Implementation and applications of Tri-State self-organizing maps on FPGA

APPIAH, Kofi, HUNTER, Andrew, DICKINSON, Patrick and MENG, Hongying (2012). Implementation and applications of Tri-State self-organizing maps on FPGA. IEEE Transactions on Circuits and Systems for Video Technology, 22 (8), 1150-1160.

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Official URL: https://ieeexplore.ieee.org/document/6193165/
Link to published version:: https://doi.org/10.1109/TCSVT.2012.2197077

Abstract

This paper introduces a tri-state logic self-organizing map (bSOM) designed and implemented on a field programmable gate array (FPGA) chip. The bSOM takes binary inputs and maintains tri-state weights. A novel training rule is presented. The bSOM is well suited to FPGA implementation, trains quicker than the original self-organizing map (SOM), and can be used in clustering and classification problems with binary input data. Two practical applications, character recognition and appearance-based object identification, are used to illustrate the performance of the implementation. The appearance-based object identification forms part of an end-to-end surveillance system implemented wholly on FPGA. In both applications, binary signatures extracted from the objects are processed by the bSOM. The system performance is compared with a traditional SOM with real-valued weights and a strictly binary weighted SOM.

Item Type: Article
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.1109/TCSVT.2012.2197077
Depositing User: Kofi Appiah
Date Deposited: 13 Aug 2018 15:32
Last Modified: 13 Aug 2018 15:32
URI: http://shura.shu.ac.uk/id/eprint/22194

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