David L. Donoho,Michael Elad.Optimally sparse representation in general (nonorthogonal) dictionaries via ?1 minimization.Proceedings of the National Academy of Sciences of the United States of America. 2003D. D
The concept of optimally sparse approximation of cartoon-like images of general (directional) representation systems was already discussed in Section 1.2. However, the attentive reader will have realized that only the situation of tight frames was studied whereas here we need to consider sparse approxi...
Our main contribution is the introduction of several valid inequalities (cuts) based on a sparse graph representation of warehouses which, to the best of our knowledge, have never been proposed before. We show that the inclusion of these cuts in the non-compact formulation greatly improves ...
The general steepest ascent algorithm features a virtual C++ class called Position. A position has three functions: value(), neighbors(), and show(), the last of which returns a string containing a textual representation of a Position. Here are snippets of the code, taken from my hillclimb....
Elad, "Optimally sparse representation in general (nonorthogonal) dictionaries via 1 minimization," Proceedings of the National Academy of Sciences, vol. 100, no. 5, pp. 2197-2202, 2003.Donoho, D. L. and Elad, M. (2003). Optimally sparse representation in general (nonorthogonal) dictionaries...
We prove that for a wide class of linear hyperbolic differential equations, the curvelet representation of the solution operator is both optimally sparse and well organized. \\ud\\ud \t* It is sparse in the sense that the matrix entries decay nearly exponentially fast (i.e., faster than ...