Lecture-by-lecture Outline, Spring 2019

  1. Chapter 1. Introduction, Errors, representing numbers in a computer. Numerical errors.
  2. Floating Point Arithmetic, machine precision, NaN, Inf, overflow, underflow
  3. Arithmetical operations in Floating Points. Chapter 2 Solving nonlinear equations, rate of convergence, Bisection method, fixed point iterations.
  4. Newton Method, rate of convergence.
  5. Stopping criteria, hybrid methods, overview. Secant Method 3 Chapter 3, Linear system of equations $ A x = b$. Existence and uniqueness of solutions.
  6. S19 Forward and Backward substitution, Gauss Elementary elimination matrices and LU decomposition. Partial and Complete pivoting.
  7. F24 Vector and Matrix norms. Condition number of a matrix. Properties of vector and matrix norms. Properties of condition numbers.
  8. F28 Absolute and relative residual. Error Estimates. Newton method for solving nonlinear system of equations.
  9. S29
  10. O3
  11. O6
  12. O11
  13. O13 Introduction to interpolation. Formulation of a problem, monomial interpolation.
  14. O17 Interpolation - Lagrange interpolation, wiggles, Piece wise linear interpolation.
  15. O20
  16. O24 Midterm
  17. O27
  18. O31
  19. N3
  20. N7
  21. N10
  22. N14
  23. N17
  24. N21 Midterm
  25. N28
  26. D1
  27. D5 Matlab Lab
  28. D8 concluding Remarks