語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Detection of random signals in depen...
~
Gualtierotti, Antonio F.
Detection of random signals in dependent Gaussian noise
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Detection of random signals in dependent Gaussian noiseby 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.
電子資源:
http://dx.doi.org/10.1007/978-3-319-22315-5
ISBN:
9783319223155$q(electronic bk.)
Detection of random signals in dependent Gaussian noise
Gualtierotti, Antonio F.
Detection of random signals in dependent Gaussian noise
[electronic resource] /by Antonio F. Gualtierotti. - Cham :Springer International Publishing :2015. - xxxiv, 1176 p. :ill., digital ;24 cm.
Prolog -- Part I: Reproducing Kernel Hilbert Spaces -- Part II: Cramer-Hida Representations -- Part III: Likelihoods -- Credits and Comments -- Notation and Terminology -- References -- Index.
The book presents the necessary mathematical basis to obtain and rigorously use likelihoods for detection problems with Gaussian noise. To facilitate comprehension the text is divided into three broad areas - reproducing kernel Hilbert spaces, Cramer-Hida representations and stochastic calculus - for which a somewhat different approach was used than in their usual stand-alone context. One main applicable result of the book involves arriving at a general solution to the canonical detection problem for active sonar in a reverberation-limited environment. Nonetheless, the general problems dealt with in the text also provide a useful framework for discussing other current research areas, such as wavelet decompositions, neural networks, and higher order spectral analysis. The structure of the book, with the exposition presenting as many details as necessary, was chosen to serve both those readers who are chiefly interested in the results and those who want to learn the material from scratch. Hence, the text will be useful for graduate students and researchers alike in the fields of engineering, mathematics and statistics.
ISBN: 9783319223155$q(electronic bk.)
Standard No.: 10.1007/978-3-319-22315-5doiSubjects--Topical Terms:
224681
Random noise theory.
LC Class. No.: TK5102.5
Dewey Class. No.: 003.54
Detection of random signals in dependent Gaussian noise
LDR
:02305nmm a2200325 a 4500
001
477714
003
DE-He213
005
20160512150326.0
006
m d
007
cr nn 008maaau
008
160614s2015 gw s 0 eng d
020
$a
9783319223155$q(electronic bk.)
020
$a
9783319223148$q(paper)
024
7
$a
10.1007/978-3-319-22315-5
$2
doi
035
$a
978-3-319-22315-5
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TK5102.5
072
7
$a
PBT
$2
bicssc
072
7
$a
PBWL
$2
bicssc
072
7
$a
MAT029000
$2
bisacsh
082
0 4
$a
003.54
$2
23
090
$a
TK5102.5
$b
.G912 2015
100
1
$a
Gualtierotti, Antonio F.
$3
732724
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
224681
650
1 4
$a
Mathematics.
$3
184409
650
2 4
$a
Probability Theory and Stochastic Processes.
$3
274061
650
2 4
$a
Functional Analysis.
$3
274845
650
2 4
$a
Information and Communication, Circuits.
$3
276027
710
2
$a
SpringerLink (Online service)
$3
273601
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)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000120546
電子館藏
1圖書
電子書
EB TK5102.5 G912 2015
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-3-319-22315-5
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入