Anthony J. Kearlsey
Department of Mathematical Sciences
Carnegie Mellon University
Pittsburgh, PA 15213
email: kearsley@andrew.cmu.edu
and
Mathematical and Computational Science Division
National Institute of Standards and Technology
Gaithersburg, MD 20899
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 Gockenbach 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.
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