METHOD OF INCREASING THE ACCURACY OF AN ANALOG NEURAL NETWORK AND THE LIKE

Patent №

US 5,146,602

Granted

1992-09-08

Filed 1990

Owner

INTEL CORPORATION, A DE CORP.

Lab

AI components

2

ml · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

07634033

A method for increasing the accuracy of an analog neural network which computers a sum-of-products between an input vector and a stored weight pattern is described. In one embodiment of the present invention, the method comprises initially training the network by programming the synapses with a certain weight pattern. The training may be carried out using any standard learning algorithm. Preferably, a back-propagation learning algorithm is employed. Next, network is baked at an elevated temperature to effectuate a change in the weight pattern previously programmed during initial training. This change results from a charge redistribution which occurs within each of the synapses of the network. After baking, the network is then retrained to compensate for the change resulting from the charge redistribution. The baking and retraining steps may be successively repeated to increase the accuracy of the neural network to any desired level.

Machine learningAI hardwareH10D 30/687G06N 3/065G11C 27/005

AI classification

AI hardware1.00
Machine learning1.00
Vision0.11
Evolutionary computation0.01
Natural language0.00
Knowledge representation0.00
Speech0.00
Planning0.00

Ownership

INTEL CORPORATION, A DE CORP.

assignment · 55610143

Assignors

HOLLER, MARK A., TAM, SIMON M.

On an employer assignment, the assignors are typically the inventors.

From the same owner

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