Review article: Identification of quadratic systems using higher order cumulants and neural networks: Application to model the delay of video-packets transmission

Authors:
J. Antari;S. Chabaa;R. Iqdour;A. Zeroual;S. Safi
Affiliations:
Ibn Zohr University, 32/S Agadir 80000, Morocco and Electronic and Instrumentation Laboratory, Department of Physics, Faculty of Science Semlalia, Cadi Ayyad University, Po. Box 2390, Marrakesh 40 ...;Electronic and Instrumentation Laboratory, Department of Physics, Faculty of Science Semlalia, Cadi Ayyad University, Po. Box 2390, Marrakesh 40001, Morocco;Electronic and Instrumentation Laboratory, Department of Physics, Faculty of Science Semlalia, Cadi Ayyad University, Po. Box 2390, Marrakesh 40001, Morocco;Electronic and Instrumentation Laboratory, Department of Physics, Faculty of Science Semlalia, Cadi Ayyad University, Po. Box 2390, Marrakesh 40001, Morocco;Sultane Moulay Slimane University, Faculty Polydisciplinary Beni Mellal, Morocco
Venue:
Applied Soft Computing
Year:
2011

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Abstract

This work concerns the development of two approaches for the identification of diagonal parameters of quadratic systems from only the output observation. The systems considered are excited by an unobservable independent identically distributed (i.i.d), stationary zero mean, non-Gaussian process and corrupted by an additive Gaussian noise. The proposed approaches exploit higher order cumulants (HOC) (fourth order cumulants) and are the extension of the algorithms developed in the linear version 1D, which uses a non-Gaussian signal input. For test and validity purpose, these approaches are compared to recursive least square (RLS), least mean square (LMS) and neural network identification algorithms using non-linear model in noisy environment. To demonstrate the applicability of the theoretical methods on real processes, we applied the developed approaches to search for models able to describe the delay of the video-packets transmission over IP networks from video server. The simulation results show the correctness and the efficiency of the developed approaches.