Neural net model and neural net optimizing method and system for

Details Neural net model and neural net optimizing method and system for Neural net model and neural net optimizing method and system for

1993-07-30

1995-08-08

MacDonald, Allen R.

Boots, shoes, and leggings

364807, 364822, G06F 1500, G06G 900

Patent

active

054406714

ABSTRACT:
A recursive neural net including processing elements (1) each having a linear saturated function as an input/output function. The elements (1) are divided into a plurality of blocks (2), and the states of the elements (1) are asynchronously updated block by block while being synchronously updated within each block (2). Since convergence is ensured for any symmetric synaptic matrix (W) by selecting a step-size for each particular problem, the neural net can be applied to any optimization problem. In addition, a neural net system is composed of an optical computing unit (201 to 205) performing a vector matrix calculation using light, a threshold processing unit (206) performing a threshold processing operation, a coefficient multiplying unit (209) performing a step-size processing operation, a saturated linear computing unit (207) performing a saturated linear function operation, and a block control unit (208) performing selection of a block to be updated and state updating therefor.

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Psaltis et al, "Optical information processing based on an associative memory model of neural nets with thresholding and feedback", 1985, Optical Society of America.
Farhat et al, "Architectures for optoelectronic analogs of self-organizing neural networks", 1987, Optical Society of America.
Psaltis et al, "Nonlinear Discriminant Functions and Associative Memories", 1986 American Institute of Physics.

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