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An optically differential reconfigurable gate array and its power consumption estimation 査読

M Watanabe, F Kobayashi

2002 IEEE INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY (FPT), PROCEEDINGS 197 - 202 2002年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

A new optically differential reconfigurable gate array (ODRGA) is proposed to reduce configuration power consumption. The ODRGA has a simple architecture that adds a small circuit to conventional optically reconfigurable gate arrays (ORGAs) and uses differential configuration data stored in an optical holographic memory. In this paper configuration power consumption of ORGAs is estimated theoretically. Based on results, we show an estimation of configuration power consumption and comparative area occupied by the configuration circuit for ODRGA and conventional ORGAs.

DOI： 10.1109/FPT.2002.1188682

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A compressed implementation of neural network with finite physical quantities on FPGAs 査読

T Sotohebo, M Watanabe, F Kobayashi

SICE 2002: PROCEEDINGS OF THE 41ST SICE ANNUAL CONFERENCE, VOLS 1-5 1861 - 1862 2002年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

This paper presents the implementation of a multilayer neural network with finite physical quantities on a FPGA. The FPGA implementation extensively reduces much computer time for the neural network that requires iterative operation to exchange the physical quantities between neurons little by little.

DOI： 10.1109/SICE.2002.1196606

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ニューラルネットワークVLSI

渡邊実, 小林史典

計測と制御 = Journal of the Society of Instrument and Control Engineers 40 ( 12 ) 893 - 896 2001年12月

An optical energy neural networkwith self-organizing capability 査読

M. Watanabe, A. Itoh, F. Kobayashi

17th annual conference of International Conference on Circuits/Systems Computers and Communications 2 1292 - 1295 2001年7月

DIGITAL ASSOCIATIVE MEMORY NEURAL-NETWORK WITH OPTICAL LEARNING CAPABILITY 査読

M WATANABE, J OHTSUBO

OPTICS COMMUNICATIONS 113 ( 1-3 ) 31 - 38 1994年12月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：ELSEVIER SCIENCE BV

A digital associative memory neural network system with optical learning and recalling capabilities is proposed by using liquid crystal television spatial light modulators and an Optic RAM detector. In spite of the drawback of the limited memory capacity compared with optical analogue associative memory neural network, the proposed optical digital neural network has the advantage of all optical learning and recalling capabilities, thus an all optics network system is easily realized. Some experimental results of the learning and the recalling for character recognitions are presented. This new optical architecture offers compactness of the system and the fast learning and recalling properties. Based on the results, the practical system for the implementation of a faster optical digital associative memory neural network system with ferro-electric liquid crystal SLMs is also proposed.

DOI： 10.1016/0030-4018(94)90588-6

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