Pattern classification using linear programming

Details Pattern classification using linear programming Pattern classification using linear programming

1990-04-09

1994-03-29

MacDonald, Allen R.

395 24, G06F 1518

Patent

active

052992845

ABSTRACT:
A method and apparatus (system) is provided for the separation into and the identification of classes of events wherein each of the events is represented by a signal vector comprising the signals x1, x2, . . . , xj, . . . , xn. The system in principle is different from neural networks and statistical classifiers. The system comprises a plurality of assemblies. The training or adaptation module stores a set of training examples and has a set of procedures (linear programming, clustering and others) that operate on the training examples and determine a set of transfer function and threshold values. These transfer functions and threshold values are installed on a recognized module for use in the identification phase. The training module is extremely fast and can deal with very difficult pattern classification problems that arise in speech and image recognition, robotics, medical diagnosis, warfare systems and others. The systems also exploits parallelism in both the learning and recognition phases.

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Suzuki et al., "A Study of Regular Architectures for Digital Implementation f Neural Networks", 1989 IEEE International Symposium on Circuits and Systems, pp. 82-85.
Jonnada et al., "Clustering and Pattern Class Determination Using Linear Programming", Proceedings of the 1972 International Conference on Cybernetics and Society, pp. 221-225.

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