Signal classification through multifractal analysis and complex domain neural networks

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 36, Issue 2, 2006, Pages 196-203

  Kinsner, Witold ^a,b   Cheung, Vincent ^a,c   Cannons, Kevin ^a,c   Pear, Joseph ^a   Martin, Toby ^a  

^a UNIVERSITY OF MANITOBA   (Canada)

^b TRLABS   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

Author keywords

Classification; Complex domain neural network (CNN); Multifractal analysis; Probabilistic neural network (PNN)

Indexed keywords

FEATURE EXTRACTION; FRACTALS; NONLINEAR SYSTEMS; PROBABILITY; RANDOM PROCESSES; SIGNAL PROCESSING;

COMPLEX DOMAIN NEURAL NETWORK; MULTIFRACTAL ANALYSIS; PROBABILISTIC NEURAL NETWORK;

NEURAL NETWORKS;

EID: 33645984827     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCC.2006.871148     Document Type: Article

References (13)

1. W. Kinsner, "Batch and real-time computation of a fractal dimension based on variance of a time series," Univ. Manitoba, Winnipeg, MB, Canada, Tech. Rep. DEL94-6, Jun. 1994.
2. V. Cheung and K. Cannons "Signal classification through multifractal analysis and neural networks," B.S. thesis, Dept. Elect. Comput. Eng., Univ. Manitoba, Winnipeg, MB, Canada, 2003.
3. B. Mandelbrot, The Fractal Geometry of Nature. San Francisco, CA: Freeman, 1982.
4. H. O. Peitgen, H. Jürgens, and D. Saupe, Chaos and Fractals: New Frontiers of Science. New York: Springer-Verlag, 1992.
5. T. Masters, Signal and Image Processing with Neural Networks: A C++ Sourcebook. New York: Wiley, 1994.
6. B. L. Kalman and S. C. Kwasny, "Why tanh? Choosing a sigmoidal function," in Proc. Int. Joint Conf. Neural Networks, vol. 4, Jun. 1992, pp. 578-581.
7. D. F. Specht, "Probabilistic neural networks for classification, mapping, or associative memory," in Proc. IEEE Int. Conf. Neural Networks, vol. 1, Jul. 1988, pp. 525-532.
8. E. Parzen, "On estimation of a probability density function and mode," Ann. Math. Statist., vol. 33, no. 3, pp. 1065-1076, 1962.
9. P. Wasserman, Advanced Methods in Neural Computing. New York: Van Nostrand, 1993.
10. T. Masters, Advanced Algorithms for Neural Networks: A C++ Sourcebook. New York: Wiley, 1995.
11. T. Kohonen, Self-Organization and Associative Memory. Berlin, Germany: Springer-Verlag, 1984, pp. 255-9.
12. R. Eberhart and R. Dobbins, Neural Network PC Tools: A Practical Guide. San Diego, CA: Academic, 1990.
13. W. Kinsner, "Fractal and chaos engineering," Dept. Elect. Comput. Eng., Univ. Manitoba, Winnipeg, MB, Canada, Lecture Notes, 2004, p. 941.