Detection of non-Gaussian signals: a paradigm for modern statistical signal processing

Proceedings of the IEEE

Volumn 82, Issue 7, 1994, Pages 1061-1095

  Garth, Lee M ^a   Poor, H Vincent ^a  

^a CTS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DIGITAL COMMUNICATION SYSTEMS; NEURAL NETWORKS; SIGNAL PROCESSING; SONAR; SPECTRUM ANALYSIS; STATISTICAL METHODS;

MODERN STATISTICAL SIGNAL PROCESSING; NON GAUSSIAN SIGNAL; NONLINEAR SIGNAL PROCESSING; STATISTICAL SIGNAL PROCESSING; WAVELET DECOMPOSITION;

SIGNAL DETECTION;

EID: 0028467324     PISSN: 00189219     EISSN: None     Source Type: Journal    
DOI: 10.1109/5.293163     Document Type: Article

References (205)

1. B. Widrow S. D. Stearns Adaptive Signal Processing 1985 Prentice-Hall NJ, Englewood Cliffs
2. J. L. Hibey D. L. Snyder J. H. van Schuppen Error-probability bounds for continuous-time decision problems IEEE Trans. Informat. Theory IT-24 5 608 622 Sept. 1978
3. M. H. A. Davis E. Andreadakis Exact and approximate filtering in signal detection: An example IEEE Trans. Informat. Theory IT-23 768 772 Nov. 1977
4. V. E. Beneš Stochastics Monographs 5 447 510 1990 Gordon and Breach UK, London Nonlinear filtering in sonar detection and estimation I: probabilities of detection errors
5. L. R. Rabiner A tutorial on hidden Markov models and selected applications in speech recognition Proc. IEEE 77 2 257 286 Feb. 1989
6. S. A. Kassam Signal Detection in Non-Gaussian Noise 1988 Springer-Verlag Germany, Berlin
7. H. V. Poor An Introduction to Signal Detection and Estimation 2nd 1994 Springer-Verlag New York
8. C. W. Helstrom Statistical Theory of Signal Detection 1968 Pergamon UK, Oxford
9. I. V. Girsanov On transforming a certain class of stochastic processes by absolutely continuous substitution of measures Theor. Probability Appl. 5 285 301 1960
10. T. Kailath A general likelihood-ratio formula for random signals in Gaussian noise IEEE Trans. Informal. Theory IT-15 3 350 361 May 1969
11. T. E. Duncan Likelihood functions for stochastic signals in white noise Inform. Contr. 16 303 310 1970
12. T. T. Kadota Nonsingular detection and likelihood ratio for random signals in white Gaussian noise IEEE Trans. Informat. Theory IT-16 3 291 298 May 1970
13. J. E. Mazo J. Salz Probability of error for quadratic detectors Bell Syst. Tech. J. 44 2165 2186 1965
14. C. R. Baker Optimum quadratic detection of a random vector in Gaussian noise IEEE Trans. Commun. Technol. COM-14 6 802 805 Dec. 1966
15. C. R. Baker On the deflection of a quadratic-linear test statistic IEEE Trans. Informal. Theory IT-15 1 16 21 Jan. 1969
16. V. Veeravalli H. V. Poor Quadratic detection of signals with drifting phase J. Acoust. Soc. Amer. 89 2 811 819 Feb. 1991
17. A. F. Gualtierotti A likelihood ratio formula for spherically invariant processes IEEE Trans. Informal. Theory IT-22 610 Sept. 1976
18. B. Picinbono Spherically invariant and compound Gaussian stochastic processes IEEE Trans. Informat. Theory IT-16 1 77 79 Jan. 1970
19. K. Yao A representation theorem and its applications to spherically-invariant random processes IEEE Trans. Informat. Theory IT-19 5 600 608 Sept. 1973
20. P. L. Brockett W. N. Hudson H. G. Tucker The distribution of the likelihood ratio for additive processes J. Multivariate Anal. 8 233 243 1978
21. P. L. Brockett The likelihood ratio detector for non-Gaussian infinitely divisible and linear stochastic processes Ann. Statist. 12 737 744 1984
22. R. Lugannani J. B. Thomas On a class of stochastic processes which are closed under linear transformations Informat. Contr. 10 1 21 Jan. 1967
23. D. Middleton Man-made noise in urban environments and transportation systems: models and measurements IEEE Trans. Commun. COM-21 1232 1241 1973
24. C. R. Baker A. F. Gualtierotti Stochastic Processes in Underwater Acoustics 85 154 180 1986 Springer-Verlag Germany, Berlin Likelihood ratios and signal detection for non-Gaussian processes
