Lecture videos, homeworks and projects will be distributed through the online learning web site. In addition to these, two 1-hour sessions are scheduled for recitation and/or quiz per week. Each student must attend one of these two sessions every week.
Numerical computation and optimization is an important tool to solve many practical engineering problems. The goal of this course is to teach a number of commonly-used algorithms (e.g., linear/nonlinear solver, matrix computation, nonlinear optimization, Monte Carlo simulation, etc.) and, most importantly, how they can be used to solve practical problems related to electrical and computer engineering. This course will help to develop the mathematical skills to build customized tools, as well as the background required to use commercial solvers.
At the end of this course, students should know the basic algorithms and methodologies for numerical computation and optimization, and implement prototype solvers in MATLAB for these problems. This goal will be achieved by a combination of learning through lectures, homeworks, exams, and importantly, learning to implement numerical algorithms via selected projects. Students will be required to write MATLAB code for computation and optimization tasks. Grades will be based on project results and reports, homeworks, and exams.
Prerequisites: 18-202, 21-241, 36-217