Journal article
Volterra series analysis and synthesis of a neural network for velocity estimation
IEEE transactions on systems, man and cybernetics. Part B, Cybernetics, v 29(2), pp 190-197
1999
PMID: 18252292
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The motion detection problem occurs frequently in many applications connected with computer vision. Researchers have studied motion detection based on naturally occurring biological circuits for over a century. In this paper, we propose and analyze a motion detection circuit which is based on nerve membrane conduction. It consists of two unidirectional neural networks connected in an opposing fashion. Volterra input-output (I-O) models are then derived for the network so that velocity estimation can be cast as a parameter estimation problem. The technique is demonstrated through simulation.
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Details
- Title
- Volterra series analysis and synthesis of a neural network for velocity estimation
- Creators
- W S Gray - Old Dominion UniversityB Nabet - Drexel University
- Publication Details
- IEEE transactions on systems, man and cybernetics. Part B, Cybernetics, v 29(2), pp 190-197
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000079319900005
- Scopus ID
- 2-s2.0-0033115776
- Other Identifier
- 991019168601704721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics