Detection and classification of underwater transients with data driven methods based on time-frequency distributions and non-parametric classifiers

Oceans Conference Record (IEEE)

Volumn 1, Issue , 2002, Pages 12-16

  Oliveira, Paulo M ^a   Lobo, Victor ^a   Barroso, Victor ^b   Moura Pires, Fernando ^c  

^a Academia Naval Almada   (Portugal)

^b INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^c UNIVERSITY OF ÉVORA   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC RECEIVERS; COSTS; DATA REDUCTION; SIGNAL DETECTION; SIGNAL INTERFERENCE;

NON-PARAMETRIC CLASSIFIERS;

UNDERWATER ACOUSTICS;

EID: 0038309202     PISSN: 01977385     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. P. M. Oliveira and V. Barroso "Data Driven Underwater Transient Detection Based on Time-Frequency Distributions", Proc. of MTS/IEEE Oceans 2000, August 2000.
2. D. L. Jones and A. M. Sayeed, "Blind Quadratic and Time-Frequency Based Detectors from Training Data," Proceedings of the 1995 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP 95, Detroit, MI, pp. 1033-1036.
3. L. Cohen, Time Frequency Analysis, Englewood-Cliffs, NJ: Prentice-Hall, 1995.
4. P. Flandrin, "A time-frequency formulation of optimum detection," IEEE Trans. on Sig. Proc., vol. 36, pp. 1377-1384, Sept. 1988.
5. C. S. Cunningham and W. J. Williams, "Fast implementations of generalized discrete time-frequency distributions", IEEE Trans. on Sig. Proc., vol. 42, pp. 1496-1508, June 1994.
6. C. M. Bishop, Neural Networks for Pattern Recognition, Clarendon Press - Oxford, 1995.
7. Duda, R. O., P. E. Hart, et al.. Pattern Classification, Wiley-Interscience, 2001.
8. Fix, E. and J. L. Hodges. Discriminatory Analysis: Nonparametric Discimination: Consistency Properties. Randolph Field, USAF School of Aviation Medicine - Project 21-49-004: 261-272, 1951.
9. Cover, T. M. and P. E. Hart. "Nearest Neighbor Pattern Classification." IEEE Transactions on Information Theory 13(1): pp. 21-27, 1967.
10. Dasarathy, B. V. Nearest Neighbor Pattern Classification techniques, IEEE Computer Society Press, 1991.
11. Kuncheva, L. I. and J. C. Bezdek. "Nearest Prototype Classification: Clustering, Genetic Algorithms, or Random Search?" IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 28(1): pp. 160-164, 1998.
12. Aha, D.. "Lazy Learning - Editorial Review." Artificial Intelligence Review 11, 1997.
13. Bax, E. "Validation of Nearest Neighbor Classifiers." IEEE Transactions on Information Theory 46(7): pp. 2746-2752, 2000.
14. Nock, R. and M. Sebban. "An improved bound on the finite-sample risk of the nearest neighbor rule." Pattern Recognition Letters 22(3-4): pp. 407-412, 2001.
15. Lobo, V., R. Swiniarski, et al. Pruning a classifier based on a Self-Organizing Map using Boolean function formalization. WCCI - World Conference on Computational Intelligence, Anchorage, Alaska, USA, IEEE Press, 1998.
16. Wilson, D. L.. "Asymptotic Properties of Nearest Neighbor Rules Using Edited Data." IEEE Transactions on Systems, Man, and Cybernetics 2(3): pp. 408-421, 1972.
17. Breiman, L., J. H. Friedman, et al., Classification and Regression Trees, Chapman & Hall, 1984.