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Detailed syllabus for Semester II  B E (First Year)     MATHEMATICS II Detailed syllabus for Semester II  B E (First Year)     MATHEMATICS II

Detailed syllabus for Semester II B E (First Year) MATHEMATICS II - PDF document

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Detailed syllabus for Semester II B E (First Year) MATHEMATICS II - PPT Presentation

Topics 1 Vectors in IProperties of IIDot product Norm and Distance properties in IIIPythagorean theorem in 2 Vector spaces IDefinition Examples IIVector Subspaces of IIILinear Indepen ID: 120101

Topics Vectors I.Properties

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Detailed syllabus for Semester II B E (First Year) MATHEMATICS II Sr.No. Topics 1 Vectors in I.Properties of II.Dot product, Norm and Distance properties in III.Pythagorean theorem in 2 Vector spaces I.Definition & Examples II.Vector Subspaces of III.Linear Independence and dependence IV.Linear Span of set of vectors V.Basis of subspaces , Extension to Basis 3 System of linear equations I.Matrices a.Definition and Algebra of matrices b.Types of Matrices II. Methods to solve System of linear equations a. Gaussian Elimination (Row echelon form) b. Gauss-Jordan method (Reduced row echelon form). c. Inverse of matrices (i)By Gauss-Jordan method (ii)By Determinant method d. Rank of Matrix (iii)By Row Echelon form (iv)In terms of Determinant (v)By row space and column space 4 Linear Transformations I.Definition and Basic properties II.Types of Linear Transformations (Rotation, reflection, expansion, contraction, shear, projection) III.Matrix of Linear transformations IV.Change of Basis and similarity V. Rank Nullity Theorem ( Dimension Theorem ) 5 Inner Product Spaces I.Definition and properties II.Angle and orthogonal basis, Orthogonormality of basis III.Gram Schmidt’s Orthogonalisation process IV.Projections theorem V.Least squares approximations ( linear system ) 6 Eigen values and Eigen vectors I.a.Definition b.Characteristic Polynomials II.Eigen values of Orthogonal , symmetric, skew symmetric, Hermitian , skew Hermitian, unitary, normal matrix III. Algebraic and geometric multiplicity IV.Diagonalisation by similarity transformation V.Spectral theorem for real symmetric matrices VI.Application to Quadratic forms Reference books: 1)H. Anton, Elementary linear algebra with applications-(9 th Edition), Wiley-India.(2008) 2)G. Strang, Linear Algebra and its applications (4 th Edition), Thomson.(2006) 3)E. Kreyszig, Advanced Engineering mathematics(8 th Edition), Wiley-India.(1999) 4)S. Kumaresan, Linear Algebra – A Geometric approach , Prentice Hall India (2006) Remark: All Results and Theorems are without proof