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Department of MathematicscorelabSem 7

SCIENTIFIC COMPUTING LAB

MAT 3241

Syllabus

  • 01Basic of the MATLAB/Simulink programming, Live script, array, loop, function, plotting
  • 02Approximations and Error
  • 03Linear Algebraic Systems
  • 04Solution of linear systems – built-in methods; implementation of Gaussian elimination
  • 05Bases of column space and null space using RREF
  • 06Eigenvalues and Eigenvectors-Matrices
  • 07Curve fitting and Optimization and transportation planning
  • 08Linear and Nonlinear Equation
  • 09Regression and Interpolation
  • 10Multistep, Boundary Value Problems- of PDE
  • 11Finite Element Method
  • 12Introduction to SageMath using Jupyter Notebook
  • 13Linear algebra in SageMath. Matrix operations, eigenvalues, eigenspaces, characteristic and minimal polynomials, diagonalization. Matrices over different fields and rings; precision. Vector spaces, subspaces, bases. Matrix factorisations.
  • 14Statistical computing (R software), data accessing, and indexing, packages, Graphics in R, built in functions, saving, storing and retrieving work
  • 15Multivariate normal distributions, Principal component analysis, Factor analysis - 2 sessions, Multivariate regression, Discriminant analysis & Cluster analysis

References

  • Robert J. Schilling and Sandra L. Harries, Applied Numerical Methods for Engineers using MATLAB and C, Thomson Learning Inc., 2000.
  • Brian R Hunt, et al, Guide To Matlab: For Beginners and Experienced Users, (2e), Cambridge University Press, 2011.
  • Fausett L.V., Applied Numerical Analysis Using MATLAB, (2e)., Pearson Education, 2007.
  • MATLAB Programming Fundamentals. The MathWorks Inc. 2019.
  • B.R. Hunt, R.L. Lipsman, J.M. Rosenburg. A Guide to MATLAB. Cambridge University Press. 2001.
  • Sage Reference Manual (Release 8.9). SageMath. 2019.
Credits Structure
0Lecture
0Tutorial
6Practical
2Total
MIT Manipal Courses