signals
PublicationIn the paper the automatic and universal system for identification of Random Telegraph Signal (RTS) noise as a non-Gaussian component of the inherent noise signal of semiconductor devices is presented. The system for data acquisition and processing is described. Histograms of the instantaneous values of the noise signals are calculated as the basis for analysis of the noise signal to determine the number of local maxima of histograms...
-
System of wireless magnetic sensors for detection and identification of ferromagnetic vehicles
PublicationThe paper presents the results of deformation of the Earth's magnetic field by land vehicles. Basing on the analysis of the shape of the magnetic field deformation, it is possible to detect and identify a vehicle. In order to eliminate the interference of the Earth's magnetic field by the environment, the measurements were performed in a differential configuration. Under a development project a wireless system of magnetic sensors...
-
Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
-
Fake News: Possibility of Identification in Post-Truth Media Ecology System
PublicationInformation comes as basic good which affects social well-being. A modern society and a modern state – its administration, education, culture, national economy and armed forces – cannot function efficiently without a rationally developed field of information. The quality of the functioning of that system depends on a specific feature of information, that is namely: its reliability which makes it possible for us to evaluate accuracy,...
-
Simple Millimeter Wave Identification System Based on 60 GHz Van Atta Arrays
PublicationThe paper presents a proof-of-concept of a millimeter-wave identification system based on Van Atta array tags in the 60 GHz band. For interrogation of the tags, a vector network analyzer and a measurement transceiver were employed in alternative test configurations. The design, fabrication and measurements of co- and cross-polarized Van Atta arrays are presented in the paper. They can be treated as simple chipless RFID tags with...
-
Artur Gańcza dr inż.
PeopleI received the M.Sc. degree from the Gdańsk University of Technology (GUT), Gdańsk, Poland, in 2019. I am currently a Ph.D. student at GUT, with the Department of Automatic Control, Faculty of Electronics, Telecommunications and Informatics. My professional interests include speech recognition, system identification, adaptive signal processing and linear algebra.
-
Seidel–Herzel model of human baroreflex in cardiorespiratory system with stochastic delays
Publication -
Evaluation of possibilities in identification and susceptibility testing for Candida glabrata clinical isolates with the Integral System Yeast Plus (ISYP)
PublicationThe aim of this study was to evaluate possibilities of correct identification and susceptibility testing of C. glabrata clinical isolates with Integral System Yeast Plus (ISYP). For species identification, as the reference method, API Candida test and species-specific PCR reactions were used. The potential of antifungal susceptibility testing by the ISYP test was compared with the Sensititre Yeast One. Whilst the reference methods...
-
Automatic Identification System (AIS) Dynamic Data Integrity Monitoring and Trajectory Tracking Based on the Simultaneous Localization and Mapping (SLAM) Process Model
PublicationTo enhance the safety of marine navigation, one needs to consider the involvement of the automatic identification system (AIS), an existing system designed for ship-to-ship and shipto- shore communication. Previous research on the quality of AIS parameters revealed problems that the system experiences with sensor data exchange. In coastal areas, littoral AIS does not meet the expectations of operational continuity and system availability,...
-
Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublicationThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
-
Optical glyphs based localization and identification system
PublicationThe paper presents a description of functioning of a platform supporting the detection of obstructive diseases in the respiratory system education process. A 16-parameter model of the respiratory system simulated in the MATLAB/Simulink environment was set in the role of the tested patient. It has been linked to the control layer, developed in the LabVIEW environment, using the SIT library (Simulation Interface Toolkit). This layer...
-
Impact of sea wave stochastic characteristics on ship propulsion control system design.
PublicationWybrano do rozważań (symulacji komputerowej) 8 rejonów morskich w 4 porach roku. Określono w nich gęstość widmową amplitudy fali morskiej. Założono, upraszczająco, regulator typu PID. Dla wybranego typu statku wykonane badania symulacyjne odnoszą się do wybranych rejonów mórz i pór roku. Okazuje się, że dobierając zarówno współczynnik wzmocnienia regulatora jak i stałą całkowania, można minimalizować wartości wariancji, na przykład,...
-
Zdzisław Kowalczuk prof. dr hab. inż.
PeopleZdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...
-
Method of identification of the slide tribological system top layer condition by assessment of the t-02 four-ball tester friction node operation
Publicationa method is proposed of the assessment of t-02 four-ball tester friction node operation during extreme unit loads on the tribological system for identification of the top layer condition in that system lubricated with the tested lubricating oil. by identification of the friction node with a thermodynamic system, that operation is treated as an energy generating process of the created servo-layer structure. the friction node operation...
-
Identification of regions of interest in video for a traffic monitoring system
PublicationA system for automatic event detection in the camera image is presented in this paper. A method of limiting a region of interest to relevant parts of the image using a set of processing procedures is proposed. Image processing includes object detection with shadow removal performed in the modified YCbCr color space instead of RGB. The proposed procedures help to reduce the complexity of image processing algorithm and result in...
-
Identification of regions of interest in video for a traffic monitoring system
Publication -
The system for identification of the band saw wheel cross profile
PublicationPrzedstawiono system do identyfikacji zarysu poprzecznego koła pilarki taśmowej, dzięki któremu producent pił taśmowych ma możliwość naprężenia brzeszczotu piły w sposób zapewniający jej poprawną pracę. Opisano budowę i zasadę działania systemu. Uzyskane dane mogą być wprowadzane do układów sterowania automatycznych urządzeń ze sterowaniem CNC (naprężających piły taśmowe). Dane systemu: szerokość sprawdzanych kół do 300 mm, dokładność...
-
Cavity parameters identification for TESLA control system development
Publication -
Model-based identification of the dominant N2O emission pathway in a full-scale activated sludge system
PublicationActivated sludge models (ASMs), extended with an N2O emission module, are powerful tools to describe the operation of full-scale wastewater treatment plants (WWTPs). Specifically, such models can investigate the most contributive N2O production pathways and guide towards N2O and carbon footprint (CF) mitigation measures. A common practice is to develop and validate models using data from a single WWTP. In this study, a successfully...
-
Radar and Automatic Identification System Track Fusion in an Electronic Chart Display and Information System
Publication -
A video monitoring system using ontology-driven identification of threats
PublicationIn this paper, we present a video monitoring systemthat leverages image recognition and ontological reasoningabout threats. In the solution, an image processing subsystemuses video recording of a monitored area and recognizesknown concepts in scenes. Then, a reasoning subsystem uses anontological description of security conditions and informationfrom image recognition to check if a violation of a conditionhas occurred. If a threat...
-
Continuous-time delay system identification insensitive to measurement faults
PublicationW pracy wykorzystuje się algorytmy identyfikacji do estymacji parametrów systemów ciągłych z opóźnieniem. Zastosowanie filtrów całkujących ze skończonym horyzontem obserwacji pozwala przekształcić równanie różniczkowe opisujące system ciągły do użytecznej postaci regresyjnej z czasem dyskretnym. Uzyskany w ten sposób i zachowujący oryginalną parametryzację model dyskretny daje się identyfikować stosując klasyczną metodę najmniejszych...
-
Hardware Implementation of Real Time Cavity Parameters Identification System
Publication -
IoT-Based Smart Monitoring System Using Automatic Shape Identification
Publication