Title :
Evolutionary learning strategies for cellular neural networks
Author :
Kunz, R. ; Tetzlaff, R.
Author_Institution :
Inst. fur Angewandte Phys., Frankfurt Univ., Germany
Abstract :
A learning algorithm for cellular neural networks is presented based on evolutionary strategies. The proposed global optimization procedure is discussed in detail and the performance on various parameter determination problems is shown
Keywords :
cellular neural nets; evolutionary computation; learning (artificial intelligence); optimisation; evolutionary learning strategies; global optimization procedure; parameter determination problems; Cellular neural networks; Concrete; Couplings; Differential equations; Feedback; Image edge detection; Image processing; Neural networks; Partial differential equations; Performance analysis;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
Conference_Location :
Catania
Print_ISBN :
0-7803-6344-2
DOI :
10.1109/CNNA.2000.876852
