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Proceedings Paper

Use Of Higher-Order Statistics In Signal Processing And System Theory: An Update
Author(s): Jerry M. Mendel
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Paper 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.

Paper Details

Date Published: 23 February 1988
PDF: 19 pages
Proc. SPIE 0975, Advanced Algorithms and Architectures for Signal Processing III, (23 February 1988); doi: 10.1117/12.948499
Show Author Affiliations
Jerry M. Mendel, University of Southern California (United States)

Published in SPIE Proceedings Vol. 0975:
Advanced Algorithms and Architectures for Signal Processing III
Franklin T. Luk, Editor(s)

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