We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and discrete-time linear systems. We mainly focus on the so-called Krasnoselskij-Mann iteration, x ( k + 1) = (1-α k) x ( k) + α k A x (k ), which is relevant for distributed computation in optimization and game theory, when A is not available in a centralized way. We show that strict pseudocontractiveness of the linear operator x ↠ Ax is not only sufficient (as known) but also necessary for the convergence to a vector in the kernel of I-A. We also characterize some relevant operator-theoretic properties of linear operators via eigenvalue location and linear matrix inequalities. We apply the convergence conditions to multi-agent linear systems w...
Convergence of the policy iteration method for discrete and continuous optimal control problems hold...
AbstractWe study the rate of convergence of a sequence of linear operators that converges pointwise ...
We investigate a novel nonlinear consensus from the extreme points of doubly stochastic quadratic op...
We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and...
This note aims to develop the nonnegative matrix theory, in particular the product properties of inf...
In the last decades, the study of convergence of fixed point iterative methods has received an incre...
Let K be a nonempty, closed, and convex subset of a real Hilbert space H. Suppose that T:K→2K is a m...
In this paper we extend the notion of convergence, as defined for continuous-time dynamical systems,...
State convergence is essential in many scientific areas, e.g. multi-agent consensus/disagreement, di...
Convergent sequences of real numbers play a fundamental role in many different problems in system th...
In this paper, we define the general framework to describe the diffusion operators associated to a p...
The theory of the convergence of Krylov subspace iterations for linear systems of equations (conjuga...
We introduce a characterization of contraction for bounded convex sets. For discrete-time multi-agen...
In [6] the authors introduced the concept of paracontracting operators for fixed point problems and ...
In this paper, we present a convergence rate analysis for the inexact Krasnosel’skĭı– Mann iteratio...
Convergence of the policy iteration method for discrete and continuous optimal control problems hold...
AbstractWe study the rate of convergence of a sequence of linear operators that converges pointwise ...
We investigate a novel nonlinear consensus from the extreme points of doubly stochastic quadratic op...
We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and...
This note aims to develop the nonnegative matrix theory, in particular the product properties of inf...
In the last decades, the study of convergence of fixed point iterative methods has received an incre...
Let K be a nonempty, closed, and convex subset of a real Hilbert space H. Suppose that T:K→2K is a m...
In this paper we extend the notion of convergence, as defined for continuous-time dynamical systems,...
State convergence is essential in many scientific areas, e.g. multi-agent consensus/disagreement, di...
Convergent sequences of real numbers play a fundamental role in many different problems in system th...
In this paper, we define the general framework to describe the diffusion operators associated to a p...
The theory of the convergence of Krylov subspace iterations for linear systems of equations (conjuga...
We introduce a characterization of contraction for bounded convex sets. For discrete-time multi-agen...
In [6] the authors introduced the concept of paracontracting operators for fixed point problems and ...
In this paper, we present a convergence rate analysis for the inexact Krasnosel’skĭı– Mann iteratio...
Convergence of the policy iteration method for discrete and continuous optimal control problems hold...
AbstractWe study the rate of convergence of a sequence of linear operators that converges pointwise ...
We investigate a novel nonlinear consensus from the extreme points of doubly stochastic quadratic op...