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Search results for: identification of nonstationary processes determination of estimation bandwidth model order selection
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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
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,...
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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...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...
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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.
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe 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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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe 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 results on estimation bandwidth adaptation
PublicationThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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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...
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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...
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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...
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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...
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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...
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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On autoregressive spectrum estimation using the model averaging technique
PublicationThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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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...
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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...
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Analiza właściwości rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationRozszerzony obserwator prędkości został zaproponowany przez prof. Krzemińskiego i jest oparty na rozszerzonym modelu maszyny indukcyjnej, gdzie wprowadzona został nowa zmienna ζ. Jest to nowe podejście do estymacji zmiennych stanu maszyny indukcyjnej i nie wszystkie problemy zostały do tej pory rozwiązane. Zaproponowano wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień obserwatora. W celu redukcji nakładów obliczeniowych...
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COMPOSITE MATERIAL SELECTION FOR A PATIENT TRANSFER ASSIST DEVICE
PublicationLaminates - layered composites containing at least two elements (matrix and reinforcement) widely used in industry have also found their usage in medicine. Their main feature is the ability to modify the material in order to obtain the required properties. Depending on the needs, we can modify reinforcement, type of resin or the method of bonding substrates. Commonly used fibers are: carbon fiber, glass and aramid fibers; resins...
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Ocena zasobów oraz weryfikacja granic obszaru ochronnego GZWP nr 133 Młotkowo za pomocą numerycznego modelu przepływu wód podziemnych
PublicationModel Głównego Zbiornika Wód Podziemnych powstał w celu dokonania oceny dostępnych zasobów wód oraz zweryfikowania granic strefy ochronnej. GZWP Młotkowo jest położony w południowej części Pojezierza Krajeńskiego. Ze względu na konieczność weryfikacji granic zbiornika wyznaczonych przez Kleczkowskiego i in. (1990) do badań modelowych przyjęto obszar cztery razy większy niż rozmiar GZWP. W celu osiągnięcia najbardziej wiarygodnych...
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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.
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Automated Reduced Model Order Selection
PublicationThis letter proposes to automate generation of reduced-order models used for accelerated -parameter computation by applying a posteriori model error estimators. So far,a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select...
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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublicationThe problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.
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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...
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Multiple access in ad-hoc wireless LANs with noncooperative stations
PublicationA class of contention-type MAC protocols (e.g., CSMA/CA) relies on random deferment of packet transmission, and subsumes a deferment selection strategy and a scheduling policy that determines the winner of each contention cycle. This paper examines contention-type protocols in a noncooperative an ad-hoc wireless LAN setting, where a number of stations self-optimise their strategies to obtain a more-than-fair bandwidth share. Two...
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SZACOWANIE ZAWARTOŚCI BENZO(a)PIRENU W PYLE ZAWIESZONYM PM10 W AGLOMERACJI TRÓJMIEJSKIEJ ZA POMOCĄ WIELOWYMIAROWEJ REGRESJI LINIOWEJ=ESTIMATION OF BENZO(A)PYRENE CONTENT IN SUSPENDED DUST PM10 IN TRI-CITY AGGLOMERATION USING MULTIDIMENSIONAL LINEAR REGRESSION
PublicationW pracy przedstawiono próbę oszacowania przy pomocy wielowymiarowej regresji liniowej modelu empirycznego opisującego czynniki wpływające na zawartość B(a)P w pyle zawieszonym PM10 w Aglomeracji Trójmiejskiej w latach 2008-2011. Na przestrzeni tych lat średnioroczne stężenie B(a)P w PM10 wzrosło ponad dwukrotnie i ponad trzykrotnie przewyższa poziom docelowy. Z przeprowadzonych analiz wynika, że główną przyczyną wzrostu stężenia...
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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...
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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...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublicationAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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Study of probe signal bandwidth influence on estimation of coherence bandwidth for underwater acoustic communication channel
PublicationA signal transmitted in a shallow Underwater Acoustic Communication (UAC) channel suffers from time dispersion due to the multipath propagation and the refraction phenomena. This causes intersymbol interference of the received signal and frequency-selective fading observed in its spectrum. Coherence bandwidth is one of the key transmission parameters used for designing the physical layer of a data transmission system to minimise...
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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...
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Numerically Efficient Miniaturization-Oriented Optimization of an Ultra-Wideband Spline-Parameterized Antenna
PublicationDesign of ultra-wideband radiators for modern handheld applications is a challenging task that involves not only selection of an appropriate topology, but also its tuning oriented towards balancing the electrical performance and size. In this work, a low-cost design of a compact, broadband, spline-parameterized monopole antenna has been considered. The framework used for the structure design implements trust-region-based methods,...
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Identification of Unstable Reference Points and Estimation of Displacements Using Squared Msplit Estimation
PublicationThe article presents a new version of the method for estimating parameters in a split functional model, which enables the determination of displacements of geodetic network points with constrained datum. The main aim of the study is to present theoretical foundations of Msplit CD estimation and its basic properties and possible applications. Particular attention was paid to the efficacy of the method in the context of geodetic...
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Automatic Reduction-Order Selection for Finite-Element Macromodels
PublicationAn automatic reduction-order selection algorithm for macromodels in finite-element analysis is presented. The algorithm is based on a goal-oriented a posteriori error estimator that operates on low-order reduced blocks of matrices, and hence, it can be evaluated extremely quickly.
