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:
Apr. 23, 2013

Filed:

Nov. 04, 2009
Applicants:

Monty M. Denneau, Yorktown Heights, NY (US);

Daniel J. Friedman, Yorktown Heights, NY (US);

Ralph Linsker, Yorktown Heights, NY (US);

Mark B. Ritter, Yorktown Heights, NY (US);

Inventors:

Monty M. Denneau, Yorktown Heights, NY (US);

Daniel J. Friedman, Yorktown Heights, NY (US);

Ralph Linsker, Yorktown Heights, NY (US);

Mark B. Ritter, Yorktown Heights, NY (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
Abstract

A system, method, and design structure for address-event-representation network simulation are provided. The system includes a hardware structure with a plurality of interconnected processing modules configured to simulate a plurality of interconnected nodes. To simulate each node, the hardware structure includes a source table configured to receive an input message and identify a weight associated with a source of the input message. The hardware structure also includes state management logic configured to update a node state as a function of the identified weight, and generate an output signal responsive to the updated node state. The hardware structure further includes a target table configured to generate an output message in response to the output signal, identify a target to receive the output message, and transmit the output message. The hardware structure may further include learning logic configured to combine information about input messages and generated output signals, and to update weights.


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