A DCT-Based D-FANN for nonlinear adaptive time series prediction

IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing

Volumn 47, Issue 10, 2000, Pages 1131-1134

  Eltoft, Torbjørn ^a   Defigueiredo, Rui J P ^a  

^a UNIVERSITY OF TROMSØ   (Norway)

Author keywords

Adaptive signal processing; Discrete cosine transform; Neural networks; Nonlinear adaptive prediction

Indexed keywords

COSINE TRANSFORMS; DIGITAL FILTERS; FUNCTIONS; MATHEMATICAL MODELS; SIGNAL PROCESSING; SPEECH PROCESSING; TIME SERIES ANALYSIS;

DYNAMICAL FUNCTIONAL ARTIFICIAL NEURAL NETWORK; NONLINEAR ADAPTIVE TIME SERIES PREDICTOR; SPEECH SIGNAL;

MULTILAYER NEURAL NETWORKS;

EID: 0034294810     PISSN: 10577130     EISSN: None     Source Type: Journal    
DOI: 10.1109/82.877160     Document Type: Article

References (13)

1. M. Schetzen Nonlinear system modeling based on the Wiener theory," Proc. IEEE, vol. 69, pp. 1557-1573, Dec. 1981.
2. R. J. P. deFigueiredo and T. A. Dwyer A best approximation framework and implementation for simulation of large-scale nonlinear systems," IEEETrans.CircMtsandSyst.,voLCAS-21,pp. 1005-1014, Nov. 1980.
3. R. J. P. deFigueiredo A generalized Fock space framework for nonlinear system and signal analysis," IEEE Trans. Circuits Syst., vol. CAS-30, pp. 637-647, Sept. 1983.
4. L. V. Zyla and R. J. P. deFigueiredo Nonlinear system identification based on a Fock space framework," SI AM J. Contr. Optimiz., pp. 931-939, Nov. 1993.
5. W. G. Knecht Nonlinear noise filtering and beamforming using the perceptron and its Volterra approximation," IEEE Trans. Acoust, Speech, Signal Processing, vol. 2, pp. 55-62, Jan. 1994.
6. S. Chen, C. F. N. Cowan, and P. M. Grant Orthogonal least squares learning algorithm for radial basis function networks," IEEE Trans. Neural Networks, vol. 2, pp. 302-309, Feb. 1991.
7. P. Werbos Generalization of backpropagation with application to a recurrent gas market model," Neural Networks, vol. 1, pp. 339-356, 1988.
8. A. Weigend, B. Huberman, and D. Rumelhart Predicting the future: A connectionist approach," Int. J. Neural Syst., vol. 7, no. 31, pp. 40330, 1990.
9. E. Wan Temporal backpropagation for FIR neural networks," in Proc. Int. Joint Conf. Neural Networks, San Diego, CA, May 1-3, 1990, pp. 575-580.
10. R. J. P. deFigueiredo A neural network model for nonlinear predictive coding in Fock space," in Proc. IEEE Int. Symp. Circuits and Systems, Chicago, IL, May 1993, pp. 2164-2167.
11. Optimal interpolating and smoothing functional artificial neural networks (FANN's) based on a generalized Fock space framework," Circuits Syst. Signal Processing, vol. 17, no. 2, pp. 271-287, 1998.
12. A new nonlinear functional analytic framework for modeling artificial neural networks (invited paper)," in Proc. IEEE Int. Symp. Circuits and Systems, New Orleans, LA, May 1-3, 1990, pp. 723-726.
13. S. Haykin and L. Li Nonlinear adaptive prediction of nonstationary signals," IEEE Trans. Signal Processing, vol. 43, pp. 526-535, Feb. 1995.