東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Synchronization control of markovian complex neural networks with time-varying delays

Record Type:	Electronic resources : Monograph/item
Title/Author:	Synchronization control of markovian complex neural networks with time-varying delays/ by Junyi Wang, Jun Fu.
Author:	Wang, Junyi.
other author:	Fu, Jun.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	viii, 159 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Stochastic synchronization of Markovian coupled neural networks with partially unknown transition rates -- Local synchronization of Markovian neutral-type complex networks with partially unknown transition rates -- Local Synchronization of Markovian nonlinearly coupled neural networks with generally uncertain transition rates -- Sampled-data synchronization of complex networks based on discontinuous Lyapunov-Krasovskii functional -- Sampled-data synchronization of Markovian coupled neural networks with time-varying mode delays -- Synchronization criteria of delayed inertial neural networks with generally uncertain transition rates -- Conclusions.
Contained By:	Springer Nature eBook
Subject:	Neural networks (Computer science) -
Online resource:	https://doi.org/10.1007/978-3-031-47835-2
ISBN:	9783031478352

Synchronization control of markovian complex neural networks with time-varying delays
Wang, Junyi.

Synchronization control of markovian complex neural networks with time-varying delays[electronic resource] /by Junyi Wang, Jun Fu. - Cham :Springer Nature Switzerland :2024. - viii, 159 p. :ill. (chiefly col.), digital ;24 cm. - Studies in systems, decision and control,v. 5142198-4190 ;. - Studies in systems, decision and control ;v. 514..

Introduction -- Stochastic synchronization of Markovian coupled neural networks with partially unknown transition rates -- Local synchronization of Markovian neutral-type complex networks with partially unknown transition rates -- Local Synchronization of Markovian nonlinearly coupled neural networks with generally uncertain transition rates -- Sampled-data synchronization of complex networks based on discontinuous Lyapunov-Krasovskii functional -- Sampled-data synchronization of Markovian coupled neural networks with time-varying mode delays -- Synchronization criteria of delayed inertial neural networks with generally uncertain transition rates -- Conclusions.

This monograph studies the synchronization control of Markovian complex neural networks with time-varying delays, and the structure of the book is summarized as follows. Chapter 1 introduces the system description and some background knowledges, and also addresses the motivations of this monograph. In Chapter 2, the stochastic synchronization issue of Markovian coupled neural networks with partially unknown transition rates and random coupling strengths is investigated. In Chapter 3, the local synchronization issue of Markovian neutral complex networks with partially information of transition rates is investigated. The new delay-dependent synchronization criteria in terms of LMIs are derived, which depends on the upper and lower bounds of the delays. In Chapter 4, the local synchronization issue of Markovian nonlinear coupled neural networks with uncertain and partially unknown transition rates is investigated. The less conservative local synchronization criteria containing the bounds of delay and delay derivative are obtained based on the novel augmented Lyapunov-Krasovskii functional and a new integral inequality. In Chapter 5, the sampled-data synchronization issue of delayed complex networks with aperiodic sampling interval is investigated based on enhanced input delay approach, which makes full use of the upper bound of the variable sampling interval and the sawtooth structure information of varying input delay. In Chapter 6, the sampled-data synchronization issue of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals is investigated based on an enhanced input delay approach. Furthermore, the mode-dependent sampled-data controllers are proposed based on the delay dependent synchronization criteria. In Chapter 7, the synchronization issue of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. In Chapter 8, we conclude the monograph by briefly summarizing the main theoretical findings.

ISBN: 9783031478352

Standard No.: 10.1007/978-3-031-47835-2doiSubjects--Topical Terms:

532070
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Synchronization control of markovian complex neural networks with time-varying delays
LDR:03789nmm a2200337 a 4500 001 2368012
003 DE-He213
005 20231128070845.0
006 m d
007 cr nn 008maaau
008 241127s2024 sz s 0 eng d
020 $a 9783031478352 $q (electronic bk.)
020 $a 9783031478345 $q (paper)
024 7 $a 10.1007/978-3-031-47835-2 $2 doi
035 $a 978-3-031-47835-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.87
072 7 $a THR $2 bicssc
072 7 $a TEC007000 $2 bisacsh
072 7 $a THR $2 thema
082 0 4 $a 006.32 $2 23
090 $a QA76.87 $b .W246 2024
100 1 $a Wang, Junyi. $3 3711591
245 1 0 $a Synchronization control of markovian complex neural networks with time-varying delays $h [electronic resource] / $c by Junyi Wang, Jun Fu.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a viii, 159 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4190 ; $v v. 514
505 0 $a Introduction -- Stochastic synchronization of Markovian coupled neural networks with partially unknown transition rates -- Local synchronization of Markovian neutral-type complex networks with partially unknown transition rates -- Local Synchronization of Markovian nonlinearly coupled neural networks with generally uncertain transition rates -- Sampled-data synchronization of complex networks based on discontinuous Lyapunov-Krasovskii functional -- Sampled-data synchronization of Markovian coupled neural networks with time-varying mode delays -- Synchronization criteria of delayed inertial neural networks with generally uncertain transition rates -- Conclusions.
520 $a This monograph studies the synchronization control of Markovian complex neural networks with time-varying delays, and the structure of the book is summarized as follows. Chapter 1 introduces the system description and some background knowledges, and also addresses the motivations of this monograph. In Chapter 2, the stochastic synchronization issue of Markovian coupled neural networks with partially unknown transition rates and random coupling strengths is investigated. In Chapter 3, the local synchronization issue of Markovian neutral complex networks with partially information of transition rates is investigated. The new delay-dependent synchronization criteria in terms of LMIs are derived, which depends on the upper and lower bounds of the delays. In Chapter 4, the local synchronization issue of Markovian nonlinear coupled neural networks with uncertain and partially unknown transition rates is investigated. The less conservative local synchronization criteria containing the bounds of delay and delay derivative are obtained based on the novel augmented Lyapunov-Krasovskii functional and a new integral inequality. In Chapter 5, the sampled-data synchronization issue of delayed complex networks with aperiodic sampling interval is investigated based on enhanced input delay approach, which makes full use of the upper bound of the variable sampling interval and the sawtooth structure information of varying input delay. In Chapter 6, the sampled-data synchronization issue of Markovian coupled neural networks with mode-dependent interval time-varying delays and aperiodic sampling intervals is investigated based on an enhanced input delay approach. Furthermore, the mode-dependent sampled-data controllers are proposed based on the delay dependent synchronization criteria. In Chapter 7, the synchronization issue of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. In Chapter 8, we conclude the monograph by briefly summarizing the main theoretical findings.
650 0 $a Neural networks (Computer science) $3 532070
650 0 $a Synchronization. $3 578767
650 1 4 $a Electrical and Electronic Engineering. $3 3591890
650 2 4 $a Control, Robotics, Automation. $3 3592500
650 2 4 $a Control and Systems Theory. $3 3381515
700 1 $a Fu, Jun. $3 2101117
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in systems, decision and control ; $v v. 514. $3 3711592
856 4 0 $u https://doi.org/10.1007/978-3-031-47835-2
950 $a Engineering (SpringerNature-11647)