25. C. R. Baker A. F. Gualtierotti Discrimination with respect to a Gaussian process Probab. Theory Rel. Fields 71 159 182 1986
26. C. R. Baker A. F. Gualtierotti Advances in Statistical Signal Processing-Volume 2: Signal Detection 1 34 1993 JAI Press CT, Greenwich Likelihood-ratio detection of stochastic signals
27. L. F. Eastwood R. Lugannani Approximate likelihood ratio detectors for linear processes IEEE Trans. Informat. Theory IT-23 4 482 489 July 1977
28. R. S. Liptser A. N. Shiryayev Statistics of Random Processes I: General Theory 1977 Springer-Verlag Germany, Berlin
29. V. E. Beneš Advances in Statistical Signal Processing-Volume I: Estimation 1 14 1987 JAI Press CT, Greenwich Nonlinear filtering: problems, examples, applications
30. R. Brockett J. M. C. Clark Analysis and Optimization of Stochastic Systems 1980 Academic Press New York The geometry of the conditional density equation
31. A. P. Dempster N. M. Laird D. B. Rubin Maximum likelihood from incomplete data via the EM algorithm (with discussion) J. Roy. Statist. Soc. 39 1 38 1977
32. S. C. Schwartz The estimator-correlator for discrete-time problems IEEE Trans. Informat. Theory IT-23 1 93 100 Jan. 1977
33. H. V. Poor Optimum memoryless tests based on dependent data J. Combinatorics, Informat. Syst. Sci. 6 2 111 122 1981
34. H. V. Poor Detection of broadband signals in signal-dependent noise J. Acoust. Soc. Amer. 87 3 1227 1230 Mar. 1990
35. H. V. Poor Signal detection in the presence of weakly dependent noise—Part I: Optimum detection IEEE Trans. Informat. Theory IT-28 5 735 744 Sept. 1982
36. H. V. Poor C. I. Chang A reduced-complexity quadratic structure for the detection of stochastic signals J. Acoust. Soc. Amer. 78 5 1652 1657 Nov. 1985
37. H. V. Poor J. B. Thomas Locally-optimum detection of discrete-time stochastic signals in non-Gaussian noise J. Acoust. Soc. Amer. 63 1 75 80 Jan. 1978
38. S. A. Kassam H. V. Poor Robust techniques for signal processing: a survey Proc. IEEE 73 3 433 481 Mar. 1985
39. H. V. Poor Communications and Networks: A Survey of Recent Advances 131 156 1986 Springer-Veriag New York Robustness in signal detection
40. M. E. Zervakis T. M. Kwon Robust estimation techniques in regularized image restoration Opt. Eng. 31 10 2174 2190 Oct. 1992
41. M. E. Zervakis T. M. Kwon On the application of robust functional in regularized image restoration Proc. 1993 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing V289 V292 Proc. 1993 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Minneapolis MN 1993-Apr.-27-30
42. C. L. Nikias M. R. Raghuveer Bispectrum estimation: a digital signal processing framework Proc. IEEE 75 7 869 891 July 1987
43. C. L. Nikias J. M. Mendel Signal processing with higher-order spectra IEEE Signal Process. Mag. 10 3 10 37 July 1993
44. C. L. Nikias A. P. Petropulu Higher-Order Spectral Analysis: A Nonlinear Signal Processing Framework 1993 Prentice-Hall NJ, Englewood Cliffs
45. D. R. Brillinger M. Rosenblatt Spectral Analysis of Time Series 153 158 1967 Wiley New York Asymptotic theory of kth-order spectra
46. D. R. Brillinger M. Rosenblatt Spectral Analysis of Time Series 189 232 1967 Wiley New York Computation and interpretation of kth-order spectra
47. V. Chandran S. Elgar A general procedure for the derivation of principal domains of higher-order spectra IEEE Trans. Signal Process. 42 1 229 233 Jan. 1994
48. T. S. Rao M. M. Gabr A test for linearity of stationary time series J. Time Series Anal. 1 2 145 158 1980
49. M. J. Hinich Testing for Gaussianity and linearity of a stationary time series Time Series Anal. 3 3 169 176 1982
50. G. B. Giannakis M. K. Tsatsanis Signal detection and classification using matched filtering and higher-order statistics IEEE Trans. Acoust., Speech, Signal Process. 38 7 1284 1296 July 1990
