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University of Illinois at Urbana-Champaign

Models of Neurons in the Superior Colliculus and Unsupervised Learning of Parameters From Time Series

Abstract

dc:description

In addition, this research presents a biologically feasible unsupervised learning algorithm for learning parameter values from transiently presented stimuli. The algorithm is used to learn temporal relationships between stimuli and amplitudes.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Seguin, Christopher A.
Contributors dc:contributor
  • Sylvian R. Ray

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI9912373
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/81935

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Seguin, Christopher A.. Models of Neurons in the Superior Colliculus and Unsupervised Learning of Parameters From Time Series. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/81935