This original work offers the most comprehensive and up-to-date treatment of the important subject of optimal linear estimation, which is encountered in many areas of engineering such as communications, control, and signal processing, and also several other fields, e.g., econometrics and statistics. The book not only highlights the most significant contributions to this field during the 20th century, including the works of Weiner and Kalman, but it does so in an original and novel manner that paves the way for further developments in the new millennium.
This book contains a large collection of problems that complement the text and are an important part of it, in addition to numerous sections that offer interesting historical accounts and insights.
Largely focuses on estimation problems for finite-dimensional linear systems with state-space models, covering most aspects of an area now generally known as Wiener and Kalman filtering theory. Distinctive features the treatment are the pervasive use of a geometric point of view; the emphasis on the numerically favored square root/array forms of many algorithms; and the emphasis on equivalence and duality concepts for the solution of several related problems in adaptive filtering, estimation, and control. The authors argue that these features are not as abstract and complicated as other treatments of the topic seem to fear. Annotation c. Book News, Inc., Portland, OR (booknews.com)