Computer Science 323
Numerical Analysis and Computing
SPRING 2012
Course web page: http://www.cs.rutgers.edu/~richter/cs323
Instructor:
Gerard Richter
(richter@cs.rutgers.edu, 732-445-2001 x2097)
314 Core Building
office hrs: Monday 1:30-2:30 pm, Thursday 1:30-2:30 pm, or by appointment
Teaching assistant:
Zhennan Yan
(zhennany@cs.rutgers.edu, 732-445-2001 x9785)
Hill 405
office hours: Tuesday 2-3 pm, or by arrangement
...recitation starts SECOND week of classes
Text: (recommended, but not required)
K. Atkinson & W. Han, Elementary Numerical Analysis, 3rd edition, Wiley
on reserve in SERC reading room
Prerequisites: CALC1, CALC2, Math 250 (linear algebra),
ability to program in a high level language
Programs will be written in MATLAB language -
Matlab tutorial + links to other references
Grading:
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written homework, computer programs ~ 20-25%
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midterm ~ 30%
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final exam ~ 45%
Objectives: derivation, analysis, implementation of
algorithms for numerical problems
Outline of topics...
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Floating point numbers and roundoff error (Chap. 1-2 of text)
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Solution of nonlinear algebraic equations (Chap. 3)
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bisection method, fixed point iteration, secant method, Newton's
method
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linear and quadratic convergence
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roots of polynomials
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Solution of linear algebraic systems (Chap. 6)
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Gaussian elimination, partial pivoting
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matrix inversion
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LU decomposition
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error analysis
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iterative methods
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PageRank
- Least squares approximation (Chap. 7.1)
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Polynomial interpolation (Chap. 4)
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Lagrange and Newton forms of interpolating polynomial
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error term
- interpolation of derivatives
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piecewise polynomial interpolation, splines
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Numerical differentiation and integration (Chap. 5)
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derivation of quadrature formulas and their error terms
- composite formulas
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adaptive quadrature
- Gaussian quadrature
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derivation of numerical differentiation formulas, error terms
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Numerical solution of ordinary differential equations (Chap. 8)
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introduction to ordinary differential equations
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basic numerical methods, e.g., Euler's method
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higher order equations, systems