Some articles that might be interesting or useful, mostly later on in the course. Optimal wire and transistor sizing for circuits with non-tree topology Optimal allocation of local feedback in multistage amplifiers via geometric programming Optimization of inductor circuits via geometric programming. Antenna array pattern synthesis via convex optimization. Some good books that can serve as secondary reference texts are D. Bertsekas, Nonlinear Programming , Athena Scientific D. Luenberger, Linear and Nonlinear Programming , Addison-Wesley. J. Nocedal and S. Wright, Numerical Optimization , Springer.
Course requirements weekly homework assignments.
Most homeworks will involve Matlab programming. Course description Basic graduate course in nonlinear programming, with emphasis on convex problems. Convex optimization problems arise frequently in engineering but often go unrecognized. This course concentrates on the latter advantage, i.e., our ability to solve such problems efficiently by computer. Approximate syllabus Introduction.