Title :
General asymmetric neural networks and structure design by genetic algorithms: a learning rule for temporal patterns
Author :
Bornholdt, Stefan ; Graudenz, Dirk
Author_Institution :
Inst. fur Theor. Phys., Heidelberg Univ., Germany
Abstract :
A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback
Keywords :
feedback; genetic algorithms; learning (artificial intelligence); neural nets; feedback; general asymmetric neural networks; genetic algorithms; learning rule; structure design; temporal patterns; Algorithm design and analysis; Artificial neural networks; Biological neural networks; Biological system modeling; Brain modeling; Evolution (biology); Genetic algorithms; Genetic engineering; Neural networks; Neurofeedback;
Conference_Titel :
Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on
Conference_Location :
Le Touquet
Print_ISBN :
0-7803-0911-1
DOI :
10.1109/ICSMC.1993.384939
