Learning, Recognizing, And Predicting Multiple Groupings Of Patterned Data Using A Masking Field Neural Architecture

Michael A. Cohen; Stephen Grossberg

doi:10.1117/12.939914

11 August 1987 Learning, Recognizing, And Predicting Multiple Groupings Of Patterned Data Using A Masking Field Neural Architecture

Michael A. Cohen, Stephen Grossberg

Author Affiliations +

Proceedings Volume 0752, Digital Optical Computing; (1987) https://doi.org/10.1117/12.939914
Event: OE LASE'87 and EO Imaging Symposium, 1987, Los Angeles, CA, United States

Abstract

One of the fundamental problem areas in perception, cognition, and artificial intelligence concerns the characterization of the functional units into which perceptual and cognitive mechanisms group the patterned information that they process. A core issue concerns the context-sensitivity of these functional units, or the manner in which a grouping into functional units can depend upon the spatiotemporal patterning of all the signals being processed. Another core issue concerns the adaptive tuning of recognition mechanisms, and the manner in which such tuning can alter the groupings which emerge within a context containing familiar elements. Adaptive tuning of recognition processes is one of the mechanisms whereby representations become compressed, chunked, or unitized into coherent recognition codes through experience.

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Michael A. Cohen and Stephen Grossberg "Learning, Recognizing, And Predicting Multiple Groupings Of Patterned Data Using A Masking Field Neural Architecture", Proc. SPIE 0752, Digital Optical Computing, (11 August 1987); https://doi.org/10.1117/12.939914

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