51. A. V. Dandawaté G. B. Giannakis Asymptotic properties and covariance expressions of kth-order sample moments and cumulants Proc. 27th Asilomar Conf. on Signals, Systems, and Computers Proc. 27th Asilomar Conf. on Signals, Systems, and Computers 1993-Nov.-1-3
52. B. Porat B. Friedlander Performance analysis of parameter estimation algorithms based on high-order moments Int. J. on Adaptive Control and Signal Processing 3 2 191 230 Sept. 1989
53. G. B. Giannakis M. K. Tsatsanis A unifying maximum-likelihood view of cumulant and polyspectral measures for non-Gaussian signal classification and estimation IEEE Trans. Informat. Theory 38 2 386 406 Mar. 1992
54. E. L. Lehmann Testing Statistical Hypotheses 2nd 1986 Wiley New York
55. L. M. Garth Y. Bresler A comparison of optimized higher-order detection techniques Proc. 28th Annual Conf. on Information Sciences and Systems Proc. 28th Annual Conf. on Information Sciences and Systems Princeton NJ 1994-Mar.-16-18
56. D. Kletter H. Messer Suboptimai detection of non-Gaussian signals by third-order spectral analysis IEEE Trans. Acoust., Speech, Signal Process. 38 6 901 909 June 1990
57. M. J. Hinich G. R. Wilson Detection of non-Gaussian signals in non-Gaussian noise using the bispectrum IEEE Trans. Acoust., Speech, Signal Process. 38 7 1126 1130 July 1990
58. R. F. Dwyer A statistical frequency domain signal processing method Proc. 16th Annual Conf. on Information Sciences and Systems 604 608 Proc. 16th Annual Conf. on Information Sciences and Systems Princeton NJ 1982
59. R. F. Dwyer Detection of non-Gaussian signals by frequency domain kurtosis estimation Proc. 1983 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 607 610 Proc. 1983 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1983
60. R. F. Dwyer Use of the kurtosis statistic in the frequency domain as an aid in detecting random signals IEEE J. Ocean. Eng. OE-9 2 85 92 Apr. 1984
61. R. F. Dwyer Asymptotic detection performance of discrete power and higher-order spectra estimates IEEE J. Ocean. Eng. OE-10 3 303 315 July 1985
62. R. F. Dwyer Erratum: asymptotic detection performance of discrete power and higher-order spectra estimates IEEE J. Ocean. Eng. OE-11 1 136 Jan. 1986
63. T. S. Ferguson On the rejection of outliers Proc. 4th Berkeley Symp. on Mathematical Statistics and Probability 253 287 Proc. 4th Berkeley Symp. on Mathematical Statistics and Probability Berkeley CA 1961
64. M. J. Hinich C. S. Clay The application of the discrete Fourier transform in the estimation of power spectra, coherence, and bispectra of geophysical data Rev. Geophys. 6 3 347 363 Aug. 1968
65. E. S. Pearson A further development of tests for normality Biometrika 16 237 249 1930
66. B. H. Maranda J. A. Fawcett The performance analysis of a fourth-order detector Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1357 1360 Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Albuquerque NM 1990-Apr.-3-6
67. T. W. Epps Testing that a stationary time series is Gaussian Ann. Statist. 15 1683 1698 1987
68. A. M. Zoubir Gaussianity test for zero-skewed real and complex data Proc. IEEE Work, on Higher-Order Spectral Analysis 327 331 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
69. E. Moulines J. W. D. Molle K. Choukri M. Charbit Testing that a stationary time-series is Gaussian: time-domain vs. frequency-domain approaches Proc. IEEE Work, on Higher-Order Spectral Analysis 336 340 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
70. B. M. Sadler Sequential detection using higher-order statistics Proc. 1991 IEEE Int. Conf. Acoustics, Speech, and Signal Processing 3525 3528 Proc. 1991 IEEE Int. Conf. Acoustics, Speech, and Signal Processing Toronto 1991-May-14-17
71. G. B. Giannakis A. V. Dandawaté Detection and classification of non-stationary underwater acoustic signals using cyclic cumulants Proc. Underwater Signal Processing Workshop Proc. Underwater Signal Processing Workshop 1991-Oct.
