Numerical Analysis I

AMSC/CMSC 666, Fall 2020


Course Information

Lecture TuTh 2-3:15pm ONLINE (*)
InstructorProfessor Eitan Tadmor
Contacttel.: x5-0648   e-mail:
Office HoursBy appointment (e-mail: )
Teaching Assistant Jingcheng Lu e-mail:
Final Saturday December 19, 10:30am-12:30pm ONLINE (*)
Grading40% Homework; 60% Final

 (*) Students are expected to have an online cameras on.
      Additional notes on online class format are found here.  

Course Description

  1. Approximation Theory.

    1. General overview. Least-squares vs. the uniform norm
    2. • Lecture notes: [ the least-squares problem ]
    3. Orthogonal polynomials
    4. • Lecture notes: [ Orthogonal polynomials ]
    5. Least squares I. Fourier expansions.
    6. • Lecture notes: [ Least Squares as truncated Fourier expansion ]
      • Assignment [ #1 ] ... with [ answers]
    7. Least squares II -- the finite-dimensional case. QR, SVD, PCA (LS rank approximations)
    8. • Lecture notes: [ SVD ] (with additional notes on QR factorization )
      • Additional reading:
      ► Gilbert Strang [on SVD] (and also here)

      ► Lijie Cao [SVD applied to digital image processing]
      • Assignment [ #2 ] with answers [ pdf file]
    9. Gauss quadrature
    10. • Lecture notes: [Gauss quadrature] (with additional notes on Hermite Interpolation )
  2. Numerical Solution of ODEs: Initial-Value Problems

    1. Preliminaies. Stability of Systems of ODEs.
    2. • Lecture notes: [ Stability of Systems of ODEs ]
      Assignment [ #3 ] with answers [ pdf file]
    3. Examples of basic numerical methods: Euler's method, Leap-Frog, Milne.
    4. • Lecture notes: [ Examples of basic numerical methods ]
      Assignment [ #4 ] with answers [ pdf file] -
    5. Consistency and stability imply convergence
    6. • Lecture notes: [ Accuracy, stability and convergence ]
      Assignment [ #5 ]
      Assignment [ #6 ]
    7. Runge-Kutta methods
      • Local time stepping and error estimates. RK4 and RKF5.
      • Stability and convergence of Runge-Kutta methods
    8. Strong-Stability Preserving (SSP) schemes. Methods for stiff equations
  3. Iterative Methods for Solving Systems of Linear Equations

    1. General overview. Boundary-value problems. Stiff systems.
    2. Classical methods: Jacobi, Gauss-Seidel, SOR, ...
    3. Energy functionals and gradient methods
      • Steepest descent. Conjugate gradient. ADI and dimensional splitting.
    4. Non-stationary methods. Local vs. global methods
    5. Pre-conditioners
    6. Multigrid mthods*; GMRES*
  4. Numerical Optimization

    1. General overview. Fixed point iterations, low-order and Newton's methods
    2. Steepest descent
    3. Line search methods. Trust regions and Wolfe conditions
    4. Newton's and quasi-Newton methods: Rank one/two modifications
    5. Rates of convergence
    6. Nonlinear Least-sqaures. Conjugate gradient, Gauss-Newton.



    References

    GENERAL TEXTBOOKS

    W. Gautschi, NUMERICAL ANALYSIS, Birkhauser, 2012

    K. Atkinson, An INTRODUCTION to NUMERICAL ANALYSIS, Wiley, 1987

    S. Conte & C. deBoor, ELEMENTARY NUMERICAL ANALYSIS, McGraw-Hill
    User friendly; Shows how 'it' works; Proofs, exercises and notes

    G. Dahlquist & A. Bjorck, NUMERICAL METHODS, Prentice-Hall,
    User friendly; Shows how 'it' works; Exercises

    A. Ralston & P. Rabinowitz, FIRST COURSE in NUMERICAL ANALYSIS, 2nd ed., McGraw-hill,
    Detailed; Scholarly written; Comprehensive; Proofs exercises and notes

    J. Stoer & R. Bulrisch, INTRODUCTION TO NUMERICAL ANALYSIS, 2nd ed., Springer
    detailed account on approximation, linear solvers & eigen-solvers, ODE solvers,..

    APPROXIMATION THEORY

    E. W. Cheney, INTRODUCTION TO APPROXIMATION THEORY
    Classical

    P. Davis, INTERPOLATION & APPROXIMATION, Dover
    Very readable

    T. Rivlin, AN INTRODUCTION to the APPROXIMATION of FUNCTIONS
    Classical

    R. DeVore & G. Lorentz, CONSTRUCTIVE APPROXIMATION, Springer
    A detailed account from classical theory to the modern theory; everything; Proofs exercises and notes

    NUMERICAL INTEGRATION

    F. Davis & P. Rabinowitz, NUMERICAL INTEGRATION,
    Everything...

    NUMERICAL SOLUTION Of INITIAL-VALUE PROBLEMS

    E. Hairer, S.P. Norsett and G. Wanner, SOLVING ODEs I: NONSTIFF PROBLEMS, Springer-Verlag, Berlin. 1991, (2nd ed)
    Everything - the modern version

    A. Iserles, A FIRST COURSE in the NUMERICAL ANALYSIS of DEs, Cambridge Texts

    W. Gear, NUMERICAAL INITIAL VALUE PROBLEMS in ODEs, 1971
    The classical reference on theory and applications

    Lambert, COMPUTATIONAL METHODS for ODEs, 1991
    Detailed discussion of ideas and practical implementation

    Shampine and Gordon, COMPUTER SOLUTION of ODES, 1975
    Adams methods and practial implementation of ODE "black box" solvers

    Butcher, NUMERICAL ANALYSIS of ODEs, 1987
    Comprehensive discussion on Runge-Kutta methods

    (mainly) ITERATIVE SOLUTION OF LINEAR SYSTEMS

    A. Householder, THE THEORY OF MATRICES IN NUMERICAL ANALYSIS
    The theoretical part by one of the grand masters; Outdated in some aspects

    G. H. Golub & Van Loan, MATRIX COMPUTATIONS,
    The basic modern reference

    Y. Saad, ITERATIVE METHODS for SPARSE LINEAR SYSTEMS,
    PWS Publishing, 1996. (Available on line at http://www-users.cs.umn.edu/~saad/books.html)

    R. Varga, MATRIX ITERATIVE ANALYSIS,
    Classical reference for the theory of iterations

    James Demmel, APPLIED NUMERICAL LINEAR ALGEBRA,
    SIAM, 1997

    Kelley, C. T., ITERATIVE METHODS for LINEAR and NONLINEAR EQUATIONS,
    SIAM 1995

    NUMERICAL OPTMIZATION

    J. Nocedal, S. Wright, NUMERICAL OPTIMIZATION
    Springer, 1999

    T. Kelly, ITERATIVE METHODS for OPTIMIZATION
    SIAM
    Eitan Tadmor