Semidefinite programming: a versatile tool for analysis and design of digital filters

Semidefinite programming (SDP) is a relatively new methodology for constrained optimization of a linear matrix-variable function subject to linear equality and inequality constraints as well as linear positive-semidefinite constraints. The primary purpose of this paper is to demonstrate that many digital-filter analysis and design problems can be formulated as SDP problems and, therefore, they can be solved effectively using powerful SDP solvers.