Stability problems of continuous-time recurrent neural networks have been extensively
studied, and many papers have been published in the literature. The purpose of this paper is …

This paper reviews the stability analysis of continuous-time fuzzy-model-based (FMB)
control systems, with emphasis on state-feedback control techniques, which is an essential …

Convex optimization problems arise frequently in many different fields. This book provides a
comprehensive introduction to the subject, and shows in detail how such problems can be …

For both their theoretical and practical impact, time-delay systems have been an enduring
theme in the study of differential equations, stochastic processes, game theory, and systems …

In this paper we survey the primary research, both theoretical and applied, in the area of
robust optimization (RO). Our focus is on the computational attractiveness of RO …

We consider the problem of finding a linear iteration that yields distributed averaging
consensus over a network, ie, that asymptotically computes the average of some initial …

Safety critical and high-integrity systems, such as industrial plants and economic systems
can be subject to abrupt changes-for instance due to component or interconnection failure …

This paper reviews the vast literature on static output feedback design for linear time-
invariant systems including classical results and recent developments. In particular, we …

Hilbert space theory of Chapter 13. The rather lengthy proof that every metric space can be
embedded in its completion may be omitted. Chapter 14 contains a brief introduction to …

Convex Analysis is the calculus of inequalities while Convex Optimization is its application.
Analysis is inherently the domain of the mathematician while Optimization belongs to the …