Search results for "linear process"

showing 4 items of 4 documents

A more efficient second order blind identification method for separation of uncorrelated stationary time series

2016

The classical second order source separation methods use approximate joint diagonalization of autocovariance matrices with several lags to estimate the unmixing matrix. Based on recent asymptotic results, we propose a novel unmixing matrix estimator which selects the best lag set from a finite set of candidate sets specified by the user. The theory is illustrated by a simulation study. peerReviewed

affine equivarianceminimum distance indexSOBIasymptotic normalityjoint diagonalizationlinear process
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Adaptive Type-2 Fuzzy Logic Control of Non-Linear Processes

2011

The main objective of this study is to provide a valid and effective approach for the design and development of an adaptive type-2 fuzzy controller (AT2FLC), based on the analysis of the nonlinear process dynamics and the use of an ANFIS technique for the optimization of the controller. The performance of the obtained AT2FLC, characterized by a few number of rules, is higher than the performance of a traditional type-2 fuzzy controller with a larger rule base. The proposed controller is particurarly suitable for the control of processes characterized by uncertainty and time varying parameters.

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi Chimicilcsh:Computer engineering. Computer hardwareComputingMethodologies_DOCUMENTANDTEXTPROCESSINGAdaptive controllcsh:TP155-156Non-linear processeslcsh:TK7885-7895Adaptive control; Type-2 fuzzy control;Non-linear processesType-2 fuzzy controllcsh:Chemical engineeringComputingMilieux_MISCELLANEOUSComputingMethodologies_COMPUTERGRAPHICS
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A more efficient second order blind identification method for separation of uncorrelated stationary time series

2016

The classical second order source separation methods use approximate joint diagonalization of autocovariance matrices with several lags to estimate the unmixing matrix. Based on recent asymptotic results, we propose a novel unmixing matrix estimator which selects the best lag set from a finite set of candidate sets specified by the user. The theory is illustrated by a simulation study.

Statistics and ProbabilityMathematical optimizationaffine equivarianceminimum distance indexasymptotic normalityAsymptotic distributionlinear process01 natural sciencesSet (abstract data type)010104 statistics & probabilityMatrix (mathematics)SOBIComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0502 economics and businessSource separationjoint diagonalization0101 mathematicsFinite set050205 econometrics Mathematicsta112Series (mathematics)05 social sciencesEstimatorAutocovarianceStatistics Probability and UncertaintyAlgorithmStatistics & Probability Letters
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Separation of uncorrelated stationary time series using autocovariance matrices

2014

Blind source separation (BSS) is a signal processing tool, which is widely used in various fields. Examples include biomedical signal separation, brain imaging and economic time series applications. In BSS, one assumes that the observed $p$ time series are linear combinations of $p$ latent uncorrelated weakly stationary time series. The aim is then to find an estimate for an unmixing matrix, which transforms the observed time series back to uncorrelated latent time series. In SOBI (Second Order Blind Identification) joint diagonalization of the covariance matrix and autocovariance matrices with several lags is used to estimate the unmixing matrix. The rows of an unmixing matrix can be deriv…

62H05 62H10Asymptotic Normality ; Blind Source Separation ; Joint Diagonalization ; Linear Process ; SobiFOS: MathematicsMathematics - Statistics TheoryStatistics Theory (math.ST)
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