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{"name":"MATLAB-Sp15","tagline":"CSE Training Workshops in MATLAB, Spring 2015","body":"[](http://cse.illinois.edu/)\r\n<script src='https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></script>\r\n\r\nAll workshops will be held in the EWS computer laboratory, 1001 Mechanical Engineering Laboratory. There is no sign-up for this series—walk-ins are welcome and encouraged!\r\n\r\n# [Introduction to MATLAB](#intro)\r\n### Feb. 2, 1:00 pm\r\n\r\nWe will conduct a hands-on walkthrough of what MATLAB has to offer as a foundation for later tutorials throughout the semester. We will cover the following topics:\r\n\r\n- Variables, functions, sequences, dictionaries\r\n- Libraries and modules\r\n- Loops, logic, and conditionals\r\n- Input/output, files\r\n- Basic numerical examples & matrix solutions\r\n\r\n### Lesson Materials\r\n\r\n\r\n\r\n\r\n\r\n[Basic Exercises](https://github.com/uiuc-cse/matlab-fa14/blob/gh-pages/lessons/exercises-beginner.pdf?raw=true)\r\n\r\nSkeleton code for [`computedamrateofflow.m`](https://raw.githubusercontent.com/uiuc-cse/matlab-fa14/gh-pages/lessons/computedamrateofflow.m).\r\n\r\n\r\n# [Numerical Methods & Differential Equations](#num-methods)\r\n### **Part 1**, Feb. 9, 1:00 pm\r\n### **Part 2**, Feb. 11, 1:00 pm\r\n\r\nThis tutorial focuses on the solution of differential equations and similar systems with MATLAB. The first lesson will focus on data fitting and the finite difference method (matrix equations and loops). The second lesson will explore differential equation solutions, including systems of equations and the PDE Toolbox.\r\n\r\n### Lesson Materials\r\n\r\n**Spring Interpolation Data**\r\n\r\n m = [5 10 20 50 100]; %mass data (g)\r\n d = [15.5 33.07 53.39 140.24 301.03]; %displacement data (mm) \r\n g = 9.81; %g = 9.81\r\n F = m/1000 *g; %compute spring force (N)\r\n\r\n**Heat Equation by Finite Difference Method**\r\n\r\nFinite-difference models are used throughout engineering to obtain numerical solutions to differential equations. This particular system models the heat equation\r\n\r\n$$ \\frac{1}{\\alpha} \\frac{\\partial u}{\\partial t} = \\frac{\\partial^2 u}{\\partial x^2}$$\r\n\r\ngiven an initial condition of $u(x,t=0) = \\sin\\left(\\pi x/L\\right)$ and boundary conditions of $u(x=0,t) = 0$ and $u(x=L,t) = 0$.\r\n\r\nTo approximate a derivative, the most straightforward way is to take the formal definition\r\n\r\n$$f'(x) = \\frac{f(x+h)-f(x)}{h}$$\r\n\r\nand use a small but nonzero step $h$ in your calculation.\r\n\r\nApplication of this principle to the heat equation leads to a statement of the form\r\n\r\n$$ \\frac{1}{\\alpha} \\frac{u^m_i - u^{m-1}_i}{\\Delta t} = \\frac{u^{m-1}_{i-1} - 2 u^{m-1}_{i} + u^{m-1}_{i+1}}{\\Delta x^2} $$\r\n\r\nor $u^m_i = \\frac{\\alpha \\Delta t}{\\Delta x^2}u^{m-1}_{i-1} + \\left[1 - 2\\left(\\frac{\\alpha \\Delta t}{\\Delta x^2}\\right)\\right]u^{m-1}_{i} + \\frac{\\alpha \\Delta t}{\\Delta x^2}u^{m-1}_{i+1}$.\r\n\r\nThis clearly yields a way to calculate subsequent time steps point-by-point from the previous time step's data.\r\n\r\n\r\n\r\n**Radioactive Decay System of Differential Equations**\r\n\r\n\r\n\r\n\r\n\r\n###### Erika's scripts from class:\r\n\r\n- [`decaySchemeMain.m`](https://raw.githubusercontent.com/uiuc-cse/matlab-sp15/gh-pages/lessons/decaySchemeMain.m)\r\n- [`decay_scheme.m`](https://raw.githubusercontent.com/uiuc-cse/matlab-sp15/gh-pages/lessons/decay_scheme.m)\r\n- [`projectileMotionEOM.m`](https://raw.githubusercontent.com/uiuc-cse/matlab-sp15/gh-pages/lessons/projectileMotionEOM.m)\r\n- [`projectileMotionMain.m`](https://raw.githubusercontent.com/uiuc-cse/matlab-sp15/gh-pages/lessons/projectileMotionMain.m)\r\n\r\n# [Parallel MATLAB](#parallel)\r\n### Feb. 16, 1:00 pm\r\n\r\nWe will discuss the Parallel Computing Toolbox, which lets you utilize multiple cores and GPUs on your desktop machine.\r\n\r\n- [Lesson notes](https://github.com/uiuc-cse/matlab-sp15/blob/gh-pages/lessons/pct.md)\r\n\r\n# [Introduction to MATLAB](#intro) (repeat)\r\n### Feb. 17, 1:00 pm\r\n\r\n# [Plotting](#plot)\r\n### Feb. 23, 1:00 pm\r\n\r\nThis lesson introduces the basic features of MATLAB's plotting system, including a list of commonly required functions and their applications in a scientific computing context. We also discuss how to improve the plot such that it can be published professionally.\r\n\r\n- [Lesson notes](http://nbviewer.ipython.org/github/uiuc-cse/matlab-sp15/blob/gh-pages/lessons/plotting.ipynb)\r\n\r\n# [Image Processing in MATLAB](#image)\r\n### **Part 1**, Mar. 2, 1:00 pm\r\n### **Part 2**, Mar. 4, 1:00 pm\r\n\r\nThese workshops are designed to teach you how images are represented in MATLAB, how color spaces work, and many of the basic and advanced manipulations you can carry out using the Image Processing Toolkit, including basic automatic feature identification.\r\n\r\n###### Lesson Materials\r\n\r\n- [Notes on file formats and internal representations](https://github.com/uiuc-cse/matlab-sp15/raw/gh-pages/lessons/ImageProcessingMaterial.docx)\r\n\r\n- [Satellite k-means detection script](https://raw.githubusercontent.com/uiuc-cse/matlab-fa14/gh-pages/lessons/satellite_kmeans.m)\r\n\r\n- [Bridge angle detection script](https://raw.githubusercontent.com/uiuc-cse/matlab-fa14/gh-pages/lessons/AngleDetection.m)\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n[MRI TIF image](https://github.com/uiuc-cse/matlab-sp15/blob/gh-pages/lessons/img/mri.tif?raw=true)\r\n\r\n# About These Workshops\r\n### Contributors\r\nNeal Davis, Erika Fotsch, and Rishabh Narang developed these materials. This content is available under a Creative Commons Attribution 4.0 Unported License.\r\n\r\n\r\n\r\n# Contact\r\nIf you have any questions about course availability, concepts, or content, please contact Neal Davis, Training Coördinator for Computational Science & Engineering, at davis68 at illinois dot edu.","google":"UA-53962544-6","note":"Don't delete this file! It's used internally to help with page regeneration."}