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

Autor:	Sheng Kai Weng, Ting Kuan Lin, Wen-Jyi Hwang
Rok vydání:	2009
Předmět:	Hardware architecture Computer science Pipeline (computing) Crossover Genetic algorithm General Engineering Memetic algorithm Parallel computing Field-programmable gate array Reconfigurable computing Shift register
Zdroj:	Journal of the Chinese Institute of Engineers. 32:905-914
ISSN:	2158-7299 0253-3839
DOI:	10.1080/02533839.2009.9671577
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c21598858ad14ab0403050808809b361 https://doi.org/10.1080/02533839.2009.9671577 Zobrazit plný text záznamu