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OverviewThis text provides a unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms, which covers important approaches to obtaining an optimal estimator and analyzing its performance. Examples and real-world applications are included. The text: describes the field of parameter estimation based on time series data; provides a summary of principal approaches as well as a ""roadmap"" to use in the selection of an estimator; extends many of the results for real data/real parameters to complex data/complex parameters; summarizes as examples many of the important estimators used in practice; illustrates how a digital computer can be used to assess performance of an estimator; and emphasizes a linear model to allow an optimal estimator to be found by inspection of a data model. Full Product DetailsAuthor: Steven KayPublisher: Pearson Education (US) Imprint: Pearson Edition: US ed Dimensions: Width: 18.00cm , Height: 2.80cm , Length: 23.80cm Weight: 1.040kg ISBN: 9780133457117ISBN 10: 0133457117 Pages: 608 Publication Date: 08 May 1993 Audience: College/higher education , Tertiary & Higher Education Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |