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Title: US5317676: Apparatus and method for facilitating use of a neural network
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Country: US United States of America

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18 pages

 
Inventor: Austvold, Shawn M.; Rochester, MN
Bigus, Joseph P.; Rochester, MN
Henckel, Jonathan D.; Rochester, MN
Hospers, Paul A.; 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: 1994-05-31 / 1992-12-03

Application Number: US1992000986889

IPC Code: Advanced: G06F 15/18; G06G 7/60; G06N 3/10; G06N 99/00;
Core: G06G 7/00; G06N 3/00; more...
IPC-7: G06F 15/18;

ECLA Code: G06N3/10S;

U.S. Class: Current: 706/044; 706/016;
Original: 395/026; 395/076; 395/021;

Field of Search: 395/022,23,24,27,76,26 364/715.03,715.05

Priority Number:
1992-12-03  US1992000986889
1991-04-18  US1991000687364

Abstract:     A neural network development utility assists a developer in generating one or more filters for data to be input to or output from a neural network. A filter is a device which translates data in accordance with a data transformation definition contained in a translate template. Source data for the neural network may be expressed in any arbitrary combination of symbolic or numeric fields in a data base. The developer selects those fields to be used from an interactive menu. The utility scans the selected field entries in the source data base to identify the logical type of each field, and creates a default translate template based on this scan. Numeric data is automatically scaled. The developer may use the default template, or edit it from an interactive editor. When editing the template, the developer may select from a menu of commonly used neural network data formats, and from a menu of commonly used primitive mathematical operations. The developer may interactively define additional filters to perform data transformations in series, thus achieving more complex mathematical operations on the data. Templates may be edited at any time during the development process. If a network does not appear to be giving satisfactory results, the developer may easily alter the template to present inputs in some other format.

Attorney, Agent or Firm: Truelson, Roy W. ;

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

Maintenance Status: E3 Expired  Check current status

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Related Applications: Go to Result Set: 1 patent(s) that list this one as related
Application Number Filed Patent Pub. Date  Title
US1991000687364 1991-04-18       


       
Parent Case:     This is a continuation of U.S. Ser. No. 07/687,364 filed Apr. 18, 1991, now abandoned.

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

Family: Show 10 known family members

First Claim:
Show all 25 claims
What is claimed is:     1. An apparatus for facilitating the use of a neural network, comprising:
  • means for receiving source data for the neural network, said source data comprising a plurality of source data fields;
  • translation definition means for defining, with respect to each of said source data fields, a corresponding data transformation, wherein at least one of said data transformations is a transformation of data of one data type to data of another data type, and wherein said translation definition means comprises means for automatically generating a default data transformation definition with respect to each of said source data fields; and
  • means, responsive to said translation definition means, for translating source data contained in each said source data field according to the data transformation corresponding to said source data field, to produce a neural network input.


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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 (10)   |   Citation Link

Buy
PDF
Patent  Pub.Date  Inventor Assignee   Title
Buy PDF- 20pp US4908746  1990-03 Vaughn  United States Data Corporation Industrial control system
Buy PDF- 18pp US4914603  1990-04 Wood  GTE Laboratories Incorporated Training neural networks
Buy PDF- 19pp US4914708  1990-04 Carpenter et al.  Boston University System for self-organization of stable category recognition codes for analog input patterns
Buy PDF- 19pp US4945494  1990-07 Penz et al.  Texas Instruments Incorporated Neural network and system
Buy PDF- 11pp US4954963  1990-09 Penz et al.  Texas Instruments Incorporated Neural network and system
Buy PDF- 15pp US4972187  1990-11 Wecker  Digital Equipment Corporation Numeric encoding method and apparatus for neural networks
Buy PDF- 18pp US4979126  1990-12 Pao et al.  AI Ware Incorporated Neural network with non-linear transformations
Buy PDF- 29pp US5036479  1991-07 Prednis et al.  TRW Inc. Modular automated avionics test system
Buy PDF- 45pp US5097411  1992-03 Doyle et al.  Digital Equipment Corporation Graphics workstation for creating graphics data structure which are stored retrieved and displayed by a graphics subsystem for competing programs
Buy PDF- 8pp US5216750  1993-06 Smith  Texas Instruments Incorporated Computation system and method using hamming distance
       
Foreign References:
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PDF
Publication Date IPC Code Assignee   Title
Buy PDF- 36pp WO8909449 1989-10  G06F 15/18 AI WARE INCORPORATED FUNCTIONAL LINK NEURAL NET 


Other Abstract Info: DERABS G1992-351568

Other References:
  • Passino et al, "Neural Computing for Numeric-to-Symbolic Conversion in Control Systems," IEEE Control Systems Magazine, 1989, pp. 44-52.
  • "Neural Nets They Learn From Examples", Chemical Engineering, August 1990.
  • "An Introduction to Neural to Neural Nets", Phiroz Bhagat, Exxon Research & Engineering Co., Florham Park, N.J. 07932, Chemical Engineering Progress, Aug. 1990.
  • "Automated Design of Neural Networks For Symbolic Signal Processing", IEEE, 1989, Andrea Maccato & Rui J. P. de Figueiredo, Rice Univ. Houston, Tex. 77251-1802.
  • "A Graphical Design System for Neural Networks", Greg Hood, Computer Science Dept., Carnegie Mellon University, Pittsburgh, Pa. 15213.


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