Add to ORKGThe capabilities of photorefractive crystals as media for holographic interconnections in neural networks are examined. Limitations on the density of interconnections and the number of holographic associations which can be stored in photorefractive crystals are derived. Optical architectures for implementing various neural schemes are described. Experimental results are presented for one of these architectures
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We consider the convergence characteristics of a perceptron learning algorithm, taking into account ...
In recent years there has been a great interest in neural networks, since neural networks are capabl...
The capabilities of photorefractive crystals as media for holographic interconnections in neural net...
An optical computer which performs the classification of an input object pattern into one of two lea...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
The dense interconnections that characterize neural networks are most readily implemented using opti...
A new approach to learning in a multilayer optical neural network based on holographically interconn...
In a holographic optical learning network, the decay of multiply exposed holographic interconnection...
This paper describes a new optical processing devices that can handle large patterns and can accommo...
We describe the combination of neural network training and volume holographic storage technologies u...
We present a novel, versatile optoelectronic neural network architecture for implementing supervised...
This feature of Applied Optics is devoted to papers on the optical implementation of neural-network ...
An optical network is described that is capable of recognizing at standard video rates the identity ...
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We consider the convergence characteristics of a perceptron learning algorithm, taking into account ...
In recent years there has been a great interest in neural networks, since neural networks are capabl...
The capabilities of photorefractive crystals as media for holographic interconnections in neural net...
An optical computer which performs the classification of an input object pattern into one of two lea...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
The dense interconnections that characterize neural networks are most readily implemented using opti...
A new approach to learning in a multilayer optical neural network based on holographically interconn...
In a holographic optical learning network, the decay of multiply exposed holographic interconnection...
This paper describes a new optical processing devices that can handle large patterns and can accommo...
We describe the combination of neural network training and volume holographic storage technologies u...
We present a novel, versatile optoelectronic neural network architecture for implementing supervised...
This feature of Applied Optics is devoted to papers on the optical implementation of neural-network ...
An optical network is described that is capable of recognizing at standard video rates the identity ...
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We consider the convergence characteristics of a perceptron learning algorithm, taking into account ...
In recent years there has been a great interest in neural networks, since neural networks are capabl...