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Harmony search algorithm for infinite impulse response system identification
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AI
DOI：10.1016/j.compeleceng.2013.12.016.png)
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Abstract
En 中文
In this paper, optimal sets of filter coefficients are searched by a meta-heuristic optimization technique called Harmony Search (HS) algorithm for infinite impulse response (IIR) system identification problem. For different optimization problems, HS algorithm undergoes three basic rules; namely Random Selection (RS), Harmony Memory Consideration (HMC), and Pitch Adjustment (PA) rules, which are inspired from the process that the musicians use to improvise a perfect state of harmony with the consummate skill of blending notes in tune. With the help of the properly selected control parameters, a perfect balance is achieved in exploration and exploitation in searching phases. The detailed analysis of simulation results emphasizes the strength of HS algorithm to find the near-global optimal solution, quality of convergence profile and the speed of convergence while tested against standard benchmark examples for same and reduced order models. (c) 2014 Elsevier Ltd. All rights reserved.
Keywords:
PARTICLE SWARM OPTIMIZATION
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