Course Description
This course offers an advanced introduction to numerical analysis, with a focus on accuracy and efficiency of numerical algorithms. Topics include sparse-matrix/iterative and dense-matrix algorithms in numerical linear algebra (for linear systems and eigenproblems), floating-point arithmetic, backwards error analysis, …
This course offers an advanced introduction to numerical analysis, with a focus on accuracy and efficiency of numerical algorithms. Topics include sparse-matrix/iterative and dense-matrix algorithms in numerical linear algebra (for linear systems and eigenproblems), floating-point arithmetic, backwards error analysis, conditioning, and stability. Other computational topics (e.g., numerical integration or nonlinear optimization) are also surveyed.
Course Info
Learning Resource Types
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Problem Sets with Solutions
grading
Exams with Solutions
notes
Lecture Notes
![A six-petal symmetric graph.](/courses/18-335j-introduction-to-numerical-methods-spring-2019/d063f5d67a2a7d5a22b5a9e88e6a95be_18-335js19.jpg)
A Newton fractal showing the basins of attraction for Newton iterations for 6th-roots of unity from different starting points in the complex plane. (Image by Prof. Steven G. Johnson.)