Efficient <em>k</em>-Winner-Take-All Competitive Learning Hardware Architecture for On-Chip Learning

A novel <em>k</em>-winners-take-all (<em>k</em>-WTA) competitive learning (CL) hardware architecture is presented for on-chip learning in this paper. The architecture is based on an efficient pipeline allowing <em>k</em&...

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Bibliographic Details
Main Authors: Wen-Jyi Hwang, Hui-Ya Li, Chien-Min Ou
Format: Article
Language:English
Published: MDPI AG 2012-08-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/12/9/11661
Description
Summary:A novel <em>k</em>-winners-take-all (<em>k</em>-WTA) competitive learning (CL) hardware architecture is presented for on-chip learning in this paper. The architecture is based on an efficient pipeline allowing <em>k</em>-WTA competition processes associated with different training vectors to be performed concurrently. The pipeline architecture employs a novel codeword swapping scheme so that neurons failing the competition for a training vector are immediately available for the competitions for the subsequent training vectors. The architecture is implemented by the field programmable gate array (FPGA). It is used as a hardware accelerator in a system on programmable chip (SOPC) for realtime on-chip learning. Experimental results show that the SOPC has significantly lower training time than that of other <em>k</em>-WTA CL counterparts operating with or without hardware support.
ISSN:1424-8220