Title :
Counterexample of a claim pertaining to the synthesis of a recurrent neural network
Author :
Cai, Xindi ; Wunsch, Donald C., II
Author_Institution :
Appl. Computational Intelligence Lab., Missouri Univ., Rolla, MO, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
Recurrent neural networks have received much attention due to their nonlinear dynamic behavior. One such type of dynamic behavior is that of setting a fixed stable state. This paper shows a counterexample to the claim of A.N. Michel et al. (IEEE Control Systems Magazine, vol. 15, pp. 52-65, Jun. 1995), that "sparse constraints on the interconnecting structure for a given neural network are usually expressed as constraints which require that pre-determined elements of T [a real n×n matrix acting on a real n-vector valued function] be zero", for the synthesis of sparsely interconnected recurrent neural networks
Keywords :
constraint theory; network synthesis; recurrent neural nets; sparse matrices; stability; fixed stable state; neural net interconnecting structure; nonlinear dynamic behavior; pre-determined matrix elements; recurrent neural network synthesis; sparse constraints; sparsely interconnected networks; Algorithm design and analysis; Biological neural networks; Biological system modeling; Computational intelligence; Laboratories; Network synthesis; Neural networks; Neurofeedback; Recurrent neural networks; Stability analysis;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007451