DocumentCode
1486690
Title
Volterra series analysis and synthesis of a neural network for velocity estimation
Author
Gray, W. Steven ; Nabet, Bahram
Author_Institution
Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA
Volume
29
Issue
2
fYear
1999
fDate
4/1/1999 12:00:00 AM
Firstpage
190
Lastpage
197
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
Keywords
Volterra series; computer vision; image motion analysis; neural net architecture; parameter estimation; Volterra series analysis; biological circuits; computer vision; motion detection problem; nerve membrane conduction; neural network; parameter estimation; simulation; velocity estimation; Application software; Biological system modeling; Biomembranes; Circuit simulation; Circuit synthesis; Computer vision; Motion detection; Network synthesis; Neural networks; Parameter estimation;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
1083-4419
Type
jour
DOI
10.1109/3477.752793
Filename
752793
Link To Document