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 October 27, 2025)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Global and Local Optimization Algorithms for Optimal Signal Set Design
Published
Author(s)
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
NIST Pub Series
Pub Type
NIST Pubs
Download Paper
Keywords
nonlinear programming, optimization, signal set
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact [email protected].
Created April 1, 2001, Updated February 17, 2017