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Mathematically Inspired Environment Classification and Identification: Simplicial Complex Hierarchy
Intelligent Engineering Systems through Artificial Neural Networks
  • Robert S. Woodley, Missouri University of Science and Technology
  • Christina Welch
  • Matt Insall, Missouri University of Science and Technology
  • Levent Acar, Missouri University of Science and Technology
Abstract

We provide a mathematical foundation for a biologically inspired hierarchical identification and classification system. We describe lines detected by the viual cortex in terms of natural basis elements, upon which simplicial complexes are erected to describe simple objects. Simple objects are basis elements in the next level of the hierarchy, and objects are descirbed simply in terms of them. This is continued through several levels of the hierarchy, and each level identifies somewhat more complex objects onto a manifold the previous level. Projections of the identified objects onto a manifold provides a natural and useful representation of the system's environment.

Meeting Name
Artificial Neural Networks in Engineering Conference, ANNIE 2004 (2004: Nov. 7-10, St. Louis, MO)
Department(s)
Mathematics and Statistics
Second Department
Electrical and Computer Engineering
Keywords and Phrases
  • Neural networks,
  • Artificial life,
  • Complex systems,
  • Fuzzy logic,
  • Programming
International Standard Book Number (ISBN)
0-7918-0228-0
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2004 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
11-10-2004
Publication Date
10 Nov 2004
Citation Information
Robert S. Woodley, Christina Welch, Matt Insall and Levent Acar. "Mathematically Inspired Environment Classification and Identification: Simplicial Complex Hierarchy" Intelligent Engineering Systems through Artificial Neural Networks Vol. 14 (2004) p. 75 - 80
Available at: http://works.bepress.com/levent-acar/19/