Distortion-Invariant Associative Memories And Processors

David Casasent; Brian Telfer

doi:10.1117/12.976205

10 December 1986 Distortion-Invariant Associative Memories And Processors

David Casasent, Brian Telfer

Proceedings Volume 0697, Applications of Digital Image Processing IX; (1986) https://doi.org/10.1117/12.976205
Event: 30th Annual Technical Symposium, 1986, San Diego, United States

Abstract

Associative memories represent a major new artificial intelligence type of processor. We consider their use in pattern recognition, with particular attention to distortion-invariant and adaptive pattern recognition. New associative memory techniques and pattern recognition oriented architectures suitable for multi-class distortion-invariant pattern recognition (including systems that provide adaptive updating, forgetting, achieve reduced dynamic range and improved performance) are discussed and initial results presented. The first results of distortion-invariance, multi-class associative memories for pattern recognition are presented together with new architectures and algorithms for multi-stage associative processors, iterative processors for associative memory synthesis, and multi-class distortion-invariant associative processors. The issue of orthogonal projection vectors, associative memory capacity and new results and techniques to synthesize associative memories are included throughout.

Citation Download Citation

David Casasent and Brian Telfer "Distortion-Invariant Associative Memories And Processors", Proc. SPIE 0697, Applications of Digital Image Processing IX, (10 December 1986); https://doi.org/10.1117/12.976205

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