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

切換: 標籤 | MARC模式 | ISBD

Algebraic graph algorithms = a pract...

Erciyes, K.

FindBook

Google Book

Amazon

博客來

Algebraic graph algorithms = a practical guide using Python /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Algebraic graph algorithms/ by K. Erciyes.
其他題名:	a practical guide using Python /
作者:	Erciyes, K.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xiii, 221 p. :ill., digital ;24 cm.
內容註:	1. Introduction -- 2. Graphs, Matrices and Matroids -- 3. Parallel Matrix Algorithm Kernel -- 4. Basic Graph Algorithms -- 5. Connectivity, Matching and Matroids -- 6. Subgraph Search -- 7. Analysis of Large Graphs -- 8. Clustering in Complex Networks -- 9. Kronecker Graphs -- 10. Sample Algorithms for Complex Networks.
Contained By:	Springer Nature eBook
標題:	Graph algorithms. -
電子資源:	https://doi.org/10.1007/978-3-030-87886-3
ISBN:	9783030878863

Algebraic graph algorithms = a practical guide using Python /
Erciyes, K.

Algebraic graph algorithmsa practical guide using Python /[electronic resource] :by K. Erciyes. - Cham :Springer International Publishing :2021. - xiii, 221 p. :ill., digital ;24 cm. - Undergraduate topics in computer science,2197-1781. - Undergraduate topics in computer science..

1. Introduction -- 2. Graphs, Matrices and Matroids -- 3. Parallel Matrix Algorithm Kernel -- 4. Basic Graph Algorithms -- 5. Connectivity, Matching and Matroids -- 6. Subgraph Search -- 7. Analysis of Large Graphs -- 8. Clustering in Complex Networks -- 9. Kronecker Graphs -- 10. Sample Algorithms for Complex Networks.

There has been unprecedented growth in the study of graphs, which are discrete structures that have many real-world applications. The design and analysis of algebraic algorithms to solve graph problems have many advantages, such as implementing results from matrix algebra and using the already available matrix code for sequential and parallel processing. Providing Python programming language code for nearly all algorithms, this accessible textbook focuses on practical algebraic graph algorithms using results from matrix algebra rather than algebraic study of graphs. Given the vast theory behind the algebraic nature of graphs, the book strives for an accessible, middle-ground approach by reviewing main algebraic results that are useful in designing practical graph algorithms on the one hand, yet mostly using graph matrices to solve the graph problems. Python is selected for its simplicity, efficiency and rich library routines; and with the code herein, brevity is forsaken for clarity. Topics and features: Represents graphs by algebraic structures, enabling new, robust methods for algorithm analysis and design Provides matroid-based solutions to some graph problems, including greedy algorithm problems Offers Python code that can be tested and modified for various inputs Supplies practical hints, where possible, for parallel processing associated with algebraic algorithms Links to a web page with supportive materials This clearly arranged textbook will be highly suitable for upper-level undergraduate students of computer science, electrical and electronic engineering, bioinformatics, and any researcher or person with background in discrete mathematics, basic graph theory and algorithms. Dr. Kayhan Erciyes is a full Professor in the Department of Software Engineering at Maltepe University, Istanbul, Turkey. His other publications include the Springer titles Discrete Mathematics and Graph Theory, Distributed Real-Time Systems, Guide to Graph Algorithms, Distributed and Sequential Algorithms for Bioinformatics, and Distributed Graph Algorithms for Computer Networks.

ISBN: 9783030878863

Standard No.: 10.1007/978-3-030-87886-3doiSubjects--Topical Terms:

596326
Graph algorithms.

LC Class. No.: QA166.245 / .E73 2021

Dewey Class. No.: 518.1

Algebraic graph algorithms = a practical guide using Python /
LDR:03464nmm 22003375a 4500 001 2258713
003 DE-He213
005 20211117134618.0
006 m d
007 cr nn 008maaau
008 220422s2021 sz s 0 eng d
020 $a 9783030878863 $q (electronic bk.)
020 $a 9783030878856 $q (paper)
024 7 $a 10.1007/978-3-030-87886-3 $2 doi
035 $a 978-3-030-87886-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA166.245 $b .E73 2021
072 7 $a UMB $2 bicssc
072 7 $a COM051300 $2 bisacsh
072 7 $a UMB $2 thema
082 0 4 $a 518.1 $2 23
090 $a QA166.245 $b .E65 2021
100 1 $a Erciyes, K. $3 2162439
245 1 0 $a Algebraic graph algorithms $h [electronic resource] : $b a practical guide using Python / $c by K. Erciyes.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xiii, 221 p. : $b ill., digital ; $c 24 cm.
490 1 $a Undergraduate topics in computer science, $x 2197-1781
505 0 $a 1. Introduction -- 2. Graphs, Matrices and Matroids -- 3. Parallel Matrix Algorithm Kernel -- 4. Basic Graph Algorithms -- 5. Connectivity, Matching and Matroids -- 6. Subgraph Search -- 7. Analysis of Large Graphs -- 8. Clustering in Complex Networks -- 9. Kronecker Graphs -- 10. Sample Algorithms for Complex Networks.
520 $a There has been unprecedented growth in the study of graphs, which are discrete structures that have many real-world applications. The design and analysis of algebraic algorithms to solve graph problems have many advantages, such as implementing results from matrix algebra and using the already available matrix code for sequential and parallel processing. Providing Python programming language code for nearly all algorithms, this accessible textbook focuses on practical algebraic graph algorithms using results from matrix algebra rather than algebraic study of graphs. Given the vast theory behind the algebraic nature of graphs, the book strives for an accessible, middle-ground approach by reviewing main algebraic results that are useful in designing practical graph algorithms on the one hand, yet mostly using graph matrices to solve the graph problems. Python is selected for its simplicity, efficiency and rich library routines; and with the code herein, brevity is forsaken for clarity. Topics and features: Represents graphs by algebraic structures, enabling new, robust methods for algorithm analysis and design Provides matroid-based solutions to some graph problems, including greedy algorithm problems Offers Python code that can be tested and modified for various inputs Supplies practical hints, where possible, for parallel processing associated with algebraic algorithms Links to a web page with supportive materials This clearly arranged textbook will be highly suitable for upper-level undergraduate students of computer science, electrical and electronic engineering, bioinformatics, and any researcher or person with background in discrete mathematics, basic graph theory and algorithms. Dr. Kayhan Erciyes is a full Professor in the Department of Software Engineering at Maltepe University, Istanbul, Turkey. His other publications include the Springer titles Discrete Mathematics and Graph Theory, Distributed Real-Time Systems, Guide to Graph Algorithms, Distributed and Sequential Algorithms for Bioinformatics, and Distributed Graph Algorithms for Computer Networks.
650 0 $a Graph algorithms. $3 596326
650 0 $a Python (Computer program language) $3 729789
650 1 4 $a Algorithm Analysis and Problem Complexity. $3 891007
650 2 4 $a Discrete Mathematics in Computer Science. $3 892513
650 2 4 $a Mathematical Applications in Computer Science. $3 1567978
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Undergraduate topics in computer science. $3 1567579
856 4 0 $u https://doi.org/10.1007/978-3-030-87886-3
950 $a Computer Science (SpringerNature-11645)