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VLSI implementable associative memory based on neural network architecture Mok, Winston Ki-Cheong

Abstract

Neural network associative memories based on Hopfield's design have two failure modes. 1) Certain memories are not recallable as they do not lie in a local minimum of the system's Liapunov (energy) function, and 2) the associative memory converges to a non-memory location due to trapping by spurious local minima in the energy function surface. The properties of the first failure mechanism in the Hopfield and five related models were investigated. A new architecture eliminating such failures is proposed. The architecture is fully digital and modular. Furthermore, it is more silicon-area efficient than any of the analyzed models. VLSI circuits built using this architecture will be able to contain a large number of neurons and several circuits may be connected together to further increase capacity.

Item Metadata

Title
VLSI implementable associative memory based on neural network architecture
Creator
Mok, Winston Ki-Cheong
Publisher
University of British Columbia
Date Issued
1989
Description
Neural network associative memories based on Hopfield's design have two failure modes. 1) Certain memories are not recallable as they do not lie in a local minimum of the system's Liapunov (energy) function, and 2) the associative memory converges to a non-memory location due to trapping by spurious local minima in the energy function surface. The properties of the first failure mechanism in the Hopfield and five related models were investigated. A new architecture eliminating such failures is proposed. The architecture is fully digital and modular. Furthermore, it is more silicon-area efficient than any of the analyzed models. VLSI circuits built using this architecture will be able to contain a large number of neurons and several circuits may be connected together to further increase capacity.
Genre
Thesis/Dissertation
Type
Text
Language
eng
Date Available
2010-08-30
Provider
Vancouver : University of British Columbia Library
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
DOI
10.14288/1.0064936
URI
http://hdl.handle.net/2429/27942
Degree (Theses)
Master of Applied Science - MASc
Program (Theses)
Electrical and Computer Engineering
Affiliation
Applied Science, Faculty of; Electrical Engineering, Department of
Degree Grantor
University of British Columbia
Campus
UBCV
Scholarly Level
Graduate
Aggregated Source Repository
DSpace

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For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.