Neural network models for optical computing; Proceedings of the Meeting, Los Angeles, CA, Jan. 13, 14, 1988
Various papers on neural network models for optical computing are presented. The topics considered include: optically connected multiprocessors for simulating artificial neural networks, hardware implementation of an artificial neural network, optical neural network models applied to logic program execution, adaptive learning optical symbolic processor, continuous-time neural networks, optical associative processors for visual perception, holographic implementation of a discrete Hopfield neural network model, improving the performance of neural networks, optical neural classification of binary patterns, and architectures for a continuous level neural network based on alternating orthogonal projections. Also discussed are: electrooptical implementation of programmable quadratic neural networks, computing motion using resistive networks, visuomotor coordination, drive-reinforcement neuronal model, multiple correlations in a holographic resonator, photorefractive crystals in optical neural computers, optical network that learns to perform motion compensation in radar imaging, competitive optoelectronic learning networks, and potential difference learning and its optical architecture.
- OSTI ID:
- 6385289
- Report Number(s):
- CONF-8801148-
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
990210* -- Supercomputers-- (1987-1989)
ABSTRACTS
ARRAY PROCESSORS
ARTIFICIAL INTELLIGENCE
COMPUTER ARCHITECTURE
COMPUTERS
CYBERNETICS
DESIGN
DOCUMENT TYPES
ELECTRONIC EQUIPMENT
EQUIPMENT
HOLOGRAPHY
IMAGE PROCESSING
LEADING ABSTRACT
LEARNING
MEETINGS
OPTICAL COMPUTERS
PARALLEL PROCESSING
PROCESSING
PROGRAMMING
SIMULATION