Nonlinear spatial-temporal prediction based on optimal fusion

IEEE Transactions on Neural Networks

Volumn 17, Issue 4, 2006, Pages 975-988

  Xia, Youshen ^a   Leung, Henry ^a  

^a UNIVERSITY OF CALGARY   (Canada)

Author keywords

Chaos; Data fusion; Prediction; Radar; Spatial temporal signal processing; Support vector machine (SVM)

Indexed keywords

COMPUTER SIMULATION; FORECASTING; SIGNAL PROCESSING; STATISTICS;

DATA FUSION; NONLINEAR SPATIAL-TEMPORAL PREDICTION; OPTIMAL FUSION; SUPPORT VECTOR MACHINE;

LEARNING SYSTEMS;

ALGORITHM; ARTICLE; FORECASTING; NONLINEAR SYSTEM; THEORETICAL MODEL; TIME;

ALGORITHMS; FORECASTING; MODELS, THEORETICAL; NONLINEAR DYNAMICS; TIME FACTORS;

EID: 33746891187     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2006.875985     Document Type: Article

References (40)

1. A. M. Tekalp, Digital Video Processing. Englewood Cliffs, NJ: Prentice-Hall, 1995.
2. P. V. Rooyen, M. Lotter, and D. V. Wyk, Space-Time Processing for CDMA Mobile Communications. Boston, MA: Kluwer Academic, 2000.
3. N. Cressie and J. J. Majure, "Spatial-temporal statistical modeling of live-stock waste in streams," J. Agricult., Biol, Environ. Statist., vol. 2, pp. 24-47, 1997.
4. H. Leung and T. Lo, "A spatial temporal dynamical model for multi-path scattering from the sea," IEEE Trans. Geosci. Remote Sens., vol. 33, no. 2, pp. 441-448, Feb. 1995.
5. J. Lee and V. J. Mathews, "A fast recursive least squares adaptive second-order Volterra filter and its performance analysis," IEEE Trans. Signal Process., vol. 41, no. 3, pp. 1087-1097, Mar. 1993.
6. J. T. Lo, "Synthetic approach to optimal filtering," IEEE Trans. Neural Netw., vol. 5, no. 5, pp. 803-811, Sep. 1994.
7. H. Leung and S. Haykin, "Detection and estimation using an adaptive rational function filter," IEEE Trans. Signal Process., vol. 42, no. 11, pp. 3366-3376, Nov. 1994.
8. H. Leung, "Nonlinear clutter cancellation and detection using a memory-based predictor," IEEE Trans. Aerosp. Electron. Syst., vol. 32, no. 4, pp. 1249-1256, Oct. 1996.
9. U. Parlitz and C. Merkwirth, "Predicting low-dimensional spatiotemporal dynamics using discrete wavelet transforms," Phys. Rev. E, vol. 51, no. 4, p. R2710, 1995.
10. K. Kaneko, Theory and Application of Coupled Map Lattices. New York: Wiley, 1993.
11. U. Parlitz and C. Merkwirth, "Prediction of spatial-temporal time series based on reconstructed local states," Phys. Rev. Lett., vol. 84, pp. 1890-1893, 2000.
12. H. Leung, G. Hennessey, and A. Drosopoulos, "Signal detection using the radial basis function coupled map lattice," IEEE Trans. Neural Netw., vol. 11, no. 5, pp. 1133-1151, Sep. 2000.
13. A. Kumar and S. K. Mullick, "Nonlinear dynamical analysis of speech," J. Acoust. Soc. Amer., vol. 100, pp. 615-629, Jul. 1996.
14. E. Jakeman and R. J. A. Tough, "Non-Gaussian models for the statistics of scattered waves," Adv. Phys., vol. 37, no. 5, pp. 471-529, 1988.
15. D. Donoho, "On minimum entropy deconvolution," in Applied Time Series Analysis II. New York: Academic, 1981, pp. 565-608.
16. E. Walach and B. Widrow, "The least mean four (LMF) adaptive algorithmand its family," IEEE Trans. Inf. Theory, vol. IT-30, no. 2, pp. 275-283, Mar. 1984.
17. M. C. Hong, T. Stathaki, and A. K. Katsaggelos, "Iterative regularized mixed norm multichannel image restoration," J. Electron. Imag., vol. 14, no. 1, Mar. 2005, Art. 013004.
18. T. W. S. Chow and H. Z. Tan, "Third-order cumulant RLS algorithm for nonminimum ARMA system identification," Signal Process., vol. 61, pp. 23-38, 1997.
19. C. T. Leung and T. W. S. Chow, "Adaptive regularization parameter selection method for enhancing generalization capability of neural networks," Artif. Intell., vol. 107, pp. 347-356, 1999.
20. C. T. Leung and T. W. S. Chow, "Least third order cumulant method with adaptive parameter regularization parameter selection method for neural networks," Artif. Intell., vol. 127, pp. 169-197, 2001.
21. A. J. Bell and T. J. Sejnowski, "An information-maximisation approach to blind separation and blind deconvolution," Neural Comput., vol. 7, no. 6, pp. 1004-1034, 1995.
22. Y. S. Xia, H. Leung, and H. Chan, "A prediction fusion method for reconstructing spatial temporal dynamics," IEEE Trans. Circuits Syst. II, Express Briefs, vol. 53, no. 1, pp. 62-66, Jan. 2006.
23. P. K. Varshney, "Scanning the issue," Proc. IEEE, vol. 85, no. 1, pp. 3-5, Jan. 1997.
24. H. F. Durrant-Whyte, Integration, Coordination and Control of Multi-Sensor Robot Systems. Norwell, MA: Kluwer Academic, 1988.
25. D. Avitzour, "A maximum likehood approach to data association," IEEE Trans. Aerosp. Electron. Syst., vol. 28, no. 2, pp. 560-566, Apr. 1992.
26. Y. Xia, H. Leung, and E. BosséBosse, "Neural data fusion algorithms based on a linearly constrained least square method," IEEE Trans. Signal Process., vol. 53, no. 2, pt. I, pp. 672-685, Feb. 2005.
27. V. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
28. C. Cortes and V. Vapnik, "Support-vector networks," Machine Learn., vol. 20, pp. 273-297, 1995.
29. V. Vapnik, S. Golowich, and A. J. Smola, "Support vector method for function approximation, regression estimation and signal processing," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 1996, vol. 9, pp. 281-287.
30. S. Mukherjee, E. Osuna, and F. Girosi, "Nonlinear prediction of chaotic time series using support vector machines," in Proc. IEEE NNSP'97, Amelia Island, FL, 1997, pp. 24-26.
31. Z. Chen and S. Haykin, "On different facets of regularization theory," Neural Comput., vol. 14, pp. 2791-2846, 2002.
32. A. J. Smola and B. Scholkopf, "On a Kernel-based method for pattern recognition, regression, approximation, and operator inversion," Algorithmica, vol. 22, pp. 211-231, 1998.
33. W. X. Zheng, "Autoregressive parameter estimation from noise data," IEEE Trans. Circuits Syst., vol. 47, no. 1, pt. II, pp. 71-75, Jan. 2000.
34. S. Haykin and S. Puthusserypady, "Chaotic dynamics of sea clutter," Chaos, vol. 7, pp. 777-802, 1997.
35. A. Drosopoulos, Description of the OHGR database Defence Research Establishment, Ottawa, ON, Canada, Dec. 1994, Tech. Note 94-14.
36. J. A. K. Suykens and J. Vandewalle, "Least squares support vector machine classifiers," Neural Process. Lett., vol. 9, pp. 293-300, 1999.
37. H. Leung, T. Lo, and S. C. Wang, "Prediction of noisy chaotic time series using an optimal radial basis function neural network," IEEE Trans. Neural Netw., vol. 12, no. 5, pp. 1163-1172, Sep. 2001.
38. X. Tang, X. B. Gao, and J. Z. Liu, "A spatial-temporal approach for video caption detection and recognition," IEEE Trans. Neural Netw., vol. 13, no. 4, pp. 961-971, Jul. 2002.
39. J. Q. Wang, M. R. Azimi-Sadjadi, and D. Reinke, "A temporally adaptive classifier for multispectral imagery," IEEE Trans. Neural Netw., vol. 15, no. 1, pp. 159-165, Jan. 2004.
40. N. Xie and H. Leung, "Blind equalization using a predictive radial basis function neural network," IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 709-720, May 2005.