Filtering Theory
Publication year: 2007
ISBN: 978-0-8176-4564-9
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The focus of this book is on filtering for linear processes, and its primary goal is to design filters from a class of linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. Various hierarchical classes of filtering problems are defined based on the availability of statistical knowledge regarding noise, disturbances, and other uncertainties. An important characteristic of the approach employed in this work for several aspects of filter analysis and design is structural in nature, revealing an inherent freedom to incorporate other classical secondary engineering constraints—such as placement of filter poles at desired locations—in filter design. Such a structural approach requires an understanding of powerful tools that then may be used in several engineering applications besides filtering.
Subject: Engineering, Bias, Filter, H-infinity filtering, H2 filtering, Information, STATISTICA, Signal, communication networks, decoupled filtering, delayed filtering, filtering theory, inverse filtering, layers, micro-alloy transistor, signal processing
