Abstract Least-squares reverse-time migration (RTM) works with an inverse operation, rather than adjoint operation in a conventional RTM, and thus produces image higher resolution more balanced amplitude the RTM image. However, least-squares introduces two side effects: sidelobes around reflectors high-wavenumber artifacts. These effects are caused mainly by limited bandwidth of seismic data, c...

In this paper we devise a new algorithm for completing surface with missing geometry and topology founded upon the theory and techniques of sparse signal recovery. The key intuition is that any meaningful 3D shape, represented as a discrete mesh, almost certainly possesses a low-dimensional intrinsic structure, which can be expressed as a sparse representation in some transformed domains. Inste...

We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the resulting optimization problem is generally NP-hard, several approximation algorithms are considered. We analyze the performance of these algorithms, focusing on the characterization of the trade-off between accuracy a...

This paper presents the solution to a general decentralized state-feedback problem, in which the plant and controller must satisfy the same combination of delay constraints and sparsity constraints. The control problem is decomposed into independent subproblems, which are solved by dynamic programming. In special cases with only sparsity or only delay constraints, the controller reduces to exis...