Appiah, Kofi and Hunter, Andrew and 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). pp. 1150-1160. ISSN UNSPECIFIED
bSOMvF.pdf - Whole Document
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial.
Full text URL: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnum...
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.
|Keywords:||binary SOM, FPGA, character recognition, object recognition|
|Subjects:||G Mathematical and Computer Sciences > G411 Computer Architectures|
G Mathematical and Computer Sciences > G400 Computer Science
|Divisions:||College of Science > School of Computer Science|
|Deposited By:||INVALID USER|
|Deposited On:||06 Sep 2012 19:41|
|Last Modified:||04 Dec 2013 16:24|
Repository Staff Only: item control page