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Wyniki wyszukiwania dla: local basis function
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Local basis function estimators for identification of nonstationary systems
PublikacjaThe 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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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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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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Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublikacjaThe 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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Fast recursive basis function estimators for identification of time-varying processes
PublikacjaW pracy wprowadzono nową kategorię filtrów adaptacyjnych opartych na metodzie funkcji bazowych i wykorzystujących koncepcję postfiltracji. Proponowane algorytmy pozwalają połączyć niską złożoność obliczeniową i dobre właściwości śledzące.
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Gradient based basis function algorithms for identification of quasi periodically varying processes.
PublikacjaW pracy przedstawiono problem identyfikacji systemów, których parametry zmieniają się w sposób pseudookresowy. Pokazano sposób, w jaki można modelować takie systemy przy zastosowaniu metody harmonicznych funkcji bazowych.Przedstawiono dwa sposoby dekompozycji (struktura szeregowa i równoległa) takich układów na elementy związane z poszczególnymi funkcjami bazowymi. Zaprezentowany został sposób śledzenia częstotliwości funkcji...
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Usage of Two-Center Basis Function Neural Classifiers in Compact Smart Resistive Sensors
PublikacjaA new solution of the smart resistance sensorwith the Two-Center Basis Function (TCBF) neuralclassifier, for which the resistance sensor is a component ofan anti-aliasing filter of an ADC is proposed. Thetemperature measurement procedure is based on excitationof the filter by square impulses, sampling time response ofthe filter and processing measured voltage values by theTCBF classifier. All steps of the measurement procedure...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Two-center radial basis function network for classification of soft faults in electronic analog circuits
PublikacjaW pracy zaproponowano specjalizowaną sieć neuronową z dwucentrowymi radialnymi funkcjami bazowymi (TCRB) neuronów w warstwie ukrytej,przeznaczoną do diagnostyki uszkodzeń parametrycznych układów analogowych. Zastosowanie funkcji TCRB pozwala na znaczne zmniejszenie liczby neuronów w warstwie ukrytej, lepsze dopasowanie do słownika uszkodzeń oraz poprawę dokładności klasyfikacji, w porównaniu z dotychczas stosowaną siecią z jednocentrowymi...
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublikacjaIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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Does system of local government subsidisation fulfil revenue equalisation function? Evidence from Poland
PublikacjaThe article will discuss functions that should pursue general grants. One of them is revenue equalization. To achieve it after applying the mechanism of subsidising revenues should be reduced. In addition, to be completed, the size of the support should be inversely proportional to achieved own revenues. Besides the theoretical analysis, which will present the general grants structure and the ability of fulfilling revenue equalisation...
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Parametrized Local Reduced-Order Models With Compressed Projection Basis for Fast Parameter-Dependent Finite-Element Analysis
PublikacjaThis paper proposes an automated parametric local model-order reduction scheme for the expedited design of microwave devices using the full-wave finite-element method (FEM). The approach proposed here results in parameterized reduced-order models (ROMs) that account for the geometry and material variation in the selected subregion of the structure. In each subregion, a parameter-dependent projection basis is generated by concatenating...
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Local heaviside weighted mlpg meshless method approach to extended flamant problem using radial basis functions
PublikacjaW artykule przedstawiono rozwiązanie uogólnionego zagadnienia Flamanta za pomocą bezsiatkowej metody MLPG z wykorzystaniem funkcji o bazie radialnej. Sprawdzono wydajność metody dla dwóch klas funkcji kształtu: klasycznych funkcji radialnych i lokalnych funkcji radialnych. Porównano wyniki obliczeń oraz przedstawiono wnioski.
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Is It Right To Predict Cutting Forces On The Basis Of Wood Density?
PublikacjaSeveral properties of wood can be correlated to wood density. It is widely accepted that the cutting power requirements are following this general assumption. Therefore, according to classic literature sources available for determination of the cutting power for both band- and circular- sawing machines, the cutting power requirements (and/or cutting forces) are computed as a function of the wood specific gravity SG. It was shown...
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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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On the preestimation technique and its application to identification of nonstationary systems
PublikacjaThe 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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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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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublikacjaThe 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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Regularized identification of fast time-varying systems - comparison of two regularization strategies
PublikacjaThe problem of identification of a time-varying FIR system is considered and solved using the local basis function approach. It is shown that the estimation (tracking) results can be improved by means of regularization. Two variants of regularization are proposed and compared: the classical L2 (ridge) regularization and a new, reweighted L2 one. It is shown that the new approach can outperform the classical one and is computationally...
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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...