72. G. R. Wilson W. Ellinger Detection of chaotic processes in Gaussian noise at low signal to noise ratios using higher-order spectra Proc. IEEE Work, on Higher-Order Spectral Analysis Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
73. M. J. Hinich Detecting a transient signal by bispectral analysis IEEE Trans. Acoust., Speech, Signal Process. 38 7 1277 1283 July 1990
74. C. M. Pike J. A. Tague E. J. Sullivan Transient signal detection in multipath: a bispectral analysis approach Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1489 1492 Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Toronto 1991-May-14-17
75. P. O. Amblard J. L. Lacoume J. M. Brassier Transient detection, higher-order time-frequency distributions and the entropy Proc. IEEE Work, on Higher-Order Spectral Analysis 265 269 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
76. E. Sangfelt L. Persson Experimental performance of some higher-order cumulant detectors for hydroacoustic transients Proc. IEEE Work, on Higher-Order Spectral Analysis 182 186 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
77. I. Jouny R. L. Moses F. D. Garber Classification of radar signals using the bispectrum Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 3429 3432 Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Toronto 1991-May-14-17
78. I. Jouny Classification of clutter using the bispectrum Proc. IEEE Work, on Higher-Order Spectral Analysis 245 249 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
79. R. D. Pierce Detection of radar targets using HOS Proc. IEEE Work, on Higher-Order Spectral Analysis 314 318 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
80. J. Reichert Automatic classification of communication signals using higher-order statistics Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing V-221 V-224 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
81. R. F. Dwyer Identification of acoustic objects in motion from the fourth-order cumulant spectrum Proc. IEEE Work, on Higher-Order Spectral Analysis 250 254 Proc. IEEE Work, on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
82. R. W. Barker M. J. Hinich Statistical monitoring of rotating machinery by cumulant spectral analysis Proc. IEEE Work. on Higher-Order Spectral Analysis 187 191 Proc. IEEE Work. on Higher-Order Spectral Analysis South Lake Tahoe CA 1993-June-7-9
83. R. O. Duda P. E. Hart Pattern Classification and Scene Analysis 1973 Wiley New York
84. D. R. Brillinger Time Series: Data Analysis and Theory 1981 Holden-Day CA, San Francisco
85. R. P. Gorman T. J. Sejnowski Learned classification of sonar targets using a massively parallel network IEEE Trans. Acoust., Speech, Signal Process. 36 7 1135 1140 July 1988
86. A. Maccato R. J. P. de Figueiredo A neural network based framework for classification of oceanic acoustic signals Proc. OCEANS-89 1118 1123 Proc. OCEANS-89 Seattle WA 1989
87. R. W. Ehrich J. P. Foith Representation of random waveforms by relational trees IEEE Trans. Comput. C-25 725 736 July 1976
88. S. Shaw R. J. P. de Figueiredo Structural processing of waveforms as trees IEEE Trans. Acoust., Speech, Signal Process. 38 2 328 338 Feb. 1990
89. D. B. Malkoff L. Cohen A neural network approach to the detection problem using joint time-frequency distributions Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 2739 2742 Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Albuquerque NM 1990-Apr.-3-6
90. S. Barbarossa A. Zanalda A combined Wigner-Ville and Hough transform for cross-terms suppression and optimal detection and parameter estimation Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing V-173 V-176 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
91. B. Boashash Advances in Spectrum Analysis and Array Processing 1 1991 Prentice-Hall NJ, Englewood Cliffs Time-frequency signal analysis
92. B. Boashash G. Frazer Time-varying higher-order spectra, generalised Wigner-Ville distribution and the analysis of underwater acoustic data Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing V-193 V-196 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
93. B. Boashash P. O'Shea Application of the Wigner-Ville distribution to the identification of machine noise Proc. SPIE 975 209 220 Proc. SPIE 1988
94. B. Boashash P. O'Shea A methodology for detection and classification of some underwater acoustic signals using time-frequency analysis techniques IEEE Trans. Acoust., Speech, Signal Process. 38 11 1829 1841 Nov. 1990
