FPGA implementation of generalized hebbian algorithm for texture classification

Shiow Jyu Lin, Wen Jyi Hwang, Wei Hao Lee

研究成果: 雜誌貢獻文章同行評審

6 引文 斯高帕斯(Scopus)

摘要

This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness. The architecture is separated into three portions: The weight vector updating unit, the principal computation unit and the memory unit. In the weight vector updating unit, the computation of different synaptic weight vectors shares the same circuit for reducing the area costs. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is physically implemented by Field Programmable Gate Array (FPGA). It is embedded in a System-On-Programmable-Chip (SOPC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs.

原文英語
頁(從 - 到)6244-6268
頁數25
期刊Sensors (Switzerland)
12
發行號5
DOIs
出版狀態已發佈 - 2012 五月

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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