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Computational Methods

Scientific Computing with MATLAB, University of Waterloo  

Overview of MATLAB use for research, as used by the Univ of Waterloo.

Language: English
Submitted: Sep 13, 2007
Computational Science and Engineering I  
Description: This course provides a review of linear algebra, including applications to networks, structures, and estimation. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.
Course material created by Professor Gilbert Strang.
Target audience: Graduate
Institution: Massachusetts Institute of Technology
Materials available: Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files
Products: MATLAB

Submitted: Jul 30, 2008
Computational Economics  
Description: This course studies computational approaches for solving economic models. We formulate economic problems in computationally tractable forms, and use numerical analysis techniques to solve them. We will study examples of computational techniques in the current economic literature as well as discuss areas of economic analysis where numerical analysis may be useful in future research of dynamic economic problems. The substantive applications will cover a wide range of problems including public finance, macroeconomics, game theory, mechanism design, finance, industrial organization, agricultural economics, and econometrics.
Course material created by Dr. Kenneth L. Judd.
Target audience: Advanced undergraduate (3rd or 4th year)
Institution: Stanford University
Materials available: Problem sets or projects, Course outline or syllabus
Products: MATLAB

Submitted: Aug 06, 2008
Computational Methods in Economics  
Description: Fundamental methods for formulating and solving economic models will be developed. Emphasis will be on defining the mathematical structure of problems and on practical computer methods for obtaining model solutions. Major topics will include solution of systems of equations, complementarity relationships and optimization. Both finite and infinite dimensional problems will be addressed, the latter through the use of finite dimensional approximation techniques. Particular emphasis will be placed on solving dynamic optimization and equilibrium problems. Applications will be drawn from finance, agricultural and resource economics, macroeconomics and econometrics.
Course material created by Professor Paul L. Fackler.
Target audience: Graduate
Institution: North Carolina State University
Materials available: Problem sets or projects, Course outline or syllabus, Textbook recommendations
Products: MATLAB

Submitted: Aug 06, 2008
Analytical and Computational Methods in Electrical Engineering  
Description: This course will provide extensive coverage of numerical linear algebra, focusing on algorithms and capabilities that are incorporated into MATLAB. Applications of the material will be given in the areas of image compression, the least squares fit of a line to a data set, and n-port electrical networks.
Course material created by Dr. John L. Stensby.
Target audience: Graduate
Institution: The University of Alabama in Huntsville
Materials available: Course outline or syllabus
Products: MATLAB

Submitted: Jul 30, 2008
Introduction to Computational Biology and Chemistry