### OMA354 Syllabus - Linear Algebra - 2021 Regulation - Open Elective | Anna University

## OMA354 Syllabus - Linear Algebra - 2021 Regulation - Open Elective | Anna University

OMA354 |
LINEAR ALGEBRA |
L T P C |
---|

**3003**

**COURSE OBJECTIVES:**

• To test the consistency and solve system of linear equations.

• To find the basis and dimension of vector space.

• To obtain the matrix of linear transformation and its eigenvalues and eigenvectors.

• To find orthonormal basis of inner product space and find least square approximation.

• To find eigenvalues of a matrix using numerical techniques and perform matrix decomposition.

• To find the basis and dimension of vector space.

• To obtain the matrix of linear transformation and its eigenvalues and eigenvectors.

• To find orthonormal basis of inner product space and find least square approximation.

• To find eigenvalues of a matrix using numerical techniques and perform matrix decomposition.

UNIT I |
MATRICES AND SYSTEM OF LINEAR EQUATIONS |
9 |
---|

Matrices - Row echelon form - Rank - System of linear equations - Consistency - Gauss elimination method - Gauss Jordan method.

UNIT II |
VECTOR SPACES |
9 |
---|

Vector spaces over Real and Complex fields - Subspace – Linear space - Linear independence and dependence - Basis and dimension.

UNIT III |
LINEAR TRANSFORMATION |
9 |
---|

Linear transformation - Rank space and null space - Rank and nullity - Dimension theorem– Matrix representation of linear transformation - Eigenvalues and eigenvectors of linear transformation – Diagonalization.

UNIT IV |
INNER PRODUCT SPACES |
9 |
---|

Inner product and norms - Properties - Orthogonal, Orthonormal vectors - Gram Schmidt orthonormalization process - Least square approximation.

UNIT V |
EIGEN VALUE PROBLEMS AND MATRIX DECOMPOSITION |
9 |
---|

Eigen value Problems : Power method, Jacobi rotation method - Singular value decomposition – QR decomposition.

**TOTAL: 45 PERIODS**

**COURSE OUTCOMES: After the completion of the course the student will be able to**

1. Test the consistency and solve system of linear equations.

2. Find the basis and dimension of vector space.

3. Obtain the matrix of linear transformation and its eigenvalues and eigenvectors.

4. Find orthonormal basis of inner product space and find least square approximation.

5. Find eigenvalues of a matrix using numerical techniques and perform matrix decomposition.

2. Find the basis and dimension of vector space.

3. Obtain the matrix of linear transformation and its eigenvalues and eigenvectors.

4. Find orthonormal basis of inner product space and find least square approximation.

5. Find eigenvalues of a matrix using numerical techniques and perform matrix decomposition.

**TEXT BOOKS:**

1. Faires J.D. and Burden R., Numerical Methods, Brooks/Cole (Thomson Publications), New Delhi, 2002.

2. Friedberg A.H, Insel A.J. and Spence L, Linear Algebra, Pearson Education, 5th Edition,2019.

2. Friedberg A.H, Insel A.J. and Spence L, Linear Algebra, Pearson Education, 5th Edition,2019.

**REFERENCES:**

1. Bernard Kolman, David R. Hill, Introductory Linear Algebra, Pearson Educations, New Delhi, 8th Edition, 2009.

2. Gerald C.F. and Wheatley P.O, Applied Numerical Analysis, Pearson Educations, New Delhi, 7th Edition, 2007.

3. Kumaresan S, Linear Algebra - A geometric approach, Prentice Hall of India, New Delhi Reprint, 2010.

4. Richard Branson, Matrix Operations, Schaum's outline series, 1989.

5. Strang G, Linear Algebra and its applications, Thomson (Brooks / Cole) New Delhi, 4th Edition, 2005.

6. Sundarapandian V, Numerical Linear Algebra, Prentice Hall of India, New Delhi, 2014.

2. Gerald C.F. and Wheatley P.O, Applied Numerical Analysis, Pearson Educations, New Delhi, 7th Edition, 2007.

3. Kumaresan S, Linear Algebra - A geometric approach, Prentice Hall of India, New Delhi Reprint, 2010.

4. Richard Branson, Matrix Operations, Schaum's outline series, 1989.

5. Strang G, Linear Algebra and its applications, Thomson (Brooks / Cole) New Delhi, 4th Edition, 2005.

6. Sundarapandian V, Numerical Linear Algebra, Prentice Hall of India, New Delhi, 2014.

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