Adaptive multilayer perceptrons with long- and short-term memories

IEEE Transactions on Neural Networks

Volumn 13, Issue 1, 2002, Pages 22-33

  Lo, James T ^a,b   Bassu, Devasis ^a,b  

^a IEEE   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

Adaptive identification; Adaptive multilayer perceptron; Function approximation; Multilayer perceptron (MLP); On line training

Indexed keywords

ADAPTIVE IDENTIFICATION; FUNCTION APPROXIMATION; LONG TERM MEMORY; SHORT TERM MEMORY;

ADAPTIVE ALGORITHMS; ADAPTIVE SYSTEMS; APPROXIMATION THEORY; FUNCTION EVALUATION; LEARNING SYSTEMS;

MULTILAYER NEURAL NETWORKS;

EID: 0036127245     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.977262     Document Type: Article

References (33)

1. Adaptive neurocontrol systems with long- and short-term memories
2. Adaptive system identification by nonadaptively trained neural networks
3. Adaptive optimal filtering by pretrained neural networks
4. Adaptive communication channel equalization by nonadaptively trained neural networks
5. Adaptive critic systems with multiple-term memories
6. Parallel networks that learn to pronounce english text
7. The development of the time-delay neural network architecture for speech recognition
8. The gamma model-A new neural model for temporal processing
9. Identification and control of dynamical systems using neural networks
10. Higher order recurrent networks and grammatical inference
11. Fir and iir synapses, a new neural-network architecture for time series modeling
12. Finding structure in time
13. Recurrent network training with the decoupled extended Kalman filter algorithm
14. Approximation by superpositions of a sigmoidal function
15. On the approximate realization of continuous mappings by neural networks
16. Multilayer feedforward networks are universal approximators
17. On estimation of a probability density function and mode
18. Finite dimensional sensor orbits and optimal nonlinear filtering
19. A theory of networks for approximation and learning
20. Reducing geometric dilution of precision using ridge regression
21. A new method of fitting the Von Bertalanffy growth curve using data on the whelk