Functional Decomposition and its Applications in Design of Digital Circuits and Machine Learning

Document Type

Article

Publication Date

9-2001

Publication Title

International Journal of Computational Intelligence and Applications

Volume

1

Issue

3

First page number:

259

Last page number:

271

Abstract

In this paper, we will begin with an overview of functional decomposition algorithms based on different graph coloring heuristics. We will then discuss the applications of decomposition strategy for the computer aided design of digital circuits and for the supervised learning of neural networks. While decomposition was used successfully in logic synthesis for several years, its application in the area of neural networks is a novel and promising approach. The computer experiments will show significant benefits in mini mization of silicon space required for digital circuit implementation as well as in reduction of training time for neural networks.

Keywords

Computer algorithms; Decomposition method; Neural networks (Computer science)

Disciplines

Computer Engineering | Digital Circuits | Electrical and Computer Engineering | Signal Processing | Systems and Communications

Language

English

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Use Find in Your Library, contact the author, or use interlibrary loan to garner a copy of the article. Publisher copyright policy allows author to archive post-print (author’s final manuscript). When post-print is available or publisher policy changes, the article will be deposited

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