Date of Award

1-1-2011

Document Type

Thesis

Degree Name

M.S.

Department

Computer Engineering

First Advisor

Richard M. Voyles

Second Advisor

Sean E. Shaheen

Keywords

Districuted Computing, Hardware Neural Network, Neuromorphic Engineering, Organic Bistable Devices, Organic Electronics, Synthetic Neural Network

Abstract

This thesis presents work done simulating a type of organic neuromorphic architecture, modeled after Artificial Neural Network, and termed Synthetic Neural Network, or SNN. The first major contribution of this thesis is development of a single-transistor-single-organic-bistable-device-per-input circuit that approximates behavior of an artificial neuron. The efficacy of this design is validated by comparing the behavior of a single synthetic neuron to that of an artificial neuron as well as two examples involving a network of synthetic neurons. The analysis utilizes electrical characteristics of polymer electronic elements, namely Organic Bistable Device and Organic Field Effect Transistor, created in the laboratory at University of Denver. Polymer electronics is a new branch of electronics that is based on conductive and semi-conductive polymers. These new elements hold a great advantage over the inorganic electronics in the form of physical flexibility and low cost of fabrication. However, their device variability between individual devices is also much greater. Therefore the second major contribution of this thesis is the analysis of resilience of neural networks subjected to physical damage and other manufacturing faults.

Provenance

Recieved from ProQuest

Rights holder

Robert Nawrocki

File size

125 p.

File format

application/pdf

Language

en

Discipline

Computer engineering, Engineering, Artificial intelligence

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