On structure identification of parallel Wiener-Hammerstein models

Abstract

In this paper, models composed of parallel branches of the Wiener-Hammerstein type are studied. Using a zero-mean stationary white Gaussian sequence as input to such models, their structure can be identified by considering the bispectrum of the output sequence. Simulation examples are included to illustrate the results of the pape

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