Optical Associative Memory Using Optoelectronic Neurochips for Image Processing
Summary :
This paper presents a novel model of optical associative memory using an optoelectronic neurochips, which detects and processes a two-dimensional input image at the same time. The original point of this model is that the optoelectronic neurochips allow direct image processing in terms of parallel input/output interface and parallel neural processing. The operation principle is based on the nonlinear transformation of the input image to the corresponding the point attractor of a fully connected neural network. The learning algorithm is the simulated annealing and the energy of the network state is used as its cost function. The computer simulations show its usefulness and that the maximum number of stored images is 150 in the network with 64 neurons. Moreover, we experimentally demonstrate an optical implementation of the model using the optoelectronic neurochip. The chip consists of two-dimensional array of variable sensitivity photodetectors with 8
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- IEICE TRANSACTIONS on Electronics Vol.E77-C No.1 pp.56-62
- Publication Date
- 1994/01/25
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- Type of Manuscript
- Special Section PAPER (Special Issue on Optical Interconnection)
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Masaya OITA, Yoshikazu NITTA, Shuichi TAI, Kazuo KYUMA, "Optical Associative Memory Using Optoelectronic Neurochips for Image Processing" in IEICE TRANSACTIONS on Electronics,
vol. E77-C, no. 1, pp. 56-62, January 1994, doi: .
Abstract: This paper presents a novel model of optical associative memory using an optoelectronic neurochips, which detects and processes a two-dimensional input image at the same time. The original point of this model is that the optoelectronic neurochips allow direct image processing in terms of parallel input/output interface and parallel neural processing. The operation principle is based on the nonlinear transformation of the input image to the corresponding the point attractor of a fully connected neural network. The learning algorithm is the simulated annealing and the energy of the network state is used as its cost function. The computer simulations show its usefulness and that the maximum number of stored images is 150 in the network with 64 neurons. Moreover, we experimentally demonstrate an optical implementation of the model using the optoelectronic neurochip. The chip consists of two-dimensional array of variable sensitivity photodetectors with 8
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e77-c_1_56/_p
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@ARTICLE{e77-c_1_56,
author={Masaya OITA, Yoshikazu NITTA, Shuichi TAI, Kazuo KYUMA, },
journal={IEICE TRANSACTIONS on Electronics},
title={Optical Associative Memory Using Optoelectronic Neurochips for Image Processing},
year={1994},
volume={E77-C},
number={1},
pages={56-62},
abstract={This paper presents a novel model of optical associative memory using an optoelectronic neurochips, which detects and processes a two-dimensional input image at the same time. The original point of this model is that the optoelectronic neurochips allow direct image processing in terms of parallel input/output interface and parallel neural processing. The operation principle is based on the nonlinear transformation of the input image to the corresponding the point attractor of a fully connected neural network. The learning algorithm is the simulated annealing and the energy of the network state is used as its cost function. The computer simulations show its usefulness and that the maximum number of stored images is 150 in the network with 64 neurons. Moreover, we experimentally demonstrate an optical implementation of the model using the optoelectronic neurochip. The chip consists of two-dimensional array of variable sensitivity photodetectors with 8
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Optical Associative Memory Using Optoelectronic Neurochips for Image Processing
T2 - IEICE TRANSACTIONS on Electronics
SP - 56
EP - 62
AU - Masaya OITA
AU - Yoshikazu NITTA
AU - Shuichi TAI
AU - Kazuo KYUMA
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E77-C
IS - 1
JA - IEICE TRANSACTIONS on Electronics
Y1 - January 1994
AB - This paper presents a novel model of optical associative memory using an optoelectronic neurochips, which detects and processes a two-dimensional input image at the same time. The original point of this model is that the optoelectronic neurochips allow direct image processing in terms of parallel input/output interface and parallel neural processing. The operation principle is based on the nonlinear transformation of the input image to the corresponding the point attractor of a fully connected neural network. The learning algorithm is the simulated annealing and the energy of the network state is used as its cost function. The computer simulations show its usefulness and that the maximum number of stored images is 150 in the network with 64 neurons. Moreover, we experimentally demonstrate an optical implementation of the model using the optoelectronic neurochip. The chip consists of two-dimensional array of variable sensitivity photodetectors with 8
ER -
English
