An Adaptive Filter for Noise Cancelling

IEEE Transactions on Circuits and Systems

Volumn 35, Issue 10, 1988, Pages 1201-1209

  Abutaleb, Ahmed S ^a  

^a TEMPLE UNIVERSITY   (United States)

Author keywords

adaptive filtering; Adaptive noise cancelling; invariant imbedding; LMS algorithm; nonlinear estimation; Pontryagin minimum principle

Indexed keywords

MATHEMATICAL TECHNIQUES -- MAXIMUM PRINCIPLE; SIGNAL INTERFERENCE -- SUPPRESSION;

ADAPTIVE FILTER; ADAPTIVE NOISE CANCELLING; INVARIANT IMBEDDING; LMS ALGORITHM; PONTRYAGIN MINIMUM PRINCIPLE;

SIGNAL FILTERING AND PREDICTION;

EID: 0024090823     PISSN: 00984094     EISSN: None     Source Type: Journal    
DOI: 10.1109/31.7595     Document Type: Article

References (16)

1. G. S. Furno, and W. J. Tompkins, “A learning filter for removing noise interference”, IEEE Trans. Biomed. Eng., vol. BME-30, pp. 234-235, Apr. 1983.
2. B. Widrow and S. D. Stearns, Adaptive Signal Processing. Englweood Cliffs, NJ: Prentice-Hall, 1985.
3. B. Widrow, K. M Duvall, R. P. Gooch, and W. C. Newman, “Signal cancellation phenomena in adaptive antennas: Causes and cures”, IEEE Trans. Antennas Propagat., vol. AP-30, pp. 469-478, May 1978.
4. B. Widrow, et al., “Adaptive noise cancelling: principles and applications”, Proc. IEEE, vol. 63, pp. 1692-1716, Dec. 1975.
5. B. Friedlander, “System identification for adaptive noise cancelling”, IEEE Trans. Acoust. Speech Signal Processing, vol. ASSP-30, pp. 699-708, Oct. 1982.
6. P. Heinonen, T. Sarmarki, J. Malmivuo, and Y. Neuvo, “Periodic interference rejection using coherent sampling and waveform estimation”, IEEE Trans. Circuits Syst., vol. CAS-31, pp. 438-446, May 1984.
7. L. Ljung, and T. Soderstrom, Theory and Practice of Recursive Identification. Cambridge, MA; M.I.T. Press 1982.
8. S. S. Narayan, A. M. Peterson, and J. J. Narasimha, “Transform domain LMS algorithm”, IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-31, pp. 609-615, June 1983.
9. L. S. Pontryagin, V. Boltyanskii, R. Gamkrelidze, and E. Mischenko, “The mathematical theory of optimal processes”, New York: Interscience, 1962.
10. R. Bellman, H. Kagiwada, R. Kakaba, and R. Sridhar, “Invariant imbedding and nonlinear filtering theory”, J. Astronaut. Sci., vol. 13, pp. 110-115, May-June 1966.
11. W. B. Mikhael, F. Wu, G. Kang, and L. Fransen, “Optimum adaptive algorithms with applications to noise cancellation”, IEEE Trans. Circuits Syst., vol. CAS-31, pp. 312-315, Mar. 1984.
12. A. Abutaleb, “Adaptive noise cancelling and nonlinear estimation theory”, in Proc. 22nd Ann. Allerton Conf. Univ. of Illinois at Urbana, Chicago, IL Oct. 1984.
13. D. G. Schultz, and J. L. Melsa, State Functions and Linear ControlSystems. New York: McGraw-Hill, 1967.
14. A. Gleb, ed., Applied Optimal Estimation. Cambridge, MA: M.I.T.Press, 1974.
15. H. L. Van Trees, Detection Estimation and Modulation TheoryPart I. New York: Wiley, 1968.
16. M. Vidyasagar, Nonlinear Systems Analysis. Englewood Cliffs, NJ: Prentice-Hall, 1978.