Local stability conditions for discrete-time cascade locally recurrent neural networks

Back, A. D. and Tsoi, A. C. (1991). FIR and IIR synapses, A new neural network architecture for time series modelling, Neural Computation 3(3): 375-385.10.1162/neco.1991.3.3.375Search in Google Scholar

Campolucci, P. and Piazza, F. (2000). Intrinsic stability-control method for recursive filters and neural networks, IEEE Transactions on Circuit and Systems—II: Analog and Digital Signal Processing 47(8): 797-802.10.1109/82.861421Search in Google Scholar

Cannas, B., Cincotti, S., Marchesi, M. and Pilo, F. (2001). Learnig of Chua's circuit attractors by locally recurrent neural networks, Chaos Solitons & Fractals 12(11): 2109-2115.10.1016/S0960-0779(00)00174-0Search in Google Scholar

Cao, J., Yuan, K. and Li, H. (2006). Global asymptotical stability of recurrent neural networks with multiple discrete delays and distributed delays, IEEE Transactions on Neural Networks 17(6): 1646-1651.10.1109/TNN.2006.88148817131679Search in Google Scholar

Ensari, T. and Arik, S. (2005). Global stability analysis of neural networks with multiple time varying delays, IEEE Transactions on Automatic Control 50(11): 1781-1785.10.1109/TAC.2005.858634Search in Google Scholar

Fasconi, P., Gori, M. and Soda, G. (1992). Local feedback multilayered networks, Neural Computation 4(1): 120-130.10.1162/neco.1992.4.1.120Search in Google Scholar

Forti, M., Nistri, P. and Papini, D. (2005). Global exponential stability and global convergence in finite time of delayed neural networks with infinite gain, IEEE Transactions on Neural Networks 16(6): 1449-1463.10.1109/TNN.2005.852862Search in Google Scholar

Gori, M., Bengio, Y. and Mori, R. D. (1989). BPS: A learning algorithm for capturing the dynamic nature of speech, International Joint Conference on Neural Networks, Washington DC, USA, Vol. II, pp. 417-423.Search in Google Scholar

Gupta, M. M., Jin, L. and Homma, N. (2003). Static and Dynamic Neural Networks. From Fundamentals to Advanced Theory, John Wiley & Sons, Hoboken, NJ.10.1002/0471427950Search in Google Scholar

Gupta, M. M. and Rao, D. H. (1993). Dynamic neural units with application to the control of unknown nonlinear systems, Journal of Intelligent and Fuzzy Systems 1(1): 73-92.10.3233/IFS-1993-1108Search in Google Scholar

Marcu, T., Mirea, L. and Frank, P. M. (1999). Development of dynamical neural networks with application to observer based fault detection and isolation, International Journal of Applied Mathematics and Computer Science 9(3): 547-570.Search in Google Scholar

Patan, K. (2007). Stability analysis and the stabilization of a class of discrete-time dynamic neural network, IEEE Transactions on Neural Networks 18(3): 660-673.10.1109/TNN.2007.89119917526334Search in Google Scholar

Patan, K. (2008a). Aproximation of state-space trajectories by locally recurrent globally feed-forward neural networks, Neural Networks 21(1): 59-64.10.1016/j.neunet.2007.10.004Search in Google Scholar

Patan, K. (2008b). Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes, Lecture Notes in Control and Information Sciences, Vol. 377, Springer-Verlag, Berlin.Search in Google Scholar

Patan, K. (2008c). Stability criteria for three-layer locally recurrent networks, Proceedings of the 17th IFAC World Congress on Automatic Control, Seoul, Korea, (on CDROM).10.3182/20080706-5-KR-1001.00918Search in Google Scholar

Patan, K. and Parisini, T. (2005). Identification of neural dynamic models for fault detection and isolation: The case of a real sugar evaporation process, Journal of Process Control 15(1): 67-79.10.1016/j.jprocont.2004.04.001Search in Google Scholar

Patan, K., Witczak, M. and Korbicz, J. (2008). Towards robustness in neural network based fault diagnosis, International Journal of Applied Mathematics and Computer Science 18(4): 443-454, DOI: 10.2478/v10006-008-0039-2.10.2478/v10006-008-0039-2Search in Google Scholar

Tsoi, A. C. and Back, A. D. (1994). Locally recurrent globally feedforward networks: A critical review of architectures, IEEE Transactions on Neural Networks 5(2): 229-239.10.1109/72.279187Search in Google Scholar

Xiang-Qun, L. and Zhang, H. Y. (2000). Fault detection and diagnosis of permanent-magnet DC motor based on parameter estimation and neural network, IEEE Transactions on Industrial Electronics 47(5): 1021-1030.10.1109/41.873210Search in Google Scholar

Zhang, J., Morris, A. J. and Martin, E. B. (1998). Long term prediction models based on mixed order locally recurrent neural networks, Computers Chemical Engineering 22(7-8): 1051-1063.10.1016/S0098-1354(97)00269-XSearch in Google Scholar