Isbn: 9780521831277 - bootstrap techniques for signal processing (6 Ergebnisse)

Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Zustand: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9780521831277.…

Hardcover. Zustand: Like New. First Edition. A firm and square hardback with sharp corners and strong joints, just showing a few very minor rubs. Hence a non-text page has a small 'damaged' stamp. Despite such this book is actually in nearly new condition and appears unread. Thus the contents are crisp, fresh and tight. Also, no pen-marks and not from a library so no such stamps or labels. Now offered for sale at a very sensible price.…

Zustand: New. In English.

Zustand: New. An introduction to the use of the bootstrap in signal processing. Num Pages: 232 pages, 41 b/w illus. 34 tables. BIC Classification: TJF; TJK; UYS. Category: (P) Professional & Vocational. Dimension: 247 x 174 x 14. Weight in Grams: 625. . 2004. Illustrated. hardcover. . . . . Books ship from the US and Ireland.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.…