Presentation 2011-03-03
Dynamically reconfigurable platform for self-organizing neural networks
Hakaru TAMUKOH, Masatoshi SEKINE,
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Abstract(in English) In this paper, we propose a dynamically reconfigurable platform for self-organizing neural network hardware. In the proposed platform, a hardware unit can be handled as a hardware object in object-oriented design. The hardware object is loaded into the FPGA's virtual hardware circuit space, and accelerates the calculation of self-organizing neural networks. We design two types of the distance calculation, a winner-take-all and a rough-winner-take-all virtual hardware circuit as common parts of self-organizing neural networks. By combining them, we realize four types of self-organizing neural network. Experimental results show that the implemented self-organizing neural network hardware achieves about 100 times faster than the software implementation. Besides, the proposed platform can change its learning mode easily as well as the software implementation. Therefore, the proposed platform features both of the speed of hardware and the flexibility of software.
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Keyword(in English) Self-organizing map / Neural networks / Rough-winner-take-all / Vector quantization / FPGA / hw/sw complex system / Reconfigurable platform
Paper # SIS2010-55
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Conference Information
Committee SIS
Conference Date 2011/2/24(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Dynamically reconfigurable platform for self-organizing neural networks
Sub Title (in English)
Keyword(1) Self-organizing map
Keyword(2) Neural networks
Keyword(3) Rough-winner-take-all
Keyword(4) Vector quantization
Keyword(5) FPGA
Keyword(6) hw/sw complex system
Keyword(7) Reconfigurable platform
1st Author's Name Hakaru TAMUKOH
1st Author's Affiliation Institute of Engineering, Tokyo University of Agriculture and Technology()
2nd Author's Name Masatoshi SEKINE
2nd Author's Affiliation Institute of Engineering, Tokyo University of Agriculture and Technology
Date 2011-03-03
Paper # SIS2010-55
Volume (vol) vol.110
Number (no) 445
Page pp.pp.-
#Pages 5
Date of Issue