FPGA implementation of generalized hebbian algorithm for texture classification

Citations of this article
Mendeley users who have this article in their library.


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. © 2012 by the authors; licensee MDPI, Basel, Switzerland.




Lin, S. J., Hwang, W. J., & Lee, W. H. (2012). FPGA implementation of generalized hebbian algorithm for texture classification. Sensors (Switzerland), 12(5), 6244–6268. https://doi.org/10.3390/s120506244

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free