We present a new nonlinear optimization procedure for the computation of generalized Gaussian quadratures for a broad class of square integrable functions on intervals. While some ...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
The asymptotic convergence of parameterized variants of Newton's method for the solution of nonlinear systems of equations is considered. The original system is perturbed by a...
Nicholas I. M. Gould, Dominique Orban, Annick Sart...
This paper proposes a novel algorithm for decoding real-field codes over erroneous channels, where the encoded message is corrupted by sparse errors, i.e., impulsive noise. The m...