Applied Linear Algebra

Applied Linear Algebra

NPTEL-NOC IITM via YouTube Direct link

Polynomials and Roots

19 of 48

19 of 48

Polynomials and Roots

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Classroom Contents

Applied Linear Algebra

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  1. 1 Applied Linear Algebra _ Course Introduction
  2. 2 Vector Spaces: Introduction
  3. 3 Linear Combinations and Span
  4. 4 Subspaces, Linear Dependence and Independence
  5. 5 Basis and Dimension
  6. 6 Sums, Direct Sums and Gaussian Elimination
  7. 7 Linear Maps and Matrices
  8. 8 Null space, Range, Fundamental theorem of linear maps
  9. 9 Column space, null space and rank of a matrix
  10. 10 Algebraic operations on linear maps
  11. 11 Invertible maps, Isomorphism, Operators
  12. 12 Solving Linear Equations
  13. 13 Elementary Row Operations
  14. 14 Translates of a subspace, Quotient Spaces
  15. 15 Row space and rank of a matrix
  16. 16 Determinants
  17. 17 Coordinates and linear maps under a change of basis
  18. 18 Simplifying matrices of linear maps by choice of basis
  19. 19 Polynomials and Roots
  20. 20 Invariant subspaces, Eigenvalues, Eigenvectors
  21. 21 More on Eigenvalues, Eigenvectors, Diagonalization
  22. 22 Eigenvalues, Eigenvectors and Upper Triangularization
  23. 23 Properties of Eigenvalues
  24. 24 Linear state space equations and system stability
  25. 25 Discrete-time Linear Systems and Discrete Fourier Transforms
  26. 26 Sequences and counting paths in graphs
  27. 27 PageRank Algorithm
  28. 28 Dot product and length in Cn, Inner product and norm in V over F
  29. 29 Orthonormal basis and Gram-Schmidt orthogonalisation
  30. 30 Linear Functionals, Orthogonal Complements
  31. 31 Orthogonal Projection
  32. 32 Projection and distance from a subspace
  33. 33 Linear equations, Least squares solutions and Linear regression
  34. 34 Minimum Mean Squared Error Estimation
  35. 35 Adjoint of a linear map
  36. 36 Properties of Adjoint of a Linear Map
  37. 37 Adjoint of an Operator and Operator-Adjoint Product
  38. 38 Self-adjoint Operator
  39. 39 Normal Operators
  40. 40 Complex Spectral Theorem
  41. 41 Real Spectral Theorem
  42. 42 Positive Operators
  43. 43 Quadratic Forms, Matrix Norms and Optimization
  44. 44 Isometries
  45. 45 Classification of Operators
  46. 46 Singular Values and Vectors of a Linear Map
  47. 47 Singular Value Decomposition
  48. 48 Polar decomposition and some applications of SVD

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