Stability analysis of a self-organizing neural network with feedforward and feedback dynamics

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 2, Issue , 2004, Pages 1505-1509

  Meyer Bäse, Anke ^a   Pilyugin, Sergei S ^b   Wismuller A ^a  

^a FLORIDA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

K-MONOTONE THEORY; PONTRYAGIN MINIMUM PRINCIPLE; SUPERVISED LEARNING; SUPERVISED SYNAPTIC LEARNING;

BACKPROPAGATION; COGNITIVE SYSTEMS; FEEDFORWARD NEURAL NETWORKS; LEARNING ALGORITHMS; LEARNING SYSTEMS; LYAPUNOV METHODS; MULTILAYER NEURAL NETWORKS; PERTURBATION TECHNIQUES; PROBLEM SOLVING; RECURRENT NEURAL NETWORKS; SYSTEM STABILITY; THEOREM PROVING;

SELF ORGANIZING MAPS;

EID: 10944242278     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2004.1380176     Document Type: Conference Paper

References (9)

1. [Ama82] S. Amari. Competitive and cooperative aspects in dynamics of neural excitation and self-organization. Competition and cooperation in neural networks, 20:1-28, 7 1982.
2. [GLW99] M. Galicki, L. Leistritz und H. Witte. Learning continuous trajectories in recurrent neural networks with time-dependent weights. IEEE Transactions on Neural Networks, 10:741-756, 9 1999.
3. [Gro76] S. Grossberg. Adaptive pattern classification and universal recording. Biological Cybernetics, 23:121-134, 1 1976.
4. [JG99] L. Jin und M. Gupta. Stable dynamic backpropagation learning in recurrent neural networks. IEEE Transactions on Neural Networks, 10:1321-1334, 9 1999.
5. [LK89] M. Lemmon und V. Kumar. Emulating the dynamics for a class of laterally inhibited neural networks. Neural Networks, 2:193-214, 4 1989.
6. [MBOS96] A. Meyer-Bäse, F. Ohl und H. Scheich. Singular perturbation analysis of competitive neural networks with different time-scales. Neural Computation, Seiten 545-563, 8 1996.
7. [MBPC03] A. Meyer-Bäse, S. Pilyugin und Y. Chen. Global exponential stability of competitive neural networks with different time scales. IEEE Transactions on Neural Networks, Seiten 716-719, 2 2003.
8. [SMV00] J. Suykens, B. Moor und J. Vandewalle. Robust local stability of multilayer recurrent neural networks. IEEE Transactions on Neural Networks, 11:222-229, 9 2000.
9. [WvdM76] D. J. Willshaw und C. von der Malsburg. How patterned neural connections can be set up by self-organization. Proc. Royal Society London B, 194:431-445, 1976.