EC877 Inverse Problems: Theory & Applications

Course Name: 

EC877 Inverse Problems: Theory & Applications

Programme: 

M.Tech(SPML)

Category: 

Elective (Ele)

Credits (L-T-P): 

(3-0-2) 4

Content: 

Introduction and Basic Concepts: Ill-Posedness in inverse Problems, linear inverse problems, Classical Regularization Methods, Tikhonov Regularization, SVD, Projection Methods, Inverse Eigenvalue Problems, Besov space regularization, Inverse Scattering Problem, Variational Regularization Methods, Convex Regularization, Nonconvex Regularization, Statistical Inversion Theory, Nonlinear inverse problems, Inverse problems in imaging modalities and radar, applications in remote sensing, geoscience, biomedical, Computational inverse problems.

References: 

Jennifer L. Muller, Samuli Siltanen, Linear and nonlinear inverse problems with practical applications-Society for Industrial and Applied Mathematics 2012.
Per Christian Hansen, Discrete Inverse Problems; Insight and Algorithms, Society for Industrial and .4pplied Mathematics 2010.
Aster, Richard C. Borchers, Brian Thurber, Clifford H, Parameter estimation and inverse problem, Elsevier 2019.
J. C. Santamarina, Dante Fratta, Discrete signals and inverse problems: an introduction for engineers and scientists, Wiley 2005

Department: 

Electronics and Communication Engineering(ECE)
 

Contact us

Prof. Ramesh Kini M.
Professor and Head,
Department of ECE, NITK, Surathkal,
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

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