Date of Award
Fall 12-1-2004
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical Engineering
First Advisor
David Beach
Second Advisor
Tad Foster
Third Advisor
Douglas Herrmann
Abstract
It is difficult to be certain about brain functioning. Until now, most efforts to understand brain computations have only been conducted on a stand alone computer. In order to recreate the brain accurately, members of the Institute of Cognitive Computing Technology (ICCT) were interested in finding out whether or not a biological process could be simulated on a Distributed Artificial Neural Network (DANN). The goal of this investigation was to implement visual perception on a network of computers and compare the computations of the network with those of a human brain. The distributed network was developed as a Local Area Network in the ICCT lab at Indiana State University using three computers and a Cisco switch. The stimulus selected to teach and test the network was a modified version of Fisher's iris data measured with the vision system. In this study, only sepal length and width were used as inputs. Using a backpropagation structure, the network was trained and validated in a distributed environment. The network performance was then compared to that of a human brain, revealing similarities between the two.
Recommended Citation
Takizala, Tide Kansona, "Using Distributed Network Systems to Model Perception With An Artificial Neural Network" (2004). All-Inclusive List of Electronic Theses and Dissertations. 3736.
https://scholars.indianastate.edu/etds/3736