Introduction to the Issue on Convex Optimization Methods for Signal Processing

The early 1990s witnessed the onset of a surge of research in optimization inspired, in part, by the generalization of interior point methods for solving linear programs to a rich class of convex optimization problems. This ongoing work has substantially enlarged the set of engineering design problems that can be reliably solved in an efficient manner, and the concurrent development of general purpose software tools has made these methods accessible to researchers and practitioners alike. For example, robust optimization techniques now enable effective design in several applications in which computational efficiency and the ability to deal with uncertainties are of paramount importance.