DocumentCode
2840144
Title
Designing templates for cellular neural networks using particle swarm optimization
Author
Firpi, Hiram A. ; Goodman, Erik D.
Author_Institution
Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
fYear
2004
fDate
13-15 Oct. 2004
Firstpage
119
Lastpage
123
Abstract
Designing or learning of templates for cellular neural networks constitutes one of the crucial research problems of this paradigm. In this work, we present the use of a particle swarm optimizer, a global search algorithm, to design a template set for a CNN. A brief overview of the algorithms and methods is given. Design of popular templates is performed using the search algorithm described.
Keywords
cellular neural nets; optimisation; search problems; cellular neural network; global search algorithm; particle swarm optimization; templates design; Algorithm design and analysis; Birds; Cellular neural networks; Design methodology; Image edge detection; Image processing; Learning systems; Neurons; Nonlinear equations; Particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
ISSN
1550-5219
Print_ISBN
0-7695-2250-5
Type
conf
DOI
10.1109/AIPR.2004.21
Filename
1409685
Link To Document