Learning, Recognizing, And Predicting Multiple Groupings Of Patterned Data Using A Masking Field Neural Architecture
Michael A. Cohen, Stephen Grossberg · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1987
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.