A multilevel neural network for A/D conversion

Author

Yuh, Jen-Dong ; Newcomb, Robert W.

Author_Institution

Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA

Volume

4

Issue

3

fYear

1993

fDate

5/1/1993 12:00:00 AM

Firstpage

470

Lastpage

483

Abstract

A multilevel neuron is introduced, and its use in a neural network multilevel A/D converter is shown. An energy function suited for multilevel neural networks is defined for which local minima problems for A/D conversion are removed by modifying the method proposed by B.W. Lee and B.J. Sheu (1989, 1991). This energy function extends others in the sense that it allows one to consider more than two discrete levels in the neuron output and threshold settings. It is shown how to build and implement multilevel nonlinearities, and a way of implementing a multilevel neural network for A/D conversion by taking advantage of BiCMOS technologies is demonstrated. Computer simulations are included to illustrate how this design functions, and individual component VLSI chips measurements for multilevel A/D conversion are presented to show how each component operates

Keywords

BiCMOS integrated circuits; VLSI; analogue-digital conversion; neural chips; A/D conversion; BiCMOS technologies; VLSI chips measurements; discrete levels; energy function; local minima problems; multilevel neural network; threshold settings; Application software; Associative memory; BiCMOS integrated circuits; Computer simulation; Hopfield neural networks; Network synthesis; Neural networks; Neurons; Semiconductor device measurement; Very large scale integration;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.217190

Filename

217190