Hierarchical pattern recognition system with variable selection weights

A method of pattern recognition in a pattern recognition data processing system comprising:

• storing input signals defining an input pattern in a short term feature representation field of nodes;
• selecting at least one category node of a category representation field comprised of a plurality of nodes representing pattern categories based on a pattern from the short term feature representation field;
• and
• resetting a category selection;
• in selecting at least one category node, generating activation signals at nodes of the category representation field which are a function of signals from nodes of the feature representation field weighted by selection weights, the method further comprising initially setting the selection weights by long term memory and reducing the selection weights in selecting at least one category after reset of a category selection.

A pattern recognition data processing system comprising:

• a short term feature representation field of nodes supporting signals derived from input signals defining an input pattern and template signals defining a long term memory template;
• means for selecting at least one category of a category representation field of nodes based on a pattern from the short term feature representation field;
• means for generating the long term template based on the at least one selected category;
• and
• means for adapting category selection and the long term memory template to the input signals;
• the category representation field comprising a plurality of subfields of nodes supporting short term signals and feedback of short term signals within the category representation.

A method of pattern recognition in a pattern recognition data processing system comprising storing input signals in a short term representation field of nodes;

• selecting at least one category of a category representation field comprised of a plurality of nodes representing pattern categories based on a pattern from the short term feature representation field;
• generating a long term template based on the at least one selected category;
• and
• adapting category selection and the long term memory template to the input signals;
• the method further comprising, in the category representation field, generating short term signals in a plurality of subfields and providing feedback of short term signals within the category representation field.