Noisy recurrent neural networks: The discrete-time case

IEEE Transactions on Neural Networks

Volumn 9, Issue 5, 1998, Pages 937-946

  Olurotimi, Oluseyi ^a   Das, Soumitra ^a  

^a Krasnow Institute for Advanced Study   (United States)

Author keywords

Noise; Nonlinear control and identification; Recurrent neural networks; Stochastic dynamical systems; Trajectory learning

Indexed keywords

DISCRETE TIME CONTROL SYSTEMS; IDENTIFICATION (CONTROL SYSTEMS); LEARNING SYSTEMS; MATHEMATICAL MODELS; NONLINEAR CONTROL SYSTEMS; RANDOM PROCESSES; WHITE NOISE;

STOCHASTIC SYSTEMS;

RECURRENT NEURAL NETWORKS;

EID: 0032162942     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.712165     Document Type: Article

References (6)

1. S. Das and O. Olurotimi, "Noisy recurrent neural networks: The continuous-time case," IEEE Trans. Neural Networks, vol. 9, pp. 913-936 1998.
2. W. J. Rugh, Linear System Theory. Englewood Cliffs, NJ: Prentice-Hall, 1996.
3. T. Kailath, Linear Systems. Englewood Cliffs, NJ: Prentice-Hall, 1980.
4. B. W. Lindgren, Statistical Theory. New York: Macmillan, 1976.
5. A. Papoulis, Probability, Random Variables, and Stochastic Processes. New York: McGraw-Hill, 1965.
6. W. Rudin, Principles of Mathematical Analysis. New York: McGraw-Hill, 1976.