大葉大學圖書館 |

Submodularity in dynamics and control of networked systems[electronic resource] /

纪录类型:	书目-语言数据,印刷品 : Monograph/item
[NT 15000414] null:	511.6
[NT 47271] Title/Author:	Submodularity in dynamics and control of networked systems/ by Andrew Clark ... [et al.].
[NT 51406] other author:	Clark, Andrew.
出版者:	Cham : : Springer International Publishing :, 2016.
面页册数:	xvii, 210 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
标题:	Submodular functions.
标题:	Computer networks.
标题:	Engineering.
标题:	Control.
标题:	Systems Theory, Control.
标题:	Communications Engineering, Networks.
ISBN:	9783319269771
ISBN:	9783319269757
[NT 15000228] null:	Part I: Submodular Functions and Optimization -- Submodular Functions and Matroids -- Centralized Submodular Maximization -- Distributed Submodular Maximization -- Submodularity in Dynamics and Control -- Background on Control of Networked Systems -- Submodular Optimization for Smooth Convergence in Networked Systems -- Selecting Catalyst Nodes for Synchronization -- Input Selection for Robustness to Noise -- Input Node Selection under Noise Injection Attacks -- Input Node Selection for Joint Performance and Controllability.
[NT 15000229] null:	This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllability with provable optimality bounds in static as well as time-varying networks. Throughout the text, the submodular framework is illustrated with the help of numerical examples and application-based case studies in biological, energy and vehicular systems. The book effectively combines two areas of growing interest, and will be especially useful for researchers in control theory, applied mathematics, networking or machine learning with experience in submodular optimization but who are less familiar with the problems and tools available for networked systems (or vice versa) It will also benefit graduate students, offering consistent terminology and notation that greatly reduces the initial effort associated with beginning a course of study in a new area.
电子资源:	http://dx.doi.org/10.1007/978-3-319-26977-1

Submodularity in dynamics and control of networked systems[electronic resource] /
Submodularity in dynamics and control of networked systems[electronic resource] /by Andrew Clark ... [et al.]. - Cham :Springer International Publishing :2016. - xvii, 210 p. :ill., digital ;24 cm. - Communications and control engineering,0178-5354. - Communications and control engineering..

Part I: Submodular Functions and Optimization -- Submodular Functions and Matroids -- Centralized Submodular Maximization -- Distributed Submodular Maximization -- Submodularity in Dynamics and Control -- Background on Control of Networked Systems -- Submodular Optimization for Smooth Convergence in Networked Systems -- Selecting Catalyst Nodes for Synchronization -- Input Selection for Robustness to Noise -- Input Node Selection under Noise Injection Attacks -- Input Node Selection for Joint Performance and Controllability.

This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllability with provable optimality bounds in static as well as time-varying networks. Throughout the text, the submodular framework is illustrated with the help of numerical examples and application-based case studies in biological, energy and vehicular systems. The book effectively combines two areas of growing interest, and will be especially useful for researchers in control theory, applied mathematics, networking or machine learning with experience in submodular optimization but who are less familiar with the problems and tools available for networked systems (or vice versa) It will also benefit graduate students, offering consistent terminology and notation that greatly reduces the initial effort associated with beginning a course of study in a new area.

ISBN: 9783319269771

Standard No.: 10.1007/978-3-319-26977-1doiSubjects--Topical Terms:

486261
Submodular functions.

LC Class. No.: QA166.6

Dewey Class. No.: 511.6

Submodularity in dynamics and control of networked systems[electronic resource] /
LDR:03318nam a2200325 a 4500 001 455713
003 DE-He213
005 20160808155415.0
006 m d
007 cr nn 008maaau
008 161227s2016 gw s 0 eng d
020 $a 9783319269771 $q (electronic bk.)
020 $a 9783319269757 $q (paper)
024 7 $a 10.1007/978-3-319-26977-1 $2 doi
035 $a 978-3-319-26977-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA166.6
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
082 0 4 $a 511.6 $2 23
090 $a QA166.6 $b .S941 2016
245 0 0 $a Submodularity in dynamics and control of networked systems $h [electronic resource] / $c by Andrew Clark ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xvii, 210 p. : $b ill., digital ; $c 24 cm.
490 1 $a Communications and control engineering, $x 0178-5354
505 0 $a Part I: Submodular Functions and Optimization -- Submodular Functions and Matroids -- Centralized Submodular Maximization -- Distributed Submodular Maximization -- Submodularity in Dynamics and Control -- Background on Control of Networked Systems -- Submodular Optimization for Smooth Convergence in Networked Systems -- Selecting Catalyst Nodes for Synchronization -- Input Selection for Robustness to Noise -- Input Node Selection under Noise Injection Attacks -- Input Node Selection for Joint Performance and Controllability.
520 $a This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllability with provable optimality bounds in static as well as time-varying networks. Throughout the text, the submodular framework is illustrated with the help of numerical examples and application-based case studies in biological, energy and vehicular systems. The book effectively combines two areas of growing interest, and will be especially useful for researchers in control theory, applied mathematics, networking or machine learning with experience in submodular optimization but who are less familiar with the problems and tools available for networked systems (or vice versa) It will also benefit graduate students, offering consistent terminology and notation that greatly reduces the initial effort associated with beginning a course of study in a new area.
650 0 $a Submodular functions. $3 486261
650 0 $a Computer networks. $3 174051
650 1 4 $a Engineering. $3 372756
650 2 4 $a Control. $3 463886
650 2 4 $a Systems Theory, Control. $3 463973
650 2 4 $a Communications Engineering, Networks. $3 463863
700 1 $a Clark, Andrew. $3 654348
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a Communications and control engineering. $x 0178-5354 $3 455709
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-26977-1
950 $a Engineering (Springer-11647)