EC763 Optimization

Course Name: 

EC763 Optimization

Programme: 

M.Tech(SPML)

Semester: 

Second

Category: 

Programme Core (PC)

Credits (L-T-P): 

(4-0-0) 4

Content: 

Convex sets and Convex functions, Level sets and Gradients. Unconstrained Optimization: Search methods, Gradients Methods, Newton Method, Conjugate Direction Methods, Quasi-Newton Methods. Linear Programming: Standard Form Linear Programs, Simplex method, Duality and Non Simplex Methods. Nonlinear Constrained Optimization: Problems with equality constraints, Problems with Inequality Constraints, Convex Optimization Problems. Algorithms for Constrained Optimization: Projected Gradient Methods and Penalty Methods.

References: 

Lieven Vandenberghe and Stephen P. Boyd, Convex Optimization, Cambridge University Press, 2004.
Dimitris Bertsekas, John N. Tsitsiklis, Introduction to Linear Optimization, Athena Scientific Series, 1997.
Aharon Ben-Tal and Arkadi Nemirovski, Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering Applications, SIAM, 2001.

Department: 

Electronics and Communication Engineering(ECE)
 

Contact us

Dr. T. Laxminidhi,  Professor and Head, 
Department of E&C, NITK, Surathkal
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

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