ECS130, Scientific Computation (Numerical Algorithms)

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ECS130, Scientific Computation (Numerical Algorithms)

Software:

• MATLAB
  • Numerical Computing with MATLAB (revised reprint) by C. Moler, SIAM, 2008
    Electronic Edition
    
  • MATLAB for Student
  • Interactive MATLAB Tutorial
  • New: 2-hour MATLAB onramp
• Julia
  • The Julia programming language

• From biological modeling, to physical simulation, to graphics and image (data) processing, to data mining and social network analysis, the need for accurate and fast numerical algorithms is expanding. With problems of very large size and under the limitations of finite precision arithmetic, the design of practical algorithms becomes a challenging task. Numerical algorithms (scientific computation) is the broad field concerned with the design and analysis of efficient numerical algorithms. In this course, we will learn basic ideas and fundamental numerical algorithms in scientific computing. You can ``play'' with the mathematics that stands behind each and every new method that you learn, use graphics to appreciate convergence and error, use matrix-vector programming language to solidify the understanding of linear algebra and to prepare for advanced array-level computing.

1. Mathematics review
2. Numerics and error analysis
3. Linear algebra: linear systems, eigenvalues and eigenvectors, singular value decomposition
4. Nonlinear techniques: nonlinear systems, optimization
5. Function approximations, derivatives and integrals.

• Homework: 50%
• Exam/Project: 50%
• Homework box is located in Room 2131, Kemper Hall

• Annoucements, handouts and homework assignments will be posted at this course site. It gets updated frequently throughout the quarter.
• canvas site