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Introduction to Linear Algebra for Science and Engineering, 3rd Edition By Daniel Norman, Dan Wolczuk | eBook [PDF]

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Introduction to Linear Algebra for Science and Engineering, 3rd Edition By Daniel Norman, Dan Wolczuk | eBook [PDF] Title Page Copyright Page Table of Contents A Note to Students A Note to Instr... uctors A Personal Note Acknowledgments Chapter 1: Euclidean Vector Spaces 1.1. Vectors in R2 and R3 1.2. Spanning and Linear Independence in R2 and R3 1.3. Length and Angles in R2 and R3 1.4. Vectors in Rn 1.5. Dot Products and Projections in Rn Chapter Review Chapter 2: Systems of Linear Equations 2.1. Systems of Linear Equations and Elimination 2.2. Reduced Row Echelon Form, Rank, and Homogeneous Systems 2.3. Application to Spanning and Linear Independence 2.4. Applications of Systems of Linear Equations Chapter Review Chapter 3: Matrices, LinearMappings, and Inverses 3.1. Operations onMatrices 3.2. MatrixMappings and LinearMappings 3.3. Geometrical Transformations 3.4. Special Subspaces 3.5. InverseMatrices and InverseMappings 3.6. ElementaryMatrices 3.7. LU-Decomposition Chapter Review Chapter 4: Vector Spaces 4.1. Spaces of Polynomials 4.2. Vector Spaces 4.3. Bases and Dimensions 4.4. Coordinates 4.5. General LinearMappings 4.6. Matrix of a LinearMapping 4.7. Isomorphisms of Vector Spaces Chapter Review Chapter 5: Determinants 5.1. Determinants in Terms of Cofactors 5.2. Properties of the Determinant 5.3. Inverse by Cofactors, Cramer’s Rule 5.4. Area, Volume, and the Determinant Chapter Review Chapter 6: Eigenvectors and Diagonalization 6.1. Eigenvalues and Eigenvectors 6.2. Diagonalization 6.3. Applications of Diagonalization Chapter Review Chapter 7: Inner Products and Projections 7.1. Orthogonal Bases in Rn 7.2. Projections and the Gram-Schmidt Procedure 7.3. Method of Least Squares 7.4. Inner Product Spaces 7.5. Fourier Series Chapter Review Chapter 8: SymmetricMatrices and Quadratic Forms 8.1. Diagonalization of SymmetricMatrices 8.2. Quadratic Forms 8.3. Graphs of Quadratic Forms 8.4. Applications of Quadratic Forms 8.5. Singular Value Decomposition Chapter Review Chapter 9: Complex Vector Spaces 9.1. Complex Numbers 9.2. Systems with Complex Numbers 9.3. Complex Vector Spaces 9.4. Complex Diagonalization 9.5. Unitary Diagonalization Chapter Review Appendix A: Answers toMid-Section Exercises Appendix B: Answers to Practice Problems and Chapter Quizzes Index [Show More]

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