Self-organizing neural network for pattern classification

Details Self-organizing neural network for pattern classification Self-organizing neural network for pattern classification

1994-10-31

1995-12-26

Davis, George B.

395 24, 395 22, G06F 1518

Patent

active

054795753

ABSTRACT:
A neural network includes a plurality of input nodes for receiving the respective elements of the input vector. A copy of all of the elements of the input vector is sent to the next level of nodes in the neural network denoted as intermediate nodes. The intermediate nodes each encode a separate template pattern. They compare the actual input pattern with the template and generate a signal indicative of the difference between the input pattern and the template pattern. Each of the templates encoded in the intermediate nodes has a class associated with it. The difference calculated by the intermediate nodes is passed to an output node for each of the intermediate nodes at a given class. The output node then selects the minimum difference amongst the values sent from the intermediate nodes. This lowest difference for the class represented by the output node is then forwarded to a selector. The selector receives such values from each of the output nodes of all of the classes and then selects that to output value which is a minimum difference. The selector in turn, generates a signal indicative of the class of the intermediate node that sent the smallest difference value.

REFERENCES:
patent: 3638196 (1972-01-01), Nishiyama et al.
patent: 3950733 (1976-04-01), Cooper et al.
patent: 4044243 (1977-08-01), Cooper et al.
patent: 4326259 (1982-04-01), Cooper et al.
patent: 4451929 (1984-05-01), Yoshida
patent: 4760604 (1988-07-01), Cooper et al.
patent: 4774677 (1988-09-01), Buckley
patent: 4805225 (1989-02-01), Clark
patent: 4914708 (1990-04-01), Carpenter et al.
patent: 4958375 (1990-09-01), Reilly et al.
patent: 4975961 (1990-12-01), Sakoe
patent: 5033006 (1991-07-01), Ishizuka et al.
patent: 5045713 (1991-09-01), Shima
patent: 5048100 (1991-09-01), Kuperstein
patent: 5052043 (1991-09-01), Goborski
patent: 5056037 (1991-10-01), Eberhardt
patent: 5060278 (1991-10-01), Fukumizu
patent: 5129039 (1992-07-01), Hiraiwa
patent: 5157738 (1992-10-01), Carpenter et al.
patent: 5165010 (1992-11-01), Masuda et al.
patent: 5195169 (1993-03-01), Kamiya et al.
patent: 5214743 (1993-05-01), Asai et al.
patent: 5333239 (1994-07-01), Watanabe et al.
Sebestyen, "Decision-Making Processes in Pattern Recognition," MacMillan, 1962, pp. 17-24, 37-53, 91-96, 108-112, 120-131, 142-151.
Widrow et al, "Neural Nets for Adaptive Filtering and Adaptive Pattern Recognition" IEEE 1988.
Shynk et al, "Convergence Properties and Stationary Points of a Perception Learning Algorithm", proceedings of the IEEE Oct. 1990.
Carpenter et al, "The Art of Adaptive Pattern Recognition by a Self-Organizing Neural Network", IEEE, Mar. 1988.
T. Kohonen, "Statistical Pattern Recognition Revisited", Advanced Neural Computers, R. Eckmiller, ed. (1990), 137-143.
T. Hohonen, "Improved Versions of Learning Vector Quantization", Proc. of Int'l Joint Conf. of Neural Networks, Jun. 1990. (I-545)-(I-550).
B. G. Batchelor, "Classification and Data Analysis in Vector Spaces," pattern Recognition: Ideas in Practice, B. G. Batchelor, ed. (1977) pp. 67-116.
R. Duda et al., Pattern Classification and Scene Analysis, 1973, pp. 1-7.
C. Suen et al. "Automatic Recognition of Handprinted Characters-The State of the Art", Proc. of IEEE, Apr. 1980, 469-487.
R. Lippman, "An Introduction to Computing with Neural Nets", IEEE ASSP Magazine, Apr., 1987, pp. 4-22.
Reilly et al., Learning System Architectures Composed of Multiple Learning Modules, Brown University, Providence, R.I., (1987).
Makhoul, et al., Vector Quantization in Speech Coding, Proceedings of the IEEE, vol. 73, No. 11, pp. 1551-1588, Nov., 1985.
J. Marshall, "Self-Organizing Neural Networks for Perception of Visual Motion", Neural Networks, vol. 3, No. 1, 1990, pp. 45-74.
Fritz Seytter, "A Self-Organising Neural Net for Depth Movement Analysis", Parallel Processing in Neural Systems and Computers, Elsevier Sci. Pub. 1990, pp. 369-372.

Affiliated with

Also associated with

Rating

Self-organizing neural network for pattern classification does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Self-organizing neural network for pattern classification, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Self-organizing neural network for pattern classification will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-1375730