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This book discusses the problems that should be solved by nonlinear digital filtering and analyzes the drawbacks of the basic solutions, the mean and the median filters. It explores the intimate connection between filtering and statistical estimation.
In the meantime, it was realized that they can be used for solving important problems of prediction and statistical analysis of time series, and this book describes recent results in this area. The first chapter introduces and describes the application of universal codes to prediction and the statistical analysis of time series;
Presents and evaluates methods and applications in nonlinear digital filtering. Written for professors, researchers, and application engineers, as well as for serious students of signal processing, this book offers coverage of theoretical and practical aspects, and examples which provide information on nonlinear filtering and its applications.
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