Add to ORKGIn a holographic optical learning network, the decay of multiply exposed holographic interconnections can adversely affect the training of the network. A new dynamic photorefractive holographic memory is described that allows an arbitrarily long sequence of adaptations by rejuvenating decayed holograms with a simple all-optical feedback loop
An optical network is described that is capable of recognizing at standard video rates the identity ...
We consider the properties of a generalized perceptron learning network, taking into account the dec...
Digital holography is a well-known method to perform three-dimensional imaging by recording the ligh...
In a holographic optical learning network, the decay of multiply exposed holographic interconnection...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
We report the experimental demonstration of a photorefractive dynamic holographic memory that has a ...
The capabilities of photorefractive crystals as media for holographic interconnections in neural net...
A new approach to learning in a multilayer optical neural network based on holographically interconn...
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
We consider the convergence characteristics of a perceptron learning algorithm, taking into account ...
An optical computer which performs the classification of an input object pattern into one of two lea...
The dense interconnections that characterize neural networks are most readily implemented using opti...
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We describe a method for increasing the diffraction efficiency of multiply exposed photorefractive h...
Photonic neural network implementation has been gaining considerable attention as a potentially disr...
An optical network is described that is capable of recognizing at standard video rates the identity ...
We consider the properties of a generalized perceptron learning network, taking into account the dec...
Digital holography is a well-known method to perform three-dimensional imaging by recording the ligh...
In a holographic optical learning network, the decay of multiply exposed holographic interconnection...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
We report the experimental demonstration of a photorefractive dynamic holographic memory that has a ...
The capabilities of photorefractive crystals as media for holographic interconnections in neural net...
A new approach to learning in a multilayer optical neural network based on holographically interconn...
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
We consider the convergence characteristics of a perceptron learning algorithm, taking into account ...
An optical computer which performs the classification of an input object pattern into one of two lea...
The dense interconnections that characterize neural networks are most readily implemented using opti...
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We describe a method for increasing the diffraction efficiency of multiply exposed photorefractive h...
Photonic neural network implementation has been gaining considerable attention as a potentially disr...
An optical network is described that is capable of recognizing at standard video rates the identity ...
We consider the properties of a generalized perceptron learning network, taking into account the dec...
Digital holography is a well-known method to perform three-dimensional imaging by recording the ligh...