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Stability of Time-Delay Systems

TLDR
Preface, Notations 1.Introduction to Time-Delay Systems I.Robust Stability Analysis II.Input-output stability A.LMI and Quadratic Integral Inequalities Bibliography Index
Abstract
Preface, Notations 1.Introduction to Time-Delay Systems I.Frequency-Domain Approach 2.Systems with Commensurate Delays 3.Systems withIncommensurate Delays 4.Robust Stability Analysis II.Time Domain Approach 5.Systems with Single Delay 6.Robust Stability Analysis 7.Systems with Multiple and Distributed Delays III.Input-Output Approach 8.Input-output stability A.Matrix Facts B.LMI and Quadratic Integral Inequalities Bibliography Index

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Citations
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Journal ArticleDOI

Stability of Takagi–Sugeno Fuzzy Delay Systems With Impulse

TL;DR: The Takagi-Sugeno (T-S) model of fuzzy delay systems with impulse is presented and the criteria of uniform stability and uniform asymptotic stability for T-S fuzzy delay system with impulse are obtained.
Journal ArticleDOI

New exponential stability criteria for stochastic BAM neural networks with impulses

TL;DR: In this article, the global exponential stability of time-delayed stochastic bidirectional associative memory neural networks with impulses and Markovian jumping parameters is studied, and a generalized activation function is considered, and traditional assumptions on the boundedness, monotony and differentiability of activation functions are removed.
Journal ArticleDOI

An enhanced stability criterion for time-delay systems via a new bounding technique

TL;DR: By employing the newly bounding technique proposed in this paper, an enhanced stability criterion for a class of linear systems with an interval time-varying delay is derived.
Journal ArticleDOI

Exponential synchronization of neural networks with time-varying delays

TL;DR: By utilizing the Lyapunov functional method and combining it with linear matrix inequality approach, the exponential synchronization of the derive-response structure of neural networks is obtained.
Journal ArticleDOI

Output Feedback Stabilization of Networked Control Systems Under a Stochastic Scheduling Protocol

TL;DR: This paper investigates the output feedback stabilization problem for networked control systems under a stochastic scheduling protocol and uses the Lyapunov–Krasovskii functional approach to obtain sufficient conditions for guaranteeing the stability of the studied system in the mean-square sense.
References
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Book

The Nature of Statistical Learning Theory

TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Book

Matrix computations

Gene H. Golub
Book

Matrix Analysis

TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.