Wavelets in identification

[1]  Andrew R. Barron,et al.  Universal approximation bounds for superpositions of a sigmoidal function , 1993, IEEE Trans. Inf. Theory.

[2]  E. Nadaraya.  On Estimating Regression , 1964 .

[3]  L. Devroye,et al.  Distribution-Free Consistency Results in Nonparametric Discrimination and Regression Function Estimation , 1980 .

[4]  Michèle Basseville,et al.  The asymptotic local approach to change detection and model validation , 1987 .

[5]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[6]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[7]  Shang-Liang Chen,et al.  Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.

[8]  Michèle Basseville,et al.  Early warning of slight changes in systems , 1994, Autom..

[9]  G. S. Watson,et al.  Smooth regression analysis , 1964 .

[10]  Ker-Chau Li,et al.  Asymptotic optimality of CL and generalized cross-validation in ridge regression with application to spline smoothing , 1986 .

[11]  J. Friedman.  Multivariate adaptive regression splines , 1990 .

[12]  J. Rice.  Bandwidth Choice for Nonparametric Regression , 1984 .

[13]  Peter J. Gawthrop,et al.  Neural networks for control systems - A survey , 1992, Autom..

[14]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..

[15]  H. Akaike.  Statistical predictor identification , 1970 .

[16]  Qinghua Zhang,et al.  Monitoring the Combustion Set of a Gas Turbine , 1994 .

[17]  B. Portier.  Estimation non parametrique et commande adaptative de processus markoviens non lineaires , 1992 .

[18]  I. Johnstone,et al.  Wavelet Shrinkage: Asymptopia? , 1995 .

[19]  M. Rosenblatt.  Remarks on Some Nonparametric Estimates of a Density Function , 1956 .

[20]  H. Triebel.  Theory Of Function Spaces , 1983 .

[21]  Madan M. Gupta,et al.  Conditional Logic in Expert Systems , 1991 .

[22]  C. J. Stone,et al.  Optimal Global Rates of Convergence for Nonparametric Regression , 1982 .

[23]  Shie Qian,et al.  Signal representation using adaptive normalized Gaussian functions , 1994, Signal Process..

[24]  D. Dubois,et al.  Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions , 1999 .

[25]  W. Sickel.  Spline Representations of Functions in Besov-Triebel-Lizorkin Spaces on ℝ n , 1990 .

[26]  P. Vaidyanathan.  Quadrature mirror filter banks, M-band extensions and perfect-reconstruction techniques , 1987, IEEE ASSP Magazine.

[27]  T. Wagner,et al.  Asymptotically optimal discriminant functions for pattern classification , 1969, IEEE Trans. Inf. Theory.

[28]  J. Friedman,et al.  Projection Pursuit Regression , 1981 .

[29]  H. Müller,et al.  Variable Bandwidth Kernel Estimators of Regression Curves , 1987 .

[30]  G. Kerkyacharian,et al.  Density estimation in Besov spaces , 1992 .

[31]  D. M. Ellis,et al.  Applied Regression Analysis , 1968 .

[32]  Chuen-Chien Lee,et al.  Fuzzy logic in control systems: fuzzy logic controller. II , 1990, IEEE Trans. Syst. Man Cybern..

[33]  C. L. Mallows.  Some comments on C_p , 1973 .

[34]  Lennart Ljung,et al.  Perspectives on the Process of Identification , 1993 .

[35]  Qinghua Zhang.  Contribution à la surveillance de procédés industriels , 1991 .

[36]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[37]  Leo Breiman,et al.  Hinging hyperplanes for regression, classification, and function approximation , 1993, IEEE Trans. Inf. Theory.

[38]  Qinghua Zhang,et al.  Regressor selection and wavelet network construction , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[39]  I. Johnstone,et al.  Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[40]  Qinghua Zhang,et al.  Wavelet networks , 1992, IEEE Trans. Neural Networks.

[41]  J. Morgan,et al.  Problems in the Analysis of Survey Data, and a Proposal , 1963 .

[42]  R. DeVore,et al.  Compression of wavelet decompositions , 1992 .

[43]  Eduardo Sontag.  Nonlinear regulation: The piecewise linear approach , 1981 .

[44]  Bernard Delyon,et al.  Accuracy analysis for wavelet approximations , 1995, IEEE Trans. Neural Networks.

[45]  Qinghua Zhang.  Wavelet Network : The Radial Structure and an Efficient Initialization Procedure , 1992 .

[46]  Peter Craven,et al.  Smoothing noisy data with spline functions , 1978 .

[47]  Sheng Chen,et al.  Orthogonal least squares methods and their application to non-linear system identification , 1989 .

[48]  R. Z. Khasʹminskiĭ,et al.  Statistical estimation : asymptotic theory , 1981 .

[49]  Qinghua Zhang,et al.  Early Warning of Slight Changes in Systems and Plants , 1993 .

[50]  W. Härdle,et al.  Optimal Bandwidth Selection in Nonparametric Regression Function Estimation , 1985 .

[51]  E. Parzen.  On Estimation of a Probability Density Function and Mode , 1962 .

[52]  L. Wang,et al.  Fuzzy systems are universal approximators , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[53]  Luc Devroye,et al.  Any Discrimination Rule Can Have an Arbitrarily Bad Probability of Error for Finite Sample Size , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[54]  Lotfi A. Zadeh,et al.  Fuzzy logic, neural networks, and soft computing , 1993, CACM.

[55]  A. Tsybakov,et al.  Minimax theory of image reconstruction , 1993 .

[56]  Ker-Chau Li,et al.  Asymptotic Optimality for $C_p, C_L$, Cross-Validation and Generalized Cross-Validation: Discrete Index Set , 1987 .