Use Of Higher-Order Statistics In Signal Processing And System Theory: An Update

Jerry M. Mendel

doi:10.1117/12.948499

23 February 1988 Use Of Higher-Order Statistics In Signal Processing And System Theory: An Update

Jerry M. Mendel

Proceedings Volume 0975, Advanced Algorithms and Architectures for Signal Processing III; (1988) https://doi.org/10.1117/12.948499
Event: 32nd Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1988, San Diego, CA, United States

Abstract

During the past few years there has been an increasing interest in applying higher-order statistics, namely cumulants, and their associated Fourier transforms, polyspectra, to a wide range of signal processing and system theory problems. Cumulants and polyspectra can make a big difference in those problems where signals are non-Gaussian and systems are nonminimum phase (or, nonlinear). This paper provides a brief overview of much of the work that has occurred when parametric models are used in conjunction with higher-order statistics. It covers: identification of MA processes, identification of AR processes, identification of ARMA processes, order determination, calculation of cumulants, calculation of polyspectra, extensions to multi-channel and two-dimensional systems, and applications.

Citation Download Citation

Jerry M. Mendel "Use Of Higher-Order Statistics In Signal Processing And System Theory: An Update", Proc. SPIE 0975, Advanced Algorithms and Architectures for Signal Processing III, (23 February 1988); https://doi.org/10.1117/12.948499

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