Design of a Neural-Based A/D Converter Using Modified Hopfield Network

Bang W. Lee; Bing J. Sheu

doi:10.1109/4.34101

Design of a Neural-Based A/D Converter Using Modified Hopfield Network

Bang W. Lee, Bing J. Sheu

University of Southern California

Research output: Contribution to journal › Journal Article › peer-review

41 Scopus citations

Abstract

The architecture associated with the Hopfield network can be utilized in the VLSI realization of several important engineering optimization functions for the signal processing purpose. The properties of local minima in the energy function of Hopfield networks are investigated. A novel design technique to eliminate these local minima in the Hopfield neural-based analog-to-digital (A/D) converter has been developed. Experimental data agree well with theoretical results in the output characteristics of the neural-based data converter.

Original language	English
Pages (from-to)	1129-1135
Number of pages	7
Journal	IEEE Journal of Solid-State Circuits
Volume	24
Issue number	4
DOIs	https://doi.org/10.1109/4.34101
State	Published - 08 1989
Externally published	Yes

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abstract = "The architecture associated with the Hopfield network can be utilized in the VLSI realization of several important engineering optimization functions for the signal processing purpose. The properties of local minima in the energy function of Hopfield networks are investigated. A novel design technique to eliminate these local minima in the Hopfield neural-based analog-to-digital (A/D) converter has been developed. Experimental data agree well with theoretical results in the output characteristics of the neural-based data converter.",

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Design of a Neural-Based A/D Converter Using Modified Hopfield Network

Abstract

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