A Hybrid Neural Network/Genetic Algorithm Approach to Optimizing Feature Extraction for Signal Classification

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 34, Issue 1, 2004, Pages 695-702

  Rovithakis, G A ^a   Maniadakis, M ^b   Zervakis, M ^c  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^b INSTITUTE OF COMPUTER SCIENCE   (Greece)

^c TECHNICAL UNIVERSITY OF CRETE   (Greece)

Author keywords

Classification; Feature extraction; Genetic algorithms; Neural networks

Indexed keywords

ADAPTIVE FILTERING; BLOOD; CAMERAS; CELLS; CHARGE COUPLED DEVICES; CHROMOSOMES; COMPUTER SIMULATION; ERROR ANALYSIS; FEATURE EXTRACTION; GENETIC ALGORITHMS; IDENTIFICATION (CONTROL SYSTEMS); IMAGE ANALYSIS; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION; TISSUE; TOPOLOGY;

SIGNAL CLASSIFICATION;

NEURAL NETWORKS;

EID: 0742307283     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2003.811293     Document Type: Article

References (27)

1. N. E. Cotter, "The stone-weierstrass theorem and its applications to neural networks," IEEE Trans. Neural Networks, vol. 1, pp. 290-295, 1990.
2. G. Cybenko, "Approximations by superpositions of a sigmoidal function," Mathematics of Control, Signals, and Systems, vol. 2, pp. 303-314, 1989.
3. M. M. Gupta and D. H. Rao, Eds., Neuro-Control Systems: Theory and Applications. New York: IEEE Press, 1994.
4. Handbook of Intelligent Control: Neural, Fuzzy and Adaptive Approaches, D. A. White and D. A. Sofge, Eds., Van Nostrand and Reinhold, New York, 1993.
5. T. Poggio and F. Girosi, "Regularization algorithms for learning that are equivalent to multilayer networks," Science, vol. 247, pp. 978-982, 1990.
6. S. H. Lane, D. A. Handelman, and J. J. Gelfand, "Theory and development of higher-order CMAC neural networks," IEEE Contr. Syst. Mag., pp. 23-30, 1992.
7. G. A. Rovithakis, M. Maniadakis, M. Zervakis, G. Filippidis, G. Zacharakis, A. N. Katsamouris, and T. G. Papazoglou, "Artificial neural networks for discriminating pathologic from normal peripheral vascular tissue," IEEE Trans. Biomed. Eng., vol. 48, no. 10, pp. 1088-1097, 2001.
8. G. A. Rovithakis, "Tracking control of multi input affine nonlinear dynamical systems with unknown nonlinearities using dynamical neural networks," IEEE Trans. Syst., Man, Cybern. B, vol. 29, pp. 179-189, 1999.
9. _, "Robust neural adaptive stabilization of unknown systems with measurement noise," IEEE Trans. Syst., Man, Cybern. B, vol. 29, pp. 453-458, 1999.
10. G. A. Rovithakis and M. A. Christodoulou, Adaptive Control with Recurrent High-Order Neural Networks. London, U.K.: Springer-Verlag, 2000.
11. G. A. Rovithakis, "Performance of a neural adaptive tracking controller for multi-input nonlinear dynamical systemsin the presence of additive and multiplicative external disturbances," IEEE Trans. Syst. Man Cybern. A, vol. 30, pp. 720-730, 2000.
12. J. Glosh and Y. Shin, "Efficient higher-order neural networks for classification and function approximation," Int. J. Neural Syst., vol. 3, no. 4, pp. 323-350, 1992.
13. J. H. Holland, "Genetic algorithms," Sci. Amer., pp. 66-72, July 1992.
14. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. New York: Willey, 2001.
15. K. DeJong, "Learning with genetic algorithms: An overview," Mach. Learn., vol. 3, pp. 121-138, 1988.
16. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
17. D. B. Fogel, Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. New York: IEEE Press, 1995.
18. X. Yao, "A review of evolutionary artificial neural networks," Int. J. Intell. Syst., vol. 4, pp. 203-222, 1993.
19. B. A. Whitehead and T. D. Choate, "Evolving space-filling curves to distribute radial basis functions over an input space," IEEE Trans. Neural Networks, vol. 5, no. 1, pp. 15-23, 1994.
20. J. R. McDonnell and D. Waagen, "Evolving recurrent perceptrons for time-series modeling," IEEE Trans. Neural Networks, vol. 5, no. 1, pp. 24-38, 1994.
21. V. Maniezzo, "Genetic evolution of the topology and weight distribution of neural networks," IEEE Trans. Neural Networks, vol. 5, no. 1, pp. 39-53, 1994.
22. P. J. Angeline, G. M. Saunders, and J. B. Pollack, "An evolutionary algorithm that constructs recurrent neural networks," IEEE Trans. Neural Networks, vol. 5, no. 1, pp. 54-65, 1994.
23. H. Ishigami, T. Fukuda, T. Shibata, and F. Arai, "Structure optimization of fuzzy neural networks by genetic algorithm," Fuzzy Sets Syst., vol. 71, pp. 257-264, 1995.
24. D. Floreano and F. Mondada, "Evolution of homing navigation in a real mobile robot," IEEE Trans. Syst., Man, Cybern. B, vol. 26, no. 3, pp. 396-407, 1996.
25. A. Freitas, "A survey of evolutionary algorithms for data mining," in Evolutionary Computation, A. Glosh and S. Tsutsui, Eds. Berlin, Germany: Springer-Verlag.
26. C. Balas, "A novel optical imaging method for the early detection, quantitative grading and mapping of cancerous and precancerous lesions of cervix," IEEE Trans. Biomed. Eng., vol. 48, no. 1, pp. 96-104, 2001.
27. F. P. Preparata and M. I. Shamos, Computational Geometry: An Introduction. New York: Springer-Verlag, 1985.