DocumentCode
1643550
Title
Cellular neural network design with continuous signals
Author
Schwarz, Stephan ; Mathis, Wolfgang
Author_Institution
Dept. of Electr. Eng., Wuppertal Univ., Germany
fYear
1992
Firstpage
17
Lastpage
22
Abstract
Basic design methods for the class of cellular neural networks (CNNs) with continuous input signals are introduced. The realistic model of CNNs proposed by L.O. Chua and L. Yang (1988) combines components of the Hopfield-net, cellular automata, and of cellular systems. The CNN design methods integrate special conditions for technical architectures with respect to real-time implementations. Hacijan´s polynomial solution method is applied to solve the set of linear inequalities which correspond with the CNN design
Keywords
image processing; linear programming; neural nets; polynomials; CNN; Hopfield-net; cellular automata; cellular neural networks; continuous signals; design; linear inequalities; polynomial; Cellular neural networks; Circuit synthesis; Cloning; Computer networks; Delay; Design methodology; Nonlinear equations; Output feedback; Polynomials; Signal design;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
Conference_Location
Munich
Print_ISBN
0-7803-0875-1
Type
conf
DOI
10.1109/CNNA.1992.274333
Filename
274333
Link To Document