Synesthetic sensor fusion via a cross-wired artificial neural network
Abstract (Summary)
Synesthetic Sensor Fusion Via A Cross-Wired Artificial Neural Network
by
Stephen S. Seneker
The purpose of this interdisciplinary study was to examine the behavior of two artificial neural
networks cross-wired based on the synesthesia cross-wiring hypothesis. Motivation for the study
was derived from the study of psychology, robotics, and artificial neural networks, with
perceivable application in the domain of mobile autonomous robotics where sensor fusion is a
current research topic. This model of synesthetic sensor fusion does not exhibit synesthetic
responses. However, it was observed that cross-wiring two independent networks does not
change the functionality of the individual networks but allows the inputs to one network to
partially determine the outputs of the other network in some cases. Specifically, there are
measurable influences of network A on network B, and yet network B retains its ability to
respond independently.
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Bibliographical Information:
Advisor:
School:East Tennessee State University
School Location:USA - Tennessee
Source Type:Master's Thesis
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