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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Bootstrap Techniques for Signal Processing

Bootstrap Techniques for Signal Processing

Zoubir, Abdelhak M.
Iskander, D. Robert

Paperback

Technology & EngineeringGeneral Science

ISBN10: 0521034051
ISBN13: 9780521034050
Publisher: Cambridge
Published: Feb 15 2007
Pages: 232
Weight: 0.83
Height: 0.49 Width: 6.69 Depth: 9.61
Language: English
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 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.

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