EC458 Mathematical Algorithms for Signal Processing

Course Name: 

EC458 Mathematical Algorithms for Signal Processing

Programme: 

B.Tech (ECE)

Category: 

Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-1-0) 4

Content: 

Mathematical Foundations – mathematical models, random variables and random processes, markov and hidden markov models. Represenations and approximations - orthogonality, least squares, MMSE filtering, frequency domain optimal filtering, minimum norm solutions, Iterated reweighted least squares. Linear Operators – Operator norms, adjoint and transposes, geometry of linear equations, least squares and pseudo inverses, applications to linear models. Subspace methods – Eigen decomposition, KL transform and low rank approximation, Eigen filters, signal subspace techniques – MUSIC, ESPRIT. SVD – matrix structure, pseudo inverse and SVD, system identification using SVD, Total least squares, partial total least squares. Special matrices – Toeplitz matrices, optimal predictors and lattice filters, circulant matrices, properties.

References: 

Todd Moon and WC Stirling, Mathematical Methods and Algorithms for Signal Processing, Pearson Education, 2000
Steven, M. Kay, Modern spectral estimation: theory and application, Prentice Hall, 1988.
 

Contact us

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

  • Hot line: +91-0824-2473046

Connect with us

We're on Social Networks. Follow us & get in touch.