Nonlinear Adaptive Prediction of Nonstationary Signals

IEEE Transactions on Signal Processing

Volumn 43, Issue 2, 1995, Pages 526-535

  Haykin, Simon ^a   Li, Liang ^a  

^a MCMASTER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

NONLINEAR ADAPTIVE PREDICTION; NONSTATIONARY SIGNALS; PIPELINED RECURRENT NEURAL NETWORKS; TAPPED DELAY LINE FILTER;

ALGORITHMS; NEURAL NETWORKS; SPEECH PROCESSING;

SIGNAL FILTERING AND PREDICTION;

EID: 0029252331     PISSN: 1053587X     EISSN: 19410476     Source Type: Journal    
DOI: 10.1109/78.348134     Document Type: Article

References (16)

1. S. Shuzo and K. Nakata, Fundamentals of Speech Signal Processing. New York: Academic, 1985.
2. N. S. Jayant and P. Noll, Digital Coding of Waveforms. Englewood Cliffs, NJ: Prentice-Hall, 1984.
3. D. Gabor, W. P. L. Wilby, and R. Woodcock, “An universal nonlinear filter, predictor and simulator which optimizes itself by a learning process,” Proc Inst. Elec. Eng., vol. 108, pp. 422-438, 1961.
4. S. Haykin and L. Li, “Real-time nonlinear adaptive prediction of nonstationary signal,” CRL Rep. No. 272, Commun. Res. Lab., McMaster Univ., Oct. 1993.
5. L. Li and S. Haykin, “A cascaded recurrent neural network for real-time nonlinear adaptive filtering,” in Proc. International Conference on Neural Networks (San Francisco), 1993, pp. 857-862.
6. R. J. Williams and D. Zipser, “A learning algorithm for continually running fully recurrent neural networks,” Neural Comput., vol. 1, pp. 270-280, 1989.
7. L. E. McBride, Jr. and K. S. Narendra, “Optimization of time-varying systems,” IEEE Trans. Automat. Contr., vol. 10, 289-294, 1965.
8. D. C. Van Essen, C. H. Anderson, and D. J. Felleman, “Information processing in the primate visual system: An integrated systems perspective,” Sci., 419-423, Jan. 1992.
9. J. C. Houk, “Learning in modular networks,” in Proc. Int. Workshop Adaptive Learning Syst., (New Haven, CT), May 1992, pp. 80-84.
10. S. Haykin, Neural Networks: A Comprehensive Foundation. New York: Macmillan, 1994.
11. Adaptive Filter Theory. Englewood Cliffs, NJ: Prentice-Hall, 1991, 2nd ed.
12. B. Widrow and S. Steams, Adaptive Signal ProcessingEnglewood Cliffs, NJ: Prentice-Hall, 1985.
13. B. S. Atal and S. L. Hanauer, “Speech analysis and synthesis by linear prediction of the speech wave,” J. Acoust. Soc. Amer., vol. 50, pp. 637-655, 1971.
14. B. Townshend, “Nonlinear prediction of speech,” in Proc. Int. Conf Acoust. Speech Signal Processing (Toronto, Canada), 1991, pp. 425-427.
15. S. Haykin and L. Li, “16 kb/s Adaptive differential pulse code modulation of speech,” in Proc. Int. Workshop Applications Neural Networks Telecommun. (Princeton, NJ), 1993, pp. 132-138.
16. L. Li, “Nonlinear adaptive prediction of nonstationary signals and its application to speech communications,” Ph.D. dissertation, Dept. of Elect. and Comput. Eng., McMaster Univ., 1994.