The repositiry is for numerical analysis learning, containing the source code for all the algorithms would be learned in this course. To make it easier to use, here's the construction of the files:
- ${ALGORITHM_NAME}.m: the implement for each alogorithm. They would be sealed into a function. For more information, go into each directory and read the README file within.
- example.mlx: Live script for experiments. Details will be introduced in the code comments. You can also create your own file to do experiments.
Detailed information is provided in the README under each experimental directory. Read them carefully to help you think when doing the experiments.
Experiment 1 Linear Equations Solving
Experiment 2 Non-linear Equations Solving
Experiment 3 Eigenvalue Calculation
Experiment 4 Interpolation
Experiment 5 Function Approximation
Experiment 6 Numerical Integration
Experiment 7 ODE Numerical Solution
Thanks to Professor Zhongyi Huang from Department of Mathematical Sciences, Tsinghua University, our lecturer for Engineering and Scientific Computing Course. His course with large capacity provided us with many practical algorithms and deeper understanding about its usage, and the most importantly, pros and cons, which helped us to decide which algorithm to use in real situations.
I also appreciate some bloggers from CSDN and Zhihu, their source code provided me with inspiration when I encountered difficulties.