Syntactical computing using pulse-coupled neural network modules

Jason M. Kinser

doi:10.1117/12.258120

11 November 1996 Syntactical computing using pulse-coupled neural network modules

Jason M. Kinser

Proceedings Volume 2824, Adaptive Computing: Mathematical and Physical Methods for Complex Environments; (1996) https://doi.org/10.1117/12.258120
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

The pulse-coupled neural network (PCNN) is a biologically motivated algorithm that has tremendous potential. The PCNN has several inherent properties that make it useful in a variety of applications. This paper introduces a syntactical information processing architecture that is mainly driven by PCNNs. It exploits several of the inherent properties of the PCNN to receive and process information, to convert the information to a syntactical phrase and its 1D form which can then be used to generate an appropriate response to the information received as an input. Examples of PCNN performance which is appropriate for this systems are given.

Citation Download Citation

Jason M. Kinser "Syntactical computing using pulse-coupled neural network modules", Proc. SPIE 2824, Adaptive Computing: Mathematical and Physical Methods for Complex Environments, (11 November 1996); https://doi.org/10.1117/12.258120

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