Course Name: Optimization Theory and its Applications in Signal Processing and Communications
Prerequisites: Linear algebra
This Course concentrates on recognizing and solving convex optimization problems that arise in signal processing and communications. It should benefit anyone who uses or will use scientific computing or optimization in engineering or related work.
The course covers the following contents:
Ø Convex sets, functions, and optimization problems.
Ø Basics of convex analysis, duality theory, optimiality conditions
Ø Optimality conditions, duality theory, theorems of alternative, and applications.
Ø Unconstrained, Equality constrained and Inequality constrained minimization.
Ø Applications in scheduling, power control, beam-forming and other problems.
Ø Applications in Statistical estimation and stochastic network optimization.