Adaptive IIR phase equalizers based on stochastic search algorithms

S. Pai; W. K. Jenkins; D. J. Krusienski

Adaptive IIR phase equalizers based on stochastic search algorithms

S. Pai, W. K. Jenkins, D. J. Krusienski

Research output: Contribution to journal › Conference article › peer-review

Abstract

Two well known optimization algorithms, the Genetic Algorithm (GA) and the Simulated Annealing Algorithm (SAA), are investigated for IIR adaptive phase equalizers. For non-convex error surfaces, gradient-based algorithms often fail to find the global optimum. This work compares the ability of the GA and the SAA to achieve the global minimum solution for multi-order all-pass adaptive filters to be used for the phase equalization of minimum phase SAW filters.

Original language	English (US)
Pages (from-to)	652-656
Number of pages	5
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	1
State	Published - Dec 1 2003
Event	Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 9 2003 → Nov 12 2003

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Cite this

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title = "Adaptive IIR phase equalizers based on stochastic search algorithms",

abstract = "Two well known optimization algorithms, the Genetic Algorithm (GA) and the Simulated Annealing Algorithm (SAA), are investigated for IIR adaptive phase equalizers. For non-convex error surfaces, gradient-based algorithms often fail to find the global optimum. This work compares the ability of the GA and the SAA to achieve the global minimum solution for multi-order all-pass adaptive filters to be used for the phase equalization of minimum phase SAW filters.",

author = "S. Pai and Jenkins, {W. K.} and Krusienski, {D. J.}",

year = "2003",

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AU - Pai, S.

AU - Jenkins, W. K.

AU - Krusienski, D. J.

PY - 2003/12/1

Y1 - 2003/12/1

N2 - Two well known optimization algorithms, the Genetic Algorithm (GA) and the Simulated Annealing Algorithm (SAA), are investigated for IIR adaptive phase equalizers. For non-convex error surfaces, gradient-based algorithms often fail to find the global optimum. This work compares the ability of the GA and the SAA to achieve the global minimum solution for multi-order all-pass adaptive filters to be used for the phase equalization of minimum phase SAW filters.

AB - Two well known optimization algorithms, the Genetic Algorithm (GA) and the Simulated Annealing Algorithm (SAA), are investigated for IIR adaptive phase equalizers. For non-convex error surfaces, gradient-based algorithms often fail to find the global optimum. This work compares the ability of the GA and the SAA to achieve the global minimum solution for multi-order all-pass adaptive filters to be used for the phase equalization of minimum phase SAW filters.

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M3 - Conference article

AN - SCOPUS:4143142918

SN - 1058-6393

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EP - 656

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers

Y2 - 9 November 2003 through 12 November 2003

ER -

Adaptive IIR phase equalizers based on stochastic search algorithms

Abstract

All Science Journal Classification (ASJC) codes

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