Computational Linear Algebra(CMA703)

Course Name: 

Computational Linear Algebra


M.Tech (CMA)




Programme Core (PC)

Credits (L-T-P): 



Matrix multiplication problems: Basic algorithms and notations, exploiting structure, block matrices and algorithms, vectorization and re-use issues. Matrix analysis: basic ideas from linear algebra, vector norms, matrix norms, finite precision matrix computations, orthogonality and SVD, projections and the CS decomposition, the sensitivity of square linear systems. General linear systems: Triangular systems, the LU factorization, roundoff analysis of Gaussian elimination, pivoting, improving and estimating accuracy. Special linear systems,factorizations,positive definite systems,banded systems,symmetric indefinite systems,block systems,vander monde systems and the FFT,Toeplitz and relatedsystems.


Gene H. Golub nad Charles F. Van Loan, Matrix Computations, Third Ed, Hindustan book agency, 2007.
A.R. Gourlay and G.A. Watson, Computational methods for matrix eigenproblems, John Wiley & Sons, New York, 1973.
W.W. Hager, Applied numerical algebra, Prentice-Hall, Englewood Cliffs, N.J, 1988.
D.S. Watkins, Fundamentals of matrix computations, John Wiley and sons, N.Y, 1991.
C.F. Van Loan, Introduction to scientific computing: A Matrix vector approach using Mathlab, Prentice -Hall, Upper Saddle River, N.J, 1997.


Mathematical and Computational Sciences

Contact us

Shyam S Kamath, Professor and Head
Department of MACS, NITK, Surathkal
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.

  • Hot line: +91-0824-2474048

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