Efficient memetic vector quantizer design based on reconfigurable hardware and softcore processor

Wen Jyi Hwang, Sheng Kai Weng, Ting Kuan Lin

研究成果: 雜誌貢獻期刊論文同行評審

摘要

This paper presents a novel hardware architecture for memetic vector quantizer (VQ) design. The architecture uses steady-state genetic algorithm (GA) for global search, and C-Means algorithm for local refinement. It adopts a shift register based circuit for accelerating mutation and crossover operations for steady state CA operations. It also uses a pipeline architecture for the hardware implementation of C-Means algorithm. The proposed architecture is embedded in a softcore CPU, and implemented on a field programmable logic array (FPGA) device for physical performance measurement. Experimental results show that the proposed architecture is an effective method for VQ optimization attaining both high performance and low computational time.

ASJC Scopus subject areas

  • Engineering(all)

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