System identification using a linear combination of cumulant slices
Contribuinte(s) |
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
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Data(s) |
10/05/2012
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Resumo |
In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods. Peer reviewed |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
Direitos |
Consulteu les condicions d'ús d'aquest document en el repositori original:<a href="http://hdl.handle.net/2117/1562">http://hdl.handle.net/2117/1562</a> |
Palavras-Chave | #Àrees temàtiques de la UPC::Enginyeria electrònica i telecomunicacions::Processament del senyal #Signal processing #Statistical analysis #Colored Gaussian noise #Cumulant slices #Impulse response #Linear approach #Moving average model #NonGaussian process #Numerical conditioning #Output statistics #Parameter estimation #Signal processing #Spectral analysis #Statistical analysis #System identification #FIR systems #Processament del senyal #Simulació de processos |
Tipo |
info:eu-repo/semantics/article |