ENEE 662
Convex Optimization
Focuses on recognizing, solving, and analyzing convex optimization problems. Convex sets, convex functions, convex and quasi-convex optimization problems. Duality theory and optimality conditions. Specific classes of problems including linear optimization (LP), semi-definite optimization (SDP), geometric programming. Algorithms for unconstrained and constrained optimization; interior-point methods. Applications in controls, communications, signal processing, statistics, and other areas.
Prerequisites & course information
Recommended: MATH410 . Credit Only Granted for: ENEE759F or ENEE662 .
Sources
- Course catalogue ↗2026-2027