東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Mathematics of Computing." ]

切換: 標籤 | MARC模式 | ISBD

Information theory = three theorems ...

Chambert-Loir, Antoine.

FindBook

Google Book

Amazon

博客來

Information theory = three theorems by claude shannon /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Information theory/ by Antoine Chambert-Loir.
其他題名:	three theorems by claude shannon /
作者:	Chambert-Loir, Antoine.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xii, 209 p. :ill., digital ;24 cm.
內容註:	Elements of Theory of Probability -- Entropy and Mutual Information -- Coding -- Sampling -- Solutions to Exercises -- Bibliography -- Notation -- Index.
Contained By:	Springer Nature eBook
標題:	Information theory. -
電子資源:	https://doi.org/10.1007/978-3-031-21561-2
ISBN:	9783031215612

Information theory = three theorems by claude shannon /
Chambert-Loir, Antoine.

Information theorythree theorems by claude shannon /[electronic resource] :by Antoine Chambert-Loir. - Cham :Springer International Publishing :2022. - xii, 209 p. :ill., digital ;24 cm. - UNITEXT. La matematica per il 3+2,v. 1442038-5757 ;. - UNITEXT.La matematica per il 3+2 ;v. 144..

Elements of Theory of Probability -- Entropy and Mutual Information -- Coding -- Sampling -- Solutions to Exercises -- Bibliography -- Notation -- Index.

This book provides an introduction to information theory, focussing on Shannon's three foundational theorems of 1948-1949. Shannon's first two theorems, based on the notion of entropy in probability theory, specify the extent to which a message can be compressed for fast transmission and how to erase errors associated with poor transmission. The third theorem, using Fourier theory, ensures that a signal can be reconstructed from a sufficiently fine sampling of it. These three theorems constitute the roadmap of the book. The first chapter studies the entropy of a discrete random variable and related notions. The second chapter, on compression and error correcting, introduces the concept of coding, proves the existence of optimal codes and good codes (Shannon's first theorem), and shows how information can be transmitted in the presence of noise (Shannon's second theorem) The third chapter proves the sampling theorem (Shannon's third theorem) and looks at its connections with other results, such as the Poisson summation formula. Finally, there is a discussion of the uncertainty principle in information theory. Featuring a good supply of exercises (with solutions), and an introductory chapter covering the prerequisites, this text stems out lectures given to mathematics/computer science students at the beginning graduate level.

ISBN: 9783031215612

Standard No.: 10.1007/978-3-031-21561-2doiSubjects--Topical Terms:

542527
Information theory.

LC Class. No.: Q360

Dewey Class. No.: 003.54

Information theory = three theorems by claude shannon /
LDR:02545nmm a2200337 a 4500 001 2308185
003 DE-He213
005 20230315072045.0
006 m d
007 cr nn 008maaau
008 230526s2022 sz s 0 eng d
020 $a 9783031215612 $q (electronic bk.)
020 $a 9783031215605 $q (paper)
024 7 $a 10.1007/978-3-031-21561-2 $2 doi
035 $a 978-3-031-21561-2
040 $a GP $c GP
041 0 $a eng
050 4 $a Q360
072 7 $a UYAM $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UYAM $2 thema
082 0 4 $a 003.54 $2 23
090 $a Q360 $b .C445 2022
100 1 $a Chambert-Loir, Antoine. $3 891075
245 1 0 $a Information theory $h [electronic resource] : $b three theorems by claude shannon / $c by Antoine Chambert-Loir.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xii, 209 p. : $b ill., digital ; $c 24 cm.
490 1 $a UNITEXT. La matematica per il 3+2, $x 2038-5757 ; $v v. 144
505 0 $a Elements of Theory of Probability -- Entropy and Mutual Information -- Coding -- Sampling -- Solutions to Exercises -- Bibliography -- Notation -- Index.
520 $a This book provides an introduction to information theory, focussing on Shannon's three foundational theorems of 1948-1949. Shannon's first two theorems, based on the notion of entropy in probability theory, specify the extent to which a message can be compressed for fast transmission and how to erase errors associated with poor transmission. The third theorem, using Fourier theory, ensures that a signal can be reconstructed from a sufficiently fine sampling of it. These three theorems constitute the roadmap of the book. The first chapter studies the entropy of a discrete random variable and related notions. The second chapter, on compression and error correcting, introduces the concept of coding, proves the existence of optimal codes and good codes (Shannon's first theorem), and shows how information can be transmitted in the presence of noise (Shannon's second theorem) The third chapter proves the sampling theorem (Shannon's third theorem) and looks at its connections with other results, such as the Poisson summation formula. Finally, there is a discussion of the uncertainty principle in information theory. Featuring a good supply of exercises (with solutions), and an introductory chapter covering the prerequisites, this text stems out lectures given to mathematics/computer science students at the beginning graduate level.
650 0 $a Information theory. $3 542527
650 1 4 $a Mathematics of Computing. $3 891213
650 2 4 $a Coding and Information Theory. $3 891252
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a UNITEXT. $p La matematica per il 3+2 ; $v v. 144. $3 3614172
856 4 0 $u https://doi.org/10.1007/978-3-031-21561-2
950 $a Mathematics and Statistics (SpringerNature-11649)