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Detection Of Random Signals In Dependent Gaussian Noise 2016 Edition at Meripustak

Detection Of Random Signals In Dependent Gaussian Noise 2016 Edition

Books from same Author: Antonio F. Gualtierotti

Books from same Publisher: Springer

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    • General Information  
    Author(s)Antonio F. Gualtierotti
    PublisherSpringer
    ISBN9783319223148
    Pages1176
    BindingHardback
    LanguageEnglish
    Publish YearFebruary 2016

    Description

    Springer Detection Of Random Signals In Dependent Gaussian Noise 2016 Edition by Antonio F. Gualtierotti

    The book presents the necessary mathematical basis to obtain and rigorously use likelihoods for detection problems with Gaussian noise. To facilitate comprehension the text is divided into three broad areas - reproducing kernel Hilbert spaces Cramer-Hida representations and stochastic calculus - for which a somewhat different approach was used than in their usual stand-alone context.One main applicable result of the book involves arriving at a general solution to the canonical detection problem for active sonar in a reverberation-limited environment. Nonetheless the general problems dealt with in the text also provide a useful framework for discussing other current research areas such as wavelet decompositions neural networks and higher order spectral analysis.The structure of the book with the exposition presenting as many details as necessary was chosen to serve both those readers who are chiefly interested in the results and those who want to learn the material from scratch. Hence the text will be useful for graduate students and researchers alike in the fields of engineering mathematics and statistics. Table of contents : Prolog.- Part I: Reproducing Kernel Hilbert Spaces.- Part II: Cramer-Hida Representations.- Part III: Likelihoods.- Credits and Comments.- Notation and Terminology.- References.- Index.