95. L. Cohen Time-frequency distributions—A review Proc. IEEE 77 7 941 981 July 1989
96. M. R. Dellomo G. M. Jacyna Wigner transforms, Gabor coefficients, and Weyl-Heisenberg wavelets J. Acoust. Soc. Amer. 89 5 2355 2361 May 1991
97. P. Flandrin On detection-estimation procedures in the time-frequency plane Proc. 1986 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 2331 2334 Proc. 1986 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Tokyo Japan 1986-Apr.-7-11
98. P. Flandrin Time-frequency receivers for locally optimum detection Proc. 1988 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 2725 2728 Proc. 1988 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing New York NY 1988-Apr.-11-14
99. P. Flandrin A time-frequency formulation of optimum detection IEEE Trans. Acoust., Speech, Signal Process. 36 9 1377 1384 Sept. 1988
100. B. Friedlander B. Porat Detection of transient signals by the Gabor representation IEEE Trans. Acoust., Speech, Signal Process. 37 2 169 179 Feb. 1989
101. S. Kay G. F. Boudreaux-Bartels On the optimality of the Wigner distribution for detection Proc. 1985 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1017 1020 Proc. 1985 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Tampa FL 1985-Mar.-26-29
102. B. Porat B. Friedlander Performance analysis of a class of transient detection algorithms Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 11-473 11-476 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
103. P. Rao F. J. Taylor Detection and localization of narrowband transient signals using the Wigner distribution J. Acoust. Soc. Amer. 90 3 1423 1434 Sept. 1991
104. B. V. K. V. Kumar C. W. Carroll Performance of Wigner distribution function based detection methods Opt. Eng. 23 6 732 737 Nov./Dec. 1984
105. M. Bassevile A. Benveniste Multiscale statistical signal processing Proc. 1989 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 2065 2068 Proc. 1989 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Glasgow Scotland 1989-May-23-26
106. K. C. Chou S. Golden A. S. Willsky Modeling and estimation of multiscale stochastic processes Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1709 1712 Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Toronto 1991-May-14-17
107. I. Daubechies Wavelets, Time-Frequency and Phase Space 1989 Springer-Verlag Berlin Orthonormal bases of wavelets with finite support-connection with discrete filters
108. I. Daubechies Orthonormal bases of compactly supported wavelets Comm. Pure Appl. Math. 41 7 909 996 1988
109. I. Daubechies The wavelet transform, time-frequency localization and signal analysis IEEE Trans. Informat. Theory 36 5 961 1005 Sept. 1990
110. P. Flandrin Time-frequency and time-scale Proc. IEEE 4th Annual ASSP Work, on Spectral Estimation and Modeling Proc. IEEE 4th Annual ASSP Work, on Spectral Estimation and Modeling Minneapolis MN 1988
111. M. Frisch H. Messer Detection of a transient signal of unknown scaling and arrival time using the discrete wavelet transform Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1313 1316 Proc. 1991 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Toronto 1991-May-14-17
112. D. Garreau Multiscale inverse filtering Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 2495 2498 Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Albuquerque NM 1990-Apr.-3-6
113. P. A. Goupillaud P. A. Grossman J. Morlet Cycleoctave and related transforms in seismic signal analysis Geoexploration 23 85 102 1984/85
114. A. Grossman J. Morlet Decomposition of Hardy functions into square integrable wavelets of constant shape SIAM J. Math. Anal. 15 4 723 736 July 1984
115. C. Heil D. Walnut Continuous and discrete wavelet transforms SIAM Rev. 31 628 666 1989
116. I. Jouny Target description using wavelet transform Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing IV-289 IV-292 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
117. R. J. Kronland-Martinet R. J. Morlet A. Grossman Analysis of sound patterns through wavelet transforms Int. J. Pattern Recogn. Artificial Intell. 1 273 302 1987
118. S. G. Mallat A theory of multiresolution signal decomposition: the wavelet representation IEEE Trans. Pattern Anal. Machine Intell. 11 7 674 693 July 1989
119. A. P. Petropulu Detection of transients using discrete wavelet transform Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing II-477 II-480 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
