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East Tennessee State University

Synesthetic Sensor Fusion via a Cross-Wired Artificial Neural Network.

Abstract

dc:description.abstract

<p>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.</p>

Degree

thesis:*
Name thesis:degree_name
MALS (Master of Arts in Liberal Studies)
Level thesis:degree_level
Thesis - unrestricted
Discipline thesis:degree_discipline
Liberal Studies
Year dc:date.issued
2002

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Seneker, Stephen Samuel

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • Copyright by the authors.

Identifiers

dc:identifier.*
Repository record dc:identifier
https://dc.etsu.edu/etd/673
OAI identifier oai:identifier
oai:dc.etsu.edu:etd-1830

Chain of custody

source
Harvested from
East Tennessee State University
Base URL
dc.etsu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Seneker, Stephen Samuel. Synesthetic Sensor Fusion via a Cross-Wired Artificial Neural Network.. Thesis - unrestricted thesis, 2002. https://dc.etsu.edu/etd/673