國立虎尾科技大學 |

Probability in Electrical Engineering and Computer Science = An Application-Driven Course /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Probability in Electrical Engineering and Computer Science/ by Jean Walrand.
其他題名:	An Application-Driven Course /
作者:	Walrand, Jean.
面頁冊數:	XXI, 380 p. 214 illus., 146 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematical statistics. -
電子資源:	https://doi.org/10.1007/978-3-030-49995-2
ISBN:	9783030499952

Probability in Electrical Engineering and Computer Science = An Application-Driven Course /
Walrand, Jean.

Probability in Electrical Engineering and Computer ScienceAn Application-Driven Course /[electronic resource] :by Jean Walrand. - 1st ed. 2021. - XXI, 380 p. 214 illus., 146 illus. in color.online resource.

Chapter 1. Page Rank - A -- Chapter 2. Page Rank - B -- Chapter 3. Multiplexing - A -- Chapter 4. Multiplexing - B -- Chapter 5. Networks - A -- Chapter 6. Networks - B -- Chapter 7. Digital Link - A -- Chapter 8. Digital Link - B -- Chapter 9. Tracking - A -- Chapter 10. Tracking - B -- Chapter 11. Speech Recognition - A -- Chapter 12. Speech Recognition - B -- Chapter 13. Route planning - A -- Chapter 14. Route Planning - B -- chapter 15. Perspective & Complements -- A. Elementary Probability -- B. Basic Probability -- . Index.

Open Access

This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. The companion website now has many examples of Python demos and also Python labs used in Berkeley. Showcases techniques of applied probability with applications in EE and CS; Presents all topics with concrete applications so students see the relevance of the theory; Illustrates methods with Jupyter notebooks that use widgets to enable the users to modify parameters.

ISBN: 9783030499952

Standard No.: 10.1007/978-3-030-49995-2doiSubjects--Topical Terms:

527941
Mathematical statistics.

LC Class. No.: QA276-280

Dewey Class. No.: 005.55

Probability in Electrical Engineering and Computer Science = An Application-Driven Course /
LDR:03249nam a22004335i 4500 001 1055853
003 DE-He213
005 20210812072024.0
007 cr nn 008mamaa
008 220103s2021 sz | s |||| 0|eng d
020 $a 9783030499952 $9 978-3-030-49995-2
024 7 $a 10.1007/978-3-030-49995-2 $2 doi
035 $a 978-3-030-49995-2
050 4 $a QA276-280
072 7 $a UYAM $2 bicssc
072 7 $a COM077000 $2 bisacsh
072 7 $a UYAM $2 thema
072 7 $a UFM $2 thema
082 0 4 $a 005.55 $2 23
100 1 $a Walrand, Jean. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 882860
245 1 0 $a Probability in Electrical Engineering and Computer Science $h [electronic resource] : $b An Application-Driven Course / $c by Jean Walrand.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XXI, 380 p. 214 illus., 146 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Chapter 1. Page Rank - A -- Chapter 2. Page Rank - B -- Chapter 3. Multiplexing - A -- Chapter 4. Multiplexing - B -- Chapter 5. Networks - A -- Chapter 6. Networks - B -- Chapter 7. Digital Link - A -- Chapter 8. Digital Link - B -- Chapter 9. Tracking - A -- Chapter 10. Tracking - B -- Chapter 11. Speech Recognition - A -- Chapter 12. Speech Recognition - B -- Chapter 13. Route planning - A -- Chapter 14. Route Planning - B -- chapter 15. Perspective & Complements -- A. Elementary Probability -- B. Basic Probability -- . Index.
506 0 $a Open Access
520 $a This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. The companion website now has many examples of Python demos and also Python labs used in Berkeley. Showcases techniques of applied probability with applications in EE and CS; Presents all topics with concrete applications so students see the relevance of the theory; Illustrates methods with Jupyter notebooks that use widgets to enable the users to modify parameters.
650 0 $a Mathematical statistics. $3 527941
650 0 $a Electrical engineering. $3 596380
650 0 $a Applied mathematics. $3 1069907
650 0 $a Engineering mathematics. $3 562757
650 0 $a Probabilities. $3 527847
650 0 $a Statistics . $3 1253516
650 1 4 $a Probability and Statistics in Computer Science. $3 669886
650 2 4 $a Communications Engineering, Networks. $3 669809
650 2 4 $a Mathematical and Computational Engineering. $3 1139415
650 2 4 $a Probability Theory and Stochastic Processes. $3 593945
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030499945
776 0 8 $i Printed edition: $z 9783030499969
776 0 8 $i Printed edition: $z 9783030499976
856 4 0 $u https://doi.org/10.1007/978-3-030-49995-2
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
912 $a ZDB-2-SOB
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)