120. O. Rioul M. Vetterli Wavelets and signal processing IEEE Signal Process. Mag. 8 14 38 Oct. 1991
121. F. B. Tuteur Wavelet transformations in signal detection Proc. 1988 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 1435 1438 Proc. 1988 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing New York NY 1988-Apr.-11-14
122. Wavelets, Time-Frequency and Phase Space 1989 Springer-Verlag Berlin
123. IEEE Trans. Informat. Theory 38 2 Mar. 1992
124. X. Yu I. S. Reed W. Kraske A. D. Stocker A robust adaptive multi-spectral object detection by using wavelet transform Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing V-141 V-144 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
125. L. E. Baum T. Petrie Statistical inference for probabilistic functions of finite state Markov chains Ann. Math. Statist. 37 1554 1563 1966
126. L. E. Baum T. Petrie G. Soules N. Weiss A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains Ann. Math. Statist. 41 1 164 171 1970
127. L. E. Baum An inequality and associated maximization technique in statistical estimation for probabilistic functions of a Markov process Inequalities 3 1 8 1972
128. D. A. Coast R. M. Stern G. G. Cano S. A. Briller An approach to cardiac arrhythmia analysis using hidden Markov models IEEE Trans. Biomed. Eng. 37 9 826 836 Sept. 1990
129. N. Merhav Y. Ephraim A Bayesian classification approach with application to speech recognition IEEE Trans. Signal Process. 39 10 2157 2166 Oct. 1991
130. L. R. Rabiner B. H. Juang An introduction to hidden Markov models IEEE ASSP Mag. 3 1 4 16 Jan. 1986
131. L. R. Rabiner A tutorial on hidden Markov models and selected applications in speech recognition Proc. IEEE 77 2 257 286 Feb. 1989
132. M. K. Shields C. W. Therrien A hidden Markov model approach to the classification of acoustic transients Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 2731 2734 Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Albuquerque NM 1990-Apr.-3-6
133. J. P. Woodard Modeling and classification of natural sounds by product code hidden Markov models IEEE Trans. Signal Process. 40 7 1833 1835 July 1992
134. P. A. Devijver J. Kittler Pattern Recognition: A Statistical Approach 1982 Prentice-Hall Int. NJ, Englewood Cliffs
135. K. Fukunaga Introduction to Statistical Pattern Recognition 2nd 1990 Academic Press MA, Boston
136. R. S. Bennett The intrinsic dimensionality of signal collection IEEE Trans. Informat. Theory IT-15 517 525 Sept. 1969
137. G. V. Trunk Statistical estimation of the intrinsic dimensionality of data collections Informat. Contr. 12 508 525 1968
138. G. V. Trunk Parameter identification using intrinsic dimensionality IEEE Trans. Informat. Theory IT-18 126 133 Jan. 1972
139. T. M. Cover P. E. Hart Nearest neighbor pattern classification IEEE Trans. Informal. Theory IT-13 21 27 Jan. 1967
140. T. J. Wagner Convergence of the nearest neighbor rule IEEE Trans. Informat. Theory IT-17 566 571 Sept. 1971
141. C. J. Stone Consistent nonparametric regression Ann. Statist. 5 595 645 June 1977
142. L. Devroye On the inequality of Cover and Hart in nearest neighbor discrimination IEEE Trans. Patt. Anal. Machine Intell. PAMI-3 75 78 Jan. 1981
143. T. M. Cover Methodologies of Pattern Recognition 111 132 1969 Academic Press New York Learning in pattern recognition
144. T. M. Cover Rates of convergence of nearest neighbor decision procedures Proc. 1st Annu. Hawaii Conf. on Systems Theory 413 415 Proc. 1st Annu. Hawaii Conf. on Systems Theory 1968-Jan.
145. T. M. Cover Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition IEEE Trans. Electron. Comput. EC-14 326 334 June 1965
146. N. J. Nilsson Learning Machines: Foundations of Trainable Pattern-Classifying Systems 1965 McGraw-Hill New York
147. B. Widrow M. E. Hoff Adaptive switching circuits 1960 IRE WESCON Conv. Rec. 96 104 1960 IRE WESCON Conv. Rec. 1960-Aug.
148. S. Kirkpathrick C. Gelatt M. Vecchi Optimization by simulated annealing Science 220 671 680 1983
149. B. Hajek Cooling schedules for optimal annealing Math. Operations Res. 1985
150. C. F. J. Wu On the convergence properties of the EM algorithm Ann. Statist. 11 1 95 103 1983
151. P. J. Huber Projection pursuit Ann. Statist. 13 2 435 475 June 1985
152. S. Watanabe Karhunen-Loeve expansion and factor analysis Trans. 4th Prague Conf. on Information Theory Trans. 4th Prague Conf. on Information Theory 1965
153. J. T. Tou R. P. Heydorn Computer and Information Sciences II 57 89 1967 Academic Press New York Some approaches to optimum feature extraction
