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Global and Local Optimization Algorithms for Optimal Signal Set Design

Published

Author(s)

Anthony J. Kearsley

Abstract

The problem of choosing an optimal signal set for non-Gaussian detection was reduced to a smooth inequality constrained mini-max nonlinear programming problem by Goeckenbach and Kearsley (SIAM J. Opt., 1998). Here we consider the application of several optimization algorithms, both global and local, to this problem. The most promising results are obtained when special-purpose Sequential Quadratic Programming (SQP) algorithms are embedded into stochastic global algorithms.
Citation
Journal of Research (NIST JRES) -
Volume
106 No. 2

Keywords

nonlinear programming, optimization, signal set

Citation

Kearsley, A. (2001), Global and Local Optimization Algorithms for Optimal Signal Set Design, Journal of Research (NIST JRES), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=150793 (Accessed June 16, 2024)

Issues

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Created April 1, 2001, Updated February 17, 2017