Appiah, Kofi and Hunter, Andrew and Meng, Hongying and Yue, Shigang and Hobden, Mervyn and Priestley, Nigel and Hobden, Peter and Pettit, Cy (2009) A binary self-organizing map and its FPGA implementation. In: IEEE International Joint Conference on Neural Networks, June 14-29, 2009, Westin PeachTree Hotel, in Atlanta, Georgia.
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A binary Self Organizing Map (SOM) has been designed and implemented on a Field Programmable Gate Array (FPGA) chip. A novel learning algorithm which takes binary inputs and maintains tri-state weights is presented. The binary SOM has the capability of recognizing binary input sequences after training. A novel tri-state rule is used in updating the network weights during the training phase. The rule implementation is highly suited to the FPGA architecture, and allows extremely rapid training. This architecture may be used in real-time for fast pattern clustering and classification of the binary features.
|Item Type:||Conference or Workshop Item (Paper)|
|Keywords:||FPGA, SOM, Binary Patterns|
|Subjects:||G Mathematical and Computer Sciences > G730 Neural Computing
G Mathematical and Computer Sciences > G740 Computer Vision
|Divisions:||College of Sciences > Faculty of Science > Lincoln School of Computer Science|
|Depositing User:||Kofi Appiah|
|Date Deposited:||23 Mar 2009 16:13|
|Last Modified:||22 May 2013 13:26|
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