Title :
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
fDate :
5/1/1993 12:00:00 AM
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;
Journal_Title :
Neural Networks, IEEE Transactions on
