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Detection of random signals in depen...

Gualtierotti, Antonio F.

Detection of random signals in dependent Gaussian noise[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	003.54
書名/作者:	Detection of random signals in dependent Gaussian noise/ by Antonio F. Gualtierotti.
作者:	Gualtierotti, Antonio F.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xxxiv, 1176 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Random noise theory.
標題:	Mathematics.
標題:	Probability Theory and Stochastic Processes.
標題:	Functional Analysis.
標題:	Information and Communication, Circuits.
ISBN:	9783319223155
ISBN:	9783319223148
內容註:	Prolog -- Part I: Reproducing Kernel Hilbert Spaces -- Part II: Cramer-Hida Representations -- Part III: Likelihoods -- Credits and Comments -- Notation and Terminology -- References -- Index.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-22315-5

Detection of random signals in dependent Gaussian noise[electronic resource] /
Gualtierotti, Antonio F.

Detection of random signals in dependent Gaussian noise[electronic resource] /by Antonio F. Gualtierotti. - Cham :Springer International Publishing :2015. - xxxiv, 1176 p. :ill., digital ;24 cm.

Prolog -- Part I: Reproducing Kernel Hilbert Spaces -- Part II: Cramer-Hida Representations -- Part III: Likelihoods -- Credits and Comments -- Notation and Terminology -- References -- Index.

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.

ISBN: 9783319223155

Standard No.: 10.1007/978-3-319-22315-5doiSubjects--Topical Terms:

636366
Random noise theory.

LC Class. No.: TK5102.5

Dewey Class. No.: 003.54

Detection of random signals in dependent Gaussian noise[electronic resource] /
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100 1 $a Gualtierotti, Antonio F. $3 636365
245 1 0 $a Detection of random signals in dependent Gaussian noise $h [electronic resource] / $c by Antonio F. Gualtierotti.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xxxiv, 1176 p. : $b ill., digital ; $c 24 cm.
505 0 $a Prolog -- Part I: Reproducing Kernel Hilbert Spaces -- Part II: Cramer-Hida Representations -- Part III: Likelihoods -- Credits and Comments -- Notation and Terminology -- References -- Index.
520 $a 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.
650 0 $a Random noise theory. $3 636366
650 1 4 $a Mathematics. $3 172349
650 2 4 $a Probability Theory and Stochastic Processes. $3 463894
650 2 4 $a Functional Analysis. $3 464114
650 2 4 $a Information and Communication, Circuits. $3 464621
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773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-22315-5
950 $a Mathematics and Statistics (Springer-11649)

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