Modular learning strategy for signal detection in a nonstationary environment

IEEE Transactions on Signal Processing

Volumn 45, Issue 6, 1997, Pages 1619-1637

  Haykin, Simon ^a   Bhattacharya, Tarun Kumar ^a  

^a MCMASTER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; FEEDFORWARD NEURAL NETWORKS; FREQUENCY DOMAIN ANALYSIS; LEARNING SYSTEMS; MATHEMATICAL TRANSFORMATIONS; TIME DOMAIN ANALYSIS; TIME VARYING SYSTEMS;

CONSTANT FALSE ALARM RATE (CFAR) PROCESSING; WIGNER VILLE DISTRIBUTION (WVD);

SIGNAL DETECTION;

EID: 0031165442     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.600003     Document Type: Article

References (33)

1. A. J. Viterbi, "Wireless digital communications: A view based on three lessons learned,"IEEE Commun. Mag., vol. 29, pp. 33-36, Sept. 1991.
2. S. Haykin, "Neural networks expand SP's horizons,"IEEE Signal Pmessing Mag., vol. 13, Mar. 1996.
3. L. Cohen, 'Time-frequency distributions-A review,"Proc. IEEE, vol. 77, pp. 941-981, 1989.
4. Time-Frequency Analysis. Englewood Cliffs, NJ: PrenticeHall, 1995.
5. B. Boashash, "Time-frequency signal analysis,"in Advances in Spectrum Analysis and Array Processing, S. Haykin, Ed. Englewood Cliffs, NJ: Prentice-Hall, 1991, vol. 1, pp. 418-517.
6. L. Cohen, "Generalized phase-space distribution functions," J. Math. Phys., vol. 7, pp. 781-786, 1966.
7. P. Flandrin, "Non-destructive evaluation in the time-frequency domain by means of the Wigner-Ville distribution,"in Signal Processing and Pattern Recognition in Nondestructive Evaluation of Materials, C. H. Chen, Ed. New York: Springer-Verlag. 1988, pp. 109-116.
8. M. G. Amin and M. T. Schiavoni, "Time-varying spectrum estimation via multidimensional filter representation,"SPIE, Advanced Algorithms Architectures Signal Processing, vol. 1152, pp. 43748, 1989.
9. L. B. White, "Time frequency filtering and synthesis from convex projections,"SPIE Advanced Signal Processing Algorithms, Architectures Implementations, vol. 1348, pp. 158-169, 1990.
10. B. D. F'orrester, "Time-frequency analysis in machine fault detection,"in Time-Frequency Signal Analysis, B. Boashash, Ed. London, U.K.: Longman, 1992, pp. 406-423.
11. W. J. Williams, H. P. Zaveri, and J. C. Sackallares, "Time-frequency analysis of electrophysiology signals in epilepsy,"IEEE Eng. Med. Biol, pp. 133-143, MarVApr. 1995.
12. H. P. Zaveri, W. J. Williams, L. D. Jasemedis, and J. C. Sackallares, "Time-frequency representation of electrocardiograms in temporal like epilepsy,"IEEE Trans. Biomed. Eng., vol. 39, pp. 502-509, 1992.
13. R. A. Altes, "Signal processing for target recognition in bisonar,"Neural Networks, vol. 8, pp. 1275-1295.
14. N. Suga, "Bisonar and neural computation in bats,"Sei. Amer., vol. 262, no. 6, pp. 60-68, 1990.
15. J. A. Simmons et al, "Composition of bisonar images for target recognition by echolocation bats," Neural Networks, vol. 8, pp. 1239-1261, 1995.
16. J. Fukunaga, Statistical Pattern Recognition, 2nd ed. New York: Academic, 1990.
17. P. Flandrin, "A time-frequency formulation of optimum detection,"IEEE Trans. Signal Processing, vol. 36, pp. 1377-1384, 1988.
18. L. B. White and B. Boashash, "Time-frequency coherence in a theoretical basis for cross-spectral analysis of nonstationary signals,"in Proc. IASTED Int. Symp. Signal Processing. Appl, Brisbane, Australia, 1987, pp. 18-23.
19. S. S. Abeysekera and B. Boashash, "Methods of signal classification using the images produced by the Wigner-Ville distribution,"Pattern Recogn. Lett., vol. 12, pp. 717-729, 1991.
20. F. Hlawatsch, "Regularity and unitarity of bilinear time-frequency signal representations,"IEEE Trans. Inform. Theory, vol. 38, pp. 82-94, Jan. 1992.
21. "Bilinear time-frequency representations of signals: The shiftscale invariant class,"IEEE Trans. Signal Processing, vol. 42, pp. 357-366, Feb. 1994.
22. T. K. Bhattacharya and S. Haykin, "Neural network-based radar detection for an ocean'environment,"IEEE Trans. Aerospace Electron. Syst., to be published.
23. H. L. Van Trees, Detection, Estimation, and Modulation Theory, Pan I. New York: Wiley, 1968.
24. A. J. Viterbi and J. K. Omura, Principles of Digital Communication. New York: McGraw-Hill, 1979.
25. C. A. Stutt and L. J. Spafford, "A 'best' mismatched filter response for radar clutter discrimination,"IEEE Trans. Inform. Theory, vol. IT-14, pp. 280-287, 1968.
26. M. P. Perrone and L. N. Cooper, "Learning what's been learned: Supervised learning from multi-neural network systems,"in Proc. World Congr. Neural Networks, 1993, vol. 3, pp. 354-357.
27. T. D. Sanger, "Optimal unsupervised learning in a single-layer linear feedforward neural network,"Neural Networks, vol. 1, pp. 45973, 1989.
28. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning representations by back-propagation errors,"Nature, vol. 323, pp. 533-536, 1986.
29. S. Haykin, Neural Networks: A Comprehensive Foundation. New York: Macmillan, 1994.
30. S. Haykin, C. Krasnor, T. Nohara, B. Currie, and D. Hamburger, "A coherent dual-polarized radar for studying the ocean environment,"IEEE Trans. Geosci. Remote Sensing, vol. 29, pp. 189-191, 1991.
31. Y. LeCun et al, "Handwritten digit recognition with a back-propagation network," in Advances in Neural Information Processing Systems, D. S. Touretzky, Ed. San Francisco, ÇA: Morgan Kaufmann, 1989, vol. 2, pp. 396-404.
32. P. Weber and S. Haykin, "IPIX radar signal processing and detection," CRL Rep. 319, Commun. Res. Lab., McMaster Univ., Hamilton, Ont., 1992.
33. S. Haykin and T. K. Bhaltacharya, "Wigner-Ville distribution: An important functional block for radar target detection in clutter,"in Conf. Rec. Twenty-Eighth Asilomar Conf. Signals Syst., Comput., Pacific Grove, CA, 1994, vol. 1, pp. 68-72.