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Using Fast Frequency Hopping Technique to Improve Reliability of Underwater Communication System
PublicationAcoustic underwater communication systems designed to work reliably in shallow coastal waters must overcome major limitations such as multipath propagation and the Doppler effect. These restrictions are the reason for the complexity of receivers being built, whose task is to decode a symbol on the basis of the received signal. Additional complications are caused by the low propagation speed of the acoustic wave in the water and...
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Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
PublicationA comparative analysis of various visual descriptors is presented in this chapter. The descriptors utilize many aspects of image data: colour, texture, gradient, and statistical moments. The descriptor list is supplemented with local features calculated in close vicinity of key points found automatically in the image. The goal of the analysis is to find descriptors that are best suited for particular task, i.e. re-identification...
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Application of TOPSIS for Selection and Assessment of Analytical Procedures for Ibuprofen Determination in Wastewater
PublicationThis paper describes the possible implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as green analytical chemistry metrics tools. TOPSIS is one of the multi-criteria decision analysis (MCDA) tools that is applied in the selection of the best alternative from many possible. In this case we have applied it to assess the nineteen analytical procedures for ibuprofen determination in wastewater...
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Detection, identification and determination of chiral pharmaceutical residues in wastewater: Problems and challenges
PublicationChiral pharmaceuticals (CPs) are widely used in different areas of human life, thus they are frequentlydetected in different ecosystems. However, before CPs reach the environment, wastewater is subjected todifferent treatment processes in order to remove them. Nevertheless, such processes may affect thechirality of CPs, thus it is very important to monitor CP levels during the wastewater treatment.This review addresses the present...
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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...
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Estimation of Coherence Bandwidth for Underwater Acoustic Communication Channel
PublicationA shallow underwater acoustic communication channel is characterized by strong multipath propagation. The signal reaching the receiver consists of a direct waveform and a number of its delayed and suppressed replica. A significant time dispersion of the transmitted signal and selective fading of its spectrum are observed. Coherence bandwidth defines maximal bandwidth, wherein the channel amplitude characteristic remains constant...
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Bandwidth-Controllable Third-Order Band Pass Filter Using Substrate Integrated Full- and Semi-Circular Cavities
PublicationThe article presents a novel circular substrate integrated waveguide (SIW) bandpass filter (BPF) with controllable bandwidth. The proposed BPF is configured using two microstrip feedlines, semi- circular SIW cavities, capacitive slots, and inductive vias. The circular cavity is bisected into two halves, with the two copies thereof being cascaded. Two bisected and cascaded structures obtained this way are subsequently connected...
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Study on the time-frequency analysis of nonstationary, electrochemical and corrosion processes
PublicationW pracy przedstawiono możliwości zastosowania czasowo-częstotliwościowych metod analizy sygnałów do badania niestacjonarnych procesów elektrochemicznych, chemicznych i korozyjnych. Wnikliwej analizie z wykorzystaniem metod STFT, rozkładu Wignera-Ville'a oraz przekształceń z klasy Cohena poddano rejestry oscylacji chemicznych, elektrochemicznych i rejestry korozji wżerowej.
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Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism
PublicationIn this study, we used company level administrative data from the National Labour Inspectorate and The Polish Social Insurance Institution in order to estimate the prevalence of informal employment in Poland in 2016. Since the selection mechanism is non‐ignorable, we employed a generalization of Heckman’s sample selection model assuming non‐Gaussian correlation of errors and clustering by incorporation of random effects. We found...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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The Use of Free Adjustment and Msplit-Estimation for Determination of the Vertical Displacements in Unstable Reference System
PublicationThe problem of the determining of the displacements of engineering objects and their surroundings is the current and important issue in the field of engineering geodesy. Most control measurements are made in relation to reference points (stable points). On the other hand, sometimes it happens that it is not possible perform the measurements with reference to the stable points or identification of stable points is difficult. Therefore,...
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Reduced order model of 2d system
PublicationA new method of modelling is developed for static and dynamic analysis of two-dimensional elastic bodies. In the analysis, an elastic body is divided into strips. For each one-dimensional strip the reduced modal model is build up. The modal model contains appropriate number of inputs and outputs to connect lumped interaction that occur between strips. Proposed method of modelling enables to obtain more accurate and more simple...
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Robust identification of quadrocopter model for control purposes
PublicationThe paper addresses a problem of quadrotor unmanned aerial vehicle (so-called X4-flyer or quadrocopter) utility model identification for control design purposes. To that goal the quadrotor model is assumed to be composed of two abstracted subsystems, namely a rigid body (plant) and four motors equipped with blades (actuators). The model of the former is acquired based on a well-established dynamic equations of motion while the...
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Identification and non-integer order modelling of synchronous machines operating as generator
PublicationThis paper presents an original mathematical model of a synchronous generator using derivatives of fractional order. In contrast to classical models composed of a large number of R-L ladders, it comprises half-order impedances, which enable the accurate description of the electromagnetic induction phenomena in a wide frequency range, while minimizing the order and number of model parameters. The proposed model takes into account...
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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Experience-Driven Model of Decision-Making Processes in Project Teams
PublicationThis article presents a model of decision-making processes in project teams. Project teams constitute a specific type of organization appointed to implement a project. Decisions made by project teams result from the methods of project management and best management practices. The authors have undertaken the task of formalizing these processes using the classical method of constructing decision trees. It has been established that...