Optimization and Systems Theory Seminar
Thursday, June 24, 1999, 14.00-15.00, Room 3721, Lindstedtsv. 25

Professor Stephen P. Boyd
Department of Electrical Engineering
Stanford University
Stanford, CA 94305-9510
E-mail: boyd@stanford.edu

Optimization over linear matrix inequalities

The recent development of efficient interior-point algorithms for convex optimization problems involving linear matrix inequalities (LMIs) has spurred research in a wide variety of application fields, including control system analysis and synthesis, combinatorial optimization, circuit design, structural optimization, experiment design, and geometrical problems involving ellipsoidal bounding and approximation.

In the first part of the talk, I will describe the basic problems, semidefinite programming (SDP) and determinant maximization, discuss their basic properties, and give a brief description of interior-point methods for their solution. In the second half of the talk I will survey applications from several areas.

Calendar of seminars
Last update: June 17, 1999 by Anders Forsgren, anders.forsgren@math.kth.se.