Self organizing neural network method and system for general classification of patterns

A method of classifying a pattern into one of a plurality of pattern classes, comprising the steps of:

• converting the pattern to be classified into an image comprising at least one spatial distribution of intensity amplitudes relative to a spatial window on the pattern by disposing a center of the spatial window at a horizontal center and at a vertical center of the pattern to be classified and totally enclosing the pattern to be classified in the spatial window;
• transforming the image with a distribution of weights for each of the plurality of pattern classes into computed correlations for each of the plurality of pattern classes;
• and
• determining a single pattern class of the plurality of pattern classes from the computed correlations, whereby the pattern is classified in said single pattern class.

A system for classifying a pattern into one of a plurality of pattern classes, comprising:

• means for converting a pattern to be classified into an image comprising at least one spatial distribution of intensity amplitudes relative to a spatial window on the pattern;
• means for convolving the image with a plurality of different convolution kernels;
• means for averaging convolutions of the image across spatial sectors within the spatial window;
• means for transforming the averaged convolutions of the image with a distribution of weights for each of the plurality of pattern classes into computed correlations for each of the plurality of pattern classes;
• and
• means for determining a single pattern class of the plurality of pattern classes from the computed correlations, whereby the pattern is classified in said single pattern class.

A system for classifying a pattern into one of a plurality of pattern classes, comprising:

• means for converting a pattern to be classified into an image comprising at least one spatial distribution of intensity amplitudes relative to a spatial window on the pattern, the means for converting comprising means for disposing a center of the spatial window at a horizontal center and at a vertical center of the pattern to be classified and for totally enclosing the pattern to be classified in the spatial window;
• means for transforming the image with a distribution of weights for each of the plurality of pattern classes into computed correlations for each of the plurality of pattern classes;
• and
• means for determining a single pattern class of the plurality of pattern classes from the computed correlations, whereby the pattern is classified in said single pattern class.