The evolutionary learning rule for system identification

Authors:
Oscar Montiel;Oscar Castillo;Patricia Melin;Roberto Sepulveda
Affiliations:
CITEDI, National Polytechnic Institute, Tijuana, Mexico;Deptartment of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico;Deptartment of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico;CITEDI, National Polytechnic Institute, Tijuana, Mexico
Venue:
Applied Soft Computing
Year:
2003

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Abstract

In this paper, we are proposing an approach for integrating evolutionary computation applied to the problem of system identification in the well-known statistical signal processing theory. Here, some mathematical expressions are developed in order to justify the learning rule in the adaptive process when a breeder genetic algorithm (BGA) is used as the optimization technique. In this work, we are including an analysis of errors, energy measures, and stability.