Share Email Print

Proceedings Paper

Use Of Higher-Order Statistics In Signal Processing And System Theory: An Update
Author(s): Jerry M. Mendel
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top