154. M. Anderberg Cluster Analysis for Applications 1973 Academic Press New York
155. A. K. Jain R. C. Dubes Algorithms for Clustering Data 1988 Prentice-Hall NJ, Englewood Cliffs
156. J. Rissanen Stochastic Complexity in Statistical Inquiry 1989 World Scientific Publishing Co.
157. J. Rissanen E. S. Ristad Unsupervised classification with stochastic complexity Proc. US/Japan Conf. on Frontiers of Statistical Modeling Proc. US/Japan Conf. on Frontiers of Statistical Modeling 1993
158. R. P. Lippmann An introduction to computing with neural nets IEEE ASSP Mag. 4 2 4 22 Apr. 1987
159. Neurocomputing: Foundations of Research 1988 MIT Press MA, Cambridge
160. D. R. Hush B. G. Home Progress in supervised neural networks IEEE Signal Process. Mag. 10 1 8 39 Jan. 1993
161. B. Widrow R. G. Winter R. A. Baxter Layered neural networks for pattern recognition IEEE Trans. Acoust., Speech, Signal Process. 36 7 1109 1117 July 1988
162. R. P. Lippmann A critical overview of neural network pattern classifiers Proc. IEEE Workshop on Neural Networks for Signal Processing 266 275 Proc. IEEE Workshop on Neural Networks for Signal Processing Princeton NJ 1991
163. J. J. Hopfield Neural networks and physical systems with emergent collective computational abilities Proc. Nat. Acad. Sci. USA 79 2554 2558 Apr. 1982
164. J. J. Hopfield Neurons with graded response have collective computational properties like those of two-state neurons Proc. Natl. Acad. Sci. USA 81 3088 3092 May 1984
165. J. J. Hopfield D. W. Tank Computing with neural circuits: a model Science 233 625 633 Aug. 1986
166. D. R. Selviah J. E. Midwinter A. W. Rivers K. W. Lung Correlating matched-filter model for analysis and optimisation of neural networks Proc. Inst. Elec. Eng. 136 3 143 148 June 1989
167. D. J. Wallace Memory and learning in a class of neural models Proc. Workshop on Lattice Gauge Theory, 1985 Proc. Workshop on Lattice Gauge Theory, 1985 1986
168. G. A. Carpenter S. Grossberg Brain Structure, Learning, and Memory AAAS Symp. Ser. 1986 Neural dynamics of category learning and recognition: attention, memory consolidation, and amnesia
169. J. A. Hartigan Clustering Algorithms 1975 Wiley New York
170. R. Rosenblatt Principles of Neurodynamics 1959 Spartan New York
171. M. Minsky S. Papert Perceptrons 1988 MIT Press MA, Cambridge
172. T. Kohonen Self-Organization and Associative Memory 1984 Springer-Verlag Germany, Berlin
173. K. Hornik M. Stinchcombe H. White Multilayer feedforward networks are universal approximators J. Neural Networks 2 359 366 1989
174. G. Mirchandani W. Cao On hidden nodes for neural nets IEEE Trans. Circuits Syst. 36 5 661 664 May 1989
175. S. C. Huang Y. F. Huang Bounds on the number of hidden neurons in multilayer perceptrons IEEE Trans. Neural Networks 2 1 47 55 Jan. 1991
176. A. Maccato R. J. P. de Figueiredo Structured neural network topologies with application to acoustic transients Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing 877 880 Proc. 1990 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing Albuquerque NM 1990-Apr.-3-6
177. D. E. Rumelhart G. E. Hinton R. J. Williams Parallel Distributed Processing: Explorations in the Microstructures of Cognition 1 318 362 1986 MIT Press MA, Cambridge Learning internal representations by error propagation
178. D. E. Rumelhart G. E. Hinton R. J. Williams Learning representations by back-propagating errors Nature 323 533 536 1986
179. P. Werbos Beyond regression: New tools for prediction and analysis in the behavioral sciences 1974 Harvard University MA, Cambridge
180. M. L. Brady R. Raghavan J. Slawny Back propagation fails to separate where perceptrons succeed IEEE Trans. Circuits Syst. 36 5 665 674 May 1989
181. D. H. Ackley G. E. Hinton T. J. Sejnowski A learning algorithm for Boltzmann machines Cognitive Sci. 9 147 169 1985
182. K. Pal D. K. D. Majumder Fuzzy Mathematical Approach to Pattern Recognition 1986 Wiley New York
183. B. Kosko Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence 1992 Prentice-Hall NJ, Englewood Cliffs
184. J. C. Bezdek Computing with uncertainty IEEE Commun. Mag. 24 36 Sept. 1992
