Nonparametric Identification of Weighting Function by Orthogonal Series Method
暂无分享,去创建一个
A nonparametric algorithm for identifying the weighting function in linear dynamic continuous-time systems is proposed. The algorithm is derived from orthogonal series estimates of derivatives of regression functions. Asymptotic properties are investigated for a general orthogonal system and sufficient conditions for convergence in the sense of the mean square error are given.
[1] L. Rutkowski. On-line identification of time-varying systems by nonparametric techniques , 1982 .
[2] G. Walter. Properties of Hermite Series Estimation of Probability Density , 1977 .
[3] A. Krzyżak,et al. Non-parametric identification of a memoryless system with a cascade structure , 1979 .
[4] S. Yakowitz,et al. Contributions to the Theory of Nonparametric Regression, with Application to System Identification , 1979 .