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1Lecture 01: Introduction to Matrix Algebra - IDownload
2Lecture 02: Introduction to Matrix Algebra - IIDownload
3Lecture 03: System of Linear Equations Download
5Lecture 05: Determinant of a Matrix (Contd.)Download
10Lecture 10: Representation of Physical Systems as Matrix EquationsDownload
15Lecture 15: Column Space and Nullspace of a MatrixDownload
16Lecture 16 : Finding Null Space of a MatrixDownload
17Lecture 17 : Solving Ax=b when A is SingularDownload
18Lecture 18 : Linear Independence and Spanning of a SubspaceDownload
19Lecture 19 : Basis and Dimension of a Vector SpaceDownload
20Lecture 20 : Four Fundamental Subspaces of a MatrixDownload
21Lecture 21: Left and right inverse of a matrixDownload
22Lecture 22 : Orthogonality between the subspacesDownload
24Lecture 24 : Projection operation and linear transformationDownload
25Lecture 25 : Creating orthogonal basis vectorsDownload
26Lecture 26: Gram-Schmidt and modified Gram-Schmidt algorithmsDownload
27Lecture 27: Comparing GS and modified GSDownload
28Lecture 28: Introduction to eigenvalues and eigenvectorsDownload
29Lecture 29: Eigenvlues and eigenvectors for real symmetric matrixDownload
30Lecture 30: Positive definiteness of a matrixDownload
31Lecture 31 : Positive definiteness of a matrix (Contd.)Download
32Lecture 32 : Basic Iterative Methods: Jacobi and Gauss-SiedelDownload
33Lecture 33 : Basic Iterative Methods: Matrix RepresentationDownload
34Lecture 34 : Convergence Rate and Convergence Factor for Iterative MethodsDownload
35Lecture 35 : Numerical Experiments on ConvergenceDownload
36Lecture 36 : Steepest Descent Method: Finding Minima of a FunctionalDownload
38Lecture 38 : Steepest Descent Method: Algorithm and ConvergenceDownload
39Lecture 39 : Introduction to General Projection MethodsDownload
40Lecture 40 : Residue Norm and Minimum Residual AlgorithmDownload
41Lecture 41 : Developing computer programs for basic iterative methodsDownload
42Lecture 42 : Developing computer programs for projection based methodsDownload
43Lecture 43 : Introduction to Krylov subspace methodsDownload
44Lecture 44 : Krylov subspace methods for linear systemsDownload
45Lecture 45 : Iterative methods for solving linear systems using Krylov subspace methodsDownload
48Lecture 48 : Conjugate gradient methods(Contd.) and Introduction to GMRESDownload
50Lecture 50 : Lanczos Biorthogonalization and BCG AlgorithmDownload
51Lecture 51 : Numerical issues in BICG and polynomial based formulationDownload
55Lecture 55 : Domain Decomposition and Parallel ComputingDownload

Sl.No Chapter Name English
1Lecture 01: Introduction to Matrix Algebra - IPDF unavailable
2Lecture 02: Introduction to Matrix Algebra - IIPDF unavailable
3Lecture 03: System of Linear Equations PDF unavailable
4Lecture 04: Determinant of a MatrixPDF unavailable
5Lecture 05: Determinant of a Matrix (Contd.)PDF unavailable
6Lecture 06: Gauss Elimination PDF unavailable
7Lecture 07: Gauss Elimination(Contd.)PDF unavailable
8Lecture 08: LU DecompositionPDF unavailable
9Lecture 09: Gauss-Jordon MethodPDF unavailable
10Lecture 10: Representation of Physical Systems as Matrix EquationsPDF unavailable
11Lecture 11: Tridiagonal Matrix AlgorithmPDF unavailable
12Lecture 12: Equations with Singular MatricesPDF unavailable
13Lecture 13: Introduction to Vector SpacePDF unavailable
14Lecture 14: Vector SubspacePDF unavailable
15Lecture 15: Column Space and Nullspace of a MatrixPDF unavailable
16Lecture 16 : Finding Null Space of a MatrixPDF unavailable
17Lecture 17 : Solving Ax=b when A is SingularPDF unavailable
18Lecture 18 : Linear Independence and Spanning of a SubspacePDF unavailable
19Lecture 19 : Basis and Dimension of a Vector SpacePDF unavailable
20Lecture 20 : Four Fundamental Subspaces of a MatrixPDF unavailable
21Lecture 21: Left and right inverse of a matrixPDF unavailable
22Lecture 22 : Orthogonality between the subspacesPDF unavailable
23Lecture 23 : Best estimatePDF unavailable
24Lecture 24 : Projection operation and linear transformationPDF unavailable
25Lecture 25 : Creating orthogonal basis vectorsPDF unavailable
26Lecture 26: Gram-Schmidt and modified Gram-Schmidt algorithmsPDF unavailable
27Lecture 27: Comparing GS and modified GSPDF unavailable
28Lecture 28: Introduction to eigenvalues and eigenvectorsPDF unavailable
29Lecture 29: Eigenvlues and eigenvectors for real symmetric matrixPDF unavailable
30Lecture 30: Positive definiteness of a matrixPDF unavailable
31Lecture 31 : Positive definiteness of a matrix (Contd.)PDF unavailable
32Lecture 32 : Basic Iterative Methods: Jacobi and Gauss-SiedelPDF unavailable
33Lecture 33 : Basic Iterative Methods: Matrix RepresentationPDF unavailable
34Lecture 34 : Convergence Rate and Convergence Factor for Iterative MethodsPDF unavailable
35Lecture 35 : Numerical Experiments on ConvergencePDF unavailable
36Lecture 36 : Steepest Descent Method: Finding Minima of a FunctionalPDF unavailable
37Lecture 37 : Steepest Descent Method: Gradient SearchPDF unavailable
38Lecture 38 : Steepest Descent Method: Algorithm and ConvergencePDF unavailable
39Lecture 39 : Introduction to General Projection MethodsPDF unavailable
40Lecture 40 : Residue Norm and Minimum Residual AlgorithmPDF unavailable
41Lecture 41 : Developing computer programs for basic iterative methodsPDF unavailable
42Lecture 42 : Developing computer programs for projection based methodsPDF unavailable
43Lecture 43 : Introduction to Krylov subspace methodsPDF unavailable
44Lecture 44 : Krylov subspace methods for linear systemsPDF unavailable
45Lecture 45 : Iterative methods for solving linear systems using Krylov subspace methodsPDF unavailable
46Lecture 46 : Conjugate gradient methodsPDF unavailable
47Lecture 47 : Conjugate gradient methods(Contd.)PDF unavailable
48Lecture 48 : Conjugate gradient methods(Contd.) and Introduction to GMRESPDF unavailable
49Lecture 49 : GMRES (Contd.)PDF unavailable
50Lecture 50 : Lanczos Biorthogonalization and BCG AlgorithmPDF unavailable
51Lecture 51 : Numerical issues in BICG and polynomial based formulationPDF unavailable
52Lecture 52 : Conjugate gradient squared and Biconjugate gradient stabilizedPDF unavailable
53Lecture 53 : Line relaxation methodPDF unavailable
54Lecture 54 : Block relaxation methodPDF unavailable
55Lecture 55 : Domain Decomposition and Parallel ComputingPDF unavailable
56Lecture 56: PreconditionersPDF unavailable
57Lecture 57: Preconditioned conjugate gradientPDF unavailable
58Lecture 58: Preconditioned GMRESPDF unavailable
59Lecture 59: Multigrid methods IPDF unavailable
60Lecture 60: Multigrid methods IIPDF unavailable

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1EnglishNot Available
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available