Neural network apparatus and method for pattern recognition

Details Neural network apparatus and method for pattern recognition Neural network apparatus and method for pattern recognition

1990-04-30

1991-10-15

Moore, David K.

Image analysis

Histogram processing

For setting a threshold

382 15, 382 36, 3649724, 3642749, G06K 900

Patent

active

050581805

ABSTRACT:
A self-organizing neural network having input and output neurons mutually coupled via bottom-up and top-down adaptive weight matrics performs pattern recognition while using substantially fewer neurons and being substantially immune from pattern distortion or rotation. The network is first trained in accordance with the adaptive resonance theory by inputting reference pattern data into the input neurons for clustering within the output neurons. The input neurons then receive subject pattern data which are transferred via a bottom-up adaptive weight matrix to a set of output neurons. Vigilance testing is performed and multiple computed vigilance parameters are generated. A predetermined, but selectively variable, reference vigilance parameter is compared individually against each computed vigilance parameter and adjusted with each comparison until each computed vigilance parameter equals or exceeds the adjusted reference vigilance parameter, thereby producing an adjusted reference vigilance parameter for each output neuron. The input pattern is classified according to the output neuron corresponding to the maximum adjusted reference vigilance parameter. Alternatively, the original computed vigilance parameters can be used by classifying the input pattern according to the output neuron corresponding to the maximum computer vigilance parameter.

REFERENCES:
patent: 4876731 (1989-10-01), Loris et al.
patent: 4914708 (1990-04-01), Carpenter et al.
Computer Visions, Graphics, and Image Processing 1987, 37, 54-115.
L. D. Jackel, H. P. Graf, J. S. Denker, D. Henderson and I. Guyon, "An Application of Neural Net Chips: Handwritten Digit Recognition," ICNN Proceeding, 1988, pp. II-107-15.
G. A. Carpenter and S. Grossberg, "The Art of Adaptive Pattern Recognition by a Self-Organizing Neural Network," IEEE Computer, Mar. 1988, pp. 77-88.
T. F. Pawlicki, D. S. Lee, J. J. Hull and S. N. Srihari, "Neural Network Models and their Application to Handwritten Digit Recognition," ICNN Proceeding, 1988, pp. II-63-70.
E. Gullichsen and E. Chang, "Pattern Classification by Neural Network: An Experiment System for Icon Recognition," ICNN Proceeding on Neural Networks, Mar. 1987, pp. IV-725-32.
S. Grossberg and G. Carpenter, "A Massively Parallel Architecture for a Self-Organizing Neural Pattern Recognition Machine," Computer Vision, Graphics, and Image Processing (1987, 37, 54-115), pp. 252-315.
R. P. Lippman, "An Introduction to Computing with Neural Nets," IEEE ASSP Magazine, Apr. 1987, pp. 4-22.

Affiliated with

Also associated with

Rating

Neural network apparatus and method for pattern recognition does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Neural network apparatus and method for pattern recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Neural network apparatus and method for pattern recognition will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-997495