185. G. A. Carpenter S. Grossberg A self-organizing neural network for supervised learning, recognition, and prediction IEEE Commun. Mag. 38 19 Sept. 1992
186. L.-M. Fu Adaptive signal detection in noisy environments J. Neural Network Comput. 1 4 42 50 1990
187. S. N. Batalama A. G. Koyiantis P. Papantoni-Kazakos D. Kazakos Feedforward neural structures in binary hypothesis testing IEEE Trans. Commun. 41 7 1047 1062 July 1993
188. H. Gish A minimum classification error, maximum likelihood, neural network Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing II-289 II-292 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
189. Z. Michalopoulou L. Nolte D. Alexandrou ROC performance evaluation of multilayer perceptrons in the detection of one of M orthogonal signals Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing II-309 II-312 Proc. 1992 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing San Francisco CA 1992-Mar.-23-26
190. S. Miyake F. Kanaya A neural network approach to a Bayesian statistical decision problem IEEE Trans. Neural Networks 2 5 538 540 Sept. 1991
191. J. W. Watterson An optimum multilayer perceptron neural receiver for signal detection IEEE Trans. Neural Networks 1 4 298 300 Dec. 1990
192. C.-Y. Yao A. N. Wilson A neural-network approach to statistical decision making Proc. IEEE Int. Symp. on Circuits and Systems 727 730 Proc. IEEE Int. Symp. on Circuits and Systems New Orleans LA 1990-May-1-3
193. D. B. Malkoff E. J. Smythe An integrated neural network—time frequency method for detection and classification Proc. SPIE 1297 329 338 Proc. SPIE Orlando FL 1990-Apr.-18-20
194. S. C. Ahalt F. D. Garber I. Jouny A. K. Krishnamurthy Advances in Neural Information Processing Systems I 281 288 1989 Morgan Kaufmann CA, San Mateo Performance of synthetic neural network classification of noisy radar signals
195. S. Haykin C. Deng Classification of radar clutter using neural networks IEEE Trans. Neural Networks 2 6 589 600 Nov. 1991
196. H. K. Kwan C. K. Lee Pulse radar detection using a multilayer neural network Proc. 1989 IEEE INNS Int. Joint Conf. on Neural Networks II-75 II-80 Proc. 1989 IEEE INNS Int. Joint Conf. on Neural Networks Washington, DC 1989-June-18-22
197. M. W. Roth Neural networks for extraction of weak targets in high clutter environments Proc. 1989 IEEE INNS Int. Joint Conf. on Neural Networks I-275 I-282 Proc. 1989 IEEE INNS Int. Joint Conf. on Neural Networks Washington, DC 1989-June-18-22
198. A. Khotanzad J. H. Lu M. D. Srinath Target detection using a neural network based passive sonar system Proc. 1989 IEEE INNS Int. Joint Conf. on Neural Networks I-335 I-340 Proc. 1989 IEEE INNS Int. Joint Conf. on Neural Networks Washington, DC 1989-June-18-22
199. M. J. LeBlanc E. Manolakos Neural networks for sides-can sonar automatic target detection Proc. IEEE Workshop on Neural Networks for Signal Processing 208 216 Proc. IEEE Workshop on Neural Networks for Signal Processing Princeton NJ 1991
200. B. Aazhang B.-P. Paris G. Orsak Neural networks for multiuser detection in code-division multiple-access communications IEEE Trans. Commun. 40 7 1212 1222 July 1992
201. B.-P. Paris G. Orsak M. Varanasi B. Aazhang Advances in Neural Information Processing Systems I 272 280 1989 Morgan Kaufmann CA, San Mateo Neural net receivers in multiple-access communications
202. U. Mitra H. V. Poor Adaptive receiver algorithms for near-far resistant CDMA Proc. 3rd Int. Symp. on Personal, Indoor and Mobile Radio Communications 639 644 Proc. 3rd Int. Symp. on Personal, Indoor and Mobile Radio Communications Boston MA 1992-Oct.-19-21
203. U. Mitra H. V. Poor Neural network techniques for multiuser demodulation Proc. 1993 IEEE Neural Networks Conf. Proc. 1993 IEEE Neural Networks Conf. San Francisco CA 1993
204. U. Mitra H. V. Poor Neural networks in adaptive multiuser detection Proc. 4th Int. Conf. on Advances in Communications and Control Proc. 4th Int. Conf. on Advances in Communications and Control Rhodes Greece 1993-June-14-18
205. S. S. Rao S. Sethuraman A neural network pre-processor for multi-tone detection and estimation Proc. IEEE Workshop on Neural Networks for Signal Processing 580 588 Proc. IEEE Workshop on Neural Networks for Signal Processing Princeton NJ 1991