Supervised Fuzzy Mixture of Local Feature Models

References

[1] M. Xu and M. Golay, “Data-guided Model Combination by Decomposition and Aggregation,” Machine Learning, Vol. 63, No. 1, 2005, pp. 43-67.

[2] D. J. Bartholomew and M. Knott, “Latent Variable Models and Factor Analysis,” London: Ar-nold; New York: Oxford University Press, 1999.

[3] I. T. Jolliffe, “Principal Component Analysis,” New York: Springer-Verlag, 1986.

[4] A. Hyv?rinen, “Fast and Robust Fixed-Point Algorithms for Independent Component Analysis,” IEEE Transactions on Neural Networks, Vol. 10, No. 3, 1999, pp. 626-634.

[5] J. Karhunen and S. Malaroiu, “Locally Lin-ear Independent Component Analysis,” International Joint Conference on Neural Networks, 1999.

[6] T. A. Johansen and B. A. Foss, “Operating Regime Based Process Modeling and Identification,” Computers and Chemical Engineering, Vol. 21, 1997, pp. 159-176.
doi:10.1016/0098-1354(95)00260-X

[7] G. J. McLachlan and K. E. Basford, “Mixture Models: Inference and Application to Clustering,” New York: Marcel Dekker, 1988.

[8] R. Murray-Smith and T. A. Johansen, “Local Learning in Local Model Networks,” Proceedings of IEE International Confer-ence on Artificial Neural Networks, Cambridge, UK, 1995, pp. 40-46.
doi:10.1049/cp:19950526

[9] M. I. Jordan and R.A. Jacobs, “Hierarchical Mixtures of Experts and the EM Algorithm,” Neural Computation, Vol. 6, 1994, pp. 181-214.
doi:10.1162/neco.1994.6.2.181

[10] J. Fan, “Local Model-ling,” Encyclopidea of Statistical Science, 1995.

[11] W. S. Cleveland and S. J. Devlin, “Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting,” Journal of the American Statistical Association, Vol. 83, 1988, pp. 596-610.

[12] R. A. Jacobs, M. I. Jordan, S. J. Nowlan and G. E. Hinton, “Adaptive Mixtures of Local Experts,” Neural Computation, Vol. 3, 1991, pp. 79-87.
doi:10.1162/neco.1991.3.1.79

[13] U. S?derman, J. Top and J.-E. Str?mberg, “The Conceptual Side of Mode Switching,” Proceedings of IEE International Conference on Systems, Man, and Cybernetics, Le Touquet, France, 1993, pp. 245-250.

[14] S. Harrington, R. Zhang, P. H. Poole, F. Sciortino, and H. E. Stanley, “Liquid-Liquid Phase Transition: Evidence from Simulations,” Physical Review Letters, Vol. 78, No. 12, 1997, pp. 2409-2412.
doi:10.1103/PhysRevLett.78.2409

[15] K. Honda, H. Ichihashi, M. Ohue and K. Kitaguchi, “Extraction of Local Independent Components Using Fuzzy Clustering,” Proceedings of 6th In-ternational Conference on Soft Computing, 2000.

[16] L. J. Breiman, H. Friedman, R. A. Olshen, and C. J. Stone, “Classi-fication and Regression Trees,” Belmont CA: Wadsworth, 1984.

[17] J. C. Dunn, “A Fuzzy Relative of the ISODATA Process and Its Use in detecting Compact Well-Separated Clusters,” Journal of Cybernetics, Vol. 3, 1973, pp. 32-57.
doi:10.1080/01969727308546046

[18] J. C. Bezdek, “Pattern Recognition with Fuzzy Objective Function Algorithms,” Ple-num Press, New York, 1981.

[19] N. Kambhatla and T. Leen, “Dimension Reduction by Local Principal Component Analy-sis,” Neural Computation, Vol. 9, 1997, pp. 1493-1516.
doi:10.1162/neco.1997.9.7.1493

[20] J. Karhunen and S. Ma-laroiu, “Local Independent Component Analysis Using Clus-tering,” Proc. First Int. Workshop on Independent Component Analysis and Signal Separation, 1999, pp. 43-48.

[21] S. E. Geman, Bienenstock and R. Doursat, “Neural Networks and the Bias/Variance Dilemma,” Neural Computation, Vol. 4, 1992, pp. 1-58.

[22] H. Akaike, “Information Theory and an Exten-sion of the Maximum Likelihood Principle,” 2nd International Symposium on Information Theory (B. N. Petrov and F. Czáki, eds.), 1973, pp. 267-281.

[23] G. Schwarz, “Estimating the Dimension of a Model,” Annals of Statistics, Vol. 6, 1978, pp. 461-464.
doi:10.1214/aos/1176344136

[24] H. Hotelling, “Analysis of a Complex of Statistical Variables into Principal Components,” Journal of Educational Psychology, Vol. 24, 1933, 417-441.
doi:10.1037/h0071325

[25] A. Hyv?rinen and P. Pajunen, “Nonlinear Independent Component Analysis: Existence and Uniqueness Results,” Neural Network, Vol. 12, No. 2, 1999, pp. 209- 219.

[26] R. Murray-Smith and T. A. Johansen (Eds.), “Multiple Model Approaches to Nonlinear Modeling and Con-trol,” Taylor and Francis, London, UK, 1997.

[27] D. L. B. Jupp, “Approximation to Data by Splines with Free Knots,” SIAM Journal on Numerical Analysis, Vol. 15, No. 2, 1978, pp. 328-343.
doi:10.1137/0715022

[28] J. Friedman, “Multivariate Adap-tive Regression Splines (with discussion),” Annals of Statistics, Vol. 19, 1991, pp. 1-141. doi:10.1214/aos/1176347963

[29] H. G. Burchard, “Splines (With Optimal Knots) are Better,” Ap-plicable Analysis, Vol. 3, 1974, pp. 309-319.
doi:10.1080/00036817408839073

[30] J. M. Holland, “Adap-tation in Nature and Artificial Systems,” Ann Arbor, MI: The University of Michigan Press, 1975.

[31] J. Pittman, “Adap-tive Spline and Genetic Algorithms,” Journal of Computational and Graphical Statistics, Vol. 11, No. 3, pp. 1-24.

[32] David E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine Learning,” Kluwer Academic Publishers, Boston, MA, 1989.

[33] J. Hessner and R. M?nner, “In Proceedings of the First Workshop on Parallel Problem Solving from Nature,” Lecture Notes in Computer Science, Vol. 496, Springer- Verlag: Berlin, 1991, pp. 23-31.

[34] T. Takagi and M. Sugeno, “Fuzzy Identification of Sys- tems and Its Application to Mod-eling and Control,” IEEE Transactions on Systems, Man and Cybernetics, Vol. 15, 1985, pp. 116-132.

[35] J. H. Steidl and Y. Lee, “The SCEC Phase III Strong- Motion DataBase,” Bul-letin of the Seismological Society of America, Vol. 90, No. 6B, 2000, pp. S113-S135.
doi:10.1785/0120000511

[36] D. M. Boore, W. B. Joyner and T. E. Fumal, “Equations for Estimating Horizontal Response Spectra and Peak Acceleration from Western North American Earthquakes: A Summary of Recent Work,” Seismological Research Letters, Vol. 68, No. 1, 1997, pp. 128-153.

[37] K. Sadigh, C.-Y. Chang, J. A. Egan, F. Makdisi and R. R. Youngs, “Attenuation Relations for Shallow Crustal Earthquakes Based on California Strong Motion Data,” Seismological Research Letters, Vol. 68, No. 1, 1997, pp. 180-189.

[38] N. A. Abra-hamson, and W. J. Silva, “Empirical Response Spectral At-tenuation Relations for Shallow Crustal Earthquakes,” Seis-mological Research Letters, Vol. 68, No. 1, 1997, pp. 94-12.

[39] K. W. Campbell, “Empirical Near-source Attenua-tion Relations for Horizontal and Vertical Components of Peak Ground Acceleration, Peak Ground Velocity, and Pseudo-absolute Acceleration Response Spectra,” Seismologi-cal Research Letters, Vol. 68, No. 1, 1997, pp. 154-179.

[40] I. M. Idriss, “An Overview of Earthquake Ground Motion Perti-nent to Seismic Zonation,” 5th International Conference on Seismic Zonation, 1995, pp. 17-19.