Structured stochastic optimization strategies for problems with ill-conditioned error surfaces

Siddharth Pal, D. J. Krusienski, William Kenneth Jenkins

Research output: Contribution to journalConference article

2 Scopus citations


This paper compares the performance of several structured optimization strategies in adaptive signal processing problems that are characterized by ill-conditioned error surfaces. The genetic algorithm (GA), the particle swarm optimization (PSO) algorithm, and a new constrained random search (CRS) algorithm [8] are considered. When applied to adaptive filters, these structured stochastic search strategies re independent of the adaptive filter structure and are capable of converging to the global solution when applied in circumstances that create multi-modal mean squared error surfaces.

Original languageEnglish (US)
Article number1465081
Pages (from-to)2291-2294
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
StatePublished - Dec 1 2005
EventIEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 - Kobe, Japan
Duration: May 23 2005May 26 2005


All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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