Title :
A learning algorithm for the dynamics of CNN with nonlinear templates. I. Discrete-time case
Author :
Tetzlaff, Ronald ; Wolf, D.
Author_Institution :
Inst. fur Angewandte Phys., Frankfurt Univ., Germany
Abstract :
A learning algorithm for the dynamics of discrete-time cellular neural networks (DTCNN) with gradient-based nonlinear templates is presented. For modeling the dynamics of nonlinear spatio-temporal systems with DTCNN, the algorithm is applied to find the network parameters. Results for two different nonlinear discrete-time systems are discussed in detail
Keywords :
cellular neural nets; discrete time systems; dynamics; learning (artificial intelligence); nonlinear systems; discrete-time cellular neural networks; dynamics; gradient-based nonlinear templates; learning algorithm; nonlinear discrete-time systems; nonlinear spatio-temporal systems; nonlinear templates; Cellular neural networks; Computer aided software engineering; Design methodology; Heuristic algorithms; Learning systems; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Partial differential equations; Performance analysis;
Conference_Titel :
Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on
Conference_Location :
Seville
Print_ISBN :
0-7803-3261-X
DOI :
10.1109/CNNA.1996.566618
