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The convergence and efficiency of the reduced basis method used for the approximation of the solutions to a class of problems written as a parametrized PDE depends heavily on the choice of the elements that constitute the "reduced basis". The purpose of th ...
In this work we consider quasi-optimal versions of the Stochastic Galerkin Method for solving linear elliptic PDEs with stochastic coeffcients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solu ...
In this work, we exploit the fact that wavelets can represent magnetic resonance images well, with relatively few coefficients. We use this property to improve magnetic resonance imaging (MRI) reconstructions from undersampled data with arbitrary k-space t ...
Institute of Electrical and Electronics Engineers2011
Identification of kinetic models is essential for monitoring, control and optimization of industrial processes. Robust kinetic models are often based on first-principles and described by differential equations. Identification of reaction kinetics, namely r ...
The direct evaluation program tailored to the singular integrals arising in the first-kind and second-kind Fredholm surface integral equation formulations is presented. The exponential convergence of the proposed technique can safely guarantee the inherite ...
We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Theoretical results about the co ...
Adaptive networks consist of a collection of nodes with adaptation and learning abilities. The nodes interact with each other on a local level and diffuse information across the network through their collaborations, as dictated by the network topology and ...
We clarify questions related to the convergence of the operator product expansion and conformal block decomposition in unitary conformal field theories (for any number of spacetime dimensions). In particular, we explain why these expansions are convergent ...
Motivated by recent developments in the context of adaptation over networks, this work establishes useful results about the limiting global behavior of diffusion and consensus strategies for the solution of distributed optimization problems. It is known th ...
This paper proposes a distributed resource assignment strategy for cognitive networks mimicking a swarm foraging mechanism, assuming that the communication among the cognitive nodes is impaired by random link failures and quantization noise. Using results ...