The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 13, 1994

Filed:

Aug. 15, 1991
Applicant:
Inventors:

Ho-sun Chung, Taegu, KR;

Hyo-jin Han, Taegu, KR;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F / ;
U.S. Cl.
CPC ...
395 24 ; 395 27 ; 395 23 ; 364D / ; 3642749 ; 3642766 ; 3642713 ;
Abstract

Disclosed is a multi-layer neural network and circuit design method. The multi-layer neural network receiving an m-bit input and generating an n-bit output comprises a neuron having a cascaded pair of CMOS inverters and having an output node of the preceding CMOS inverter among the pair of CMOS inverters as its inverted output node and an output node of the succeeding CMOS inverter as its non-inverted output node, an input layer having m neurons to receive the m-bit input, an output layer having n neurons to generate the n-bit output, at least one hidden layer provided with n neurons to transfer the input received from the input layer to every upper hidden layer and the output layer, an input synapse group in a matrix having each predetermined weight value to connect each output of neurons on the input layer to each neuron of the output layer and at least one hidden layer, at least one transfer synapse group in a matrix having each predetermined weight value to connect each output of neurons of the hidden layer to each neuron of every upper hidden layer and the output layer, and a bias synapse group for biasing each input node of neurons of the hidden layers and the output layer.


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