Efficient hardware architecture based on generalized Hebbian algorithm for texture classification

Authors:
Shiow-Jyu Lin;Yi-Tsan Hung;Wen-Jyi Hwang
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan and Department of Electronic Engineering, National Ilan University, Yilan 260, Tai ...;Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan;Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan
Venue:
Neurocomputing
Year:
2011

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Abstract

The objective of this paper is to present an efficient hardware architecture for generalized Hebbian algorithm (GHA). In the architecture, the principal component computation and weight vector updating of the GHA are operated in parallel, so that the throughput of the circuit can be significantly enhanced. In addition, the weight vector updating process is separated into a number of stages for lowering area costs and increasing computational speed. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is designed. It is embedded in a system-on-programmable-chip (SOPC) platform for physical performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs.