Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412831 | Neurocomputing | 2010 | 7 Pages |
Abstract
This paper presents a novel hardware architecture for genetic vector quantizer (VQ) design. It is based on steady-state genetic algorithm (GA) and adopts shift registers for accelerating mutation and crossover operations while reducing area cost. It also uses a pipeline for fitness evaluation. The proposed architecture has been embedded in a softcore CPU for physical performance measurement. Experimental results show that it is an effective alternative for VQ optimization attaining both high performance and low computational time.
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Authors
Chien-Min Ou,