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We discuss the design of sampled-data economic nonlinear model predictive control schemes for continuous-time systems based on turnpike properties. In a recent paper we have shown that an exact turnpike property allows establishing finite-time convergence ...
We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...
We investigate the nonsmooth and nonconvex L-1-Potts functional in discrete and continuous time. We show Gamma-convergence of discrete L-1-Potts functionals toward their continuous counterpart and obtain a convergence statement for the corresponding minimi ...
This paper carries out a detailed transient analysis of the learning behavior of multiagent networks, and reveals interesting results about the learning abilities of distributed strategies. Among other results, the analysis reveals how combination policies ...
This paper is concerned with the mathematical analysis of a coupled elliptic–parabolic system modeling the interaction between the propagation of electric potential and subsequent deformation of the cardiac tissue. The problem consists in a reaction–diffus ...
A proof for the point-wise convergence of the factors in the higher-order power method for tensors towards a critical point is given. It is obtained by applying established results from the theory of Lojasiewicz inequalities to the equivalent, unconstraine ...
The goal of this paper is to derive a structure preserving integrator for geometrically exact beam dynamics, by using a Lie group variational integrator. Both spatial and temporal discretization are implemented in a geometry preserving manner. The resultin ...
We investigate the nonsmooth and nonconvex L1 -Potts functional in discrete and continuous time. We show Γ-convergence of discrete L1 -Potts functionals toward their continuous counterpart and obtain a convergence statement for the corr ...
We develop rigorous alternating direction optimization methods for a prototype constrained convex optimization template, which has broad applications in computational sciences. We build upon our earlier work on the model-based gap reduction (MGR) technique ...
The MBI (maximum block improvement) method is a greedy approach to solving optimization problems where the decision variables can be grouped into a finite number of blocks. Assuming that optimizing over one block of variables while fixing all others is rel ...
