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Title: US5222196: Neural network shell for application programs
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Country: US United States of America

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34 pages

 
Inventor: Bigus, Joseph P.; Rochester, MN

Assignee: International Business Machines Corporation, Armonk, NY
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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Published / Filed: 1993-06-22 / 1992-03-10

Application Number: US1992000849116

IPC Code: Advanced: G06N 3/04;
Core: G06N 3/00;
IPC-7: G06F 15/18;

U.S. Class: Current: 706/044;
Original: 395/026; 395/022; 395/076;

Field of Search: 395/011,21,22,23,26,76

Priority Number:
1990-02-20  US1990000482450
1992-03-10  US1992000849116

Abstract: A neural network shell has a defined interface to an application program. By interfacing with the neural network shell, any application program becomes a neural network application program. The neural network shell contains a set of utility programs that transfers data into and out of a neural network data structure. This set of utility programs allows an application program to define a new neural network model, create a neural network data structure, train a neural network, and run a neural network. Once trained, the neural network data structure can be transported to other computer systems or to application programs written in different computing languages running on similar or different computer systems.

Attorney, Agent or Firm: Rose, Curtis G. ;

Primary / Asst. Examiners: MacDonald, Allen R.;

Maintenance Status: E2 Expired  Check current status

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Related Applications: Go to Result Set: 8 patent(s) that list this one as related
Application Number Filed Patent Pub. Date  Title
US1990000482450 1990-02-20    1992-08-25  Neural network shell for application programs


       
Parent Case:     This is a divisional of co-pending application Ser. No. 07/482,450 filed on Feb. 20, 1990 now U.S. Pat. No. 5,142,665.

Designated Country: CH DE ES FR GB IT LI NL SE 

Family: Show 14 known family members

Claim What is claimed is:     1. A method in a neural network shell of enabling an application program to run one of a plurality of defined neural network models, thereby becoming a neural network having an input for data and an output for a result, said method comprising the machine-executed steps of:
  • creating a neural network data structure having a plurality of parameters and a plurality of data arrays specific to a selected one of said plurality of defined neural network models;
  • teaching said neural network by presenting training data at said input of said neural network and repeatedly adjusting the values of said plurality of data arrays until said result at said output is within tolerance of a correct result; and
  • running said neural network by presenting actual data at said input and retrieving the result from said output of said neural network.


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Forward References: Show 3 U.S. patent(s) that reference this one

       
U.S. References: Go to Result Set: All U.S. references   |  Forward references (3)   |   Backward references (1)   |   Citation Link

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Patent  Pub.Date  Inventor Assignee   Title
Buy PDF- 23pp US5111531  1992-05 Grayson et al.  Automation Technology, Inc. Process control using neural network
       
Foreign References: None

Other Abstract Info: DERABS G91-254543

Other References:
  • Structure and Application of NNSIM: A General Purpose Neural Network Simulator; NIJHUIS; Microprocessing & Microprogramming; Aug. 1989; pp. 189-194. (6 pages) Cited by 10 patents
  • ANDS: A Second Generation Neural Network Development System; Whittington; CONPAR'88; Sep. 12-16, 1988; pp. 84-91.
  • The Creation Of Delta; A New Concept In ANS Processing; Works; IEEE Inter Conf On Neural Networks; Jul. 24-27, 1988; pp. II-159-164.
  • A Declarative Neural Network Description Language; KORB; Microprocessing & Microprograming; 27 (1989) Aug.; pp. 181-188. (8 pages) Cited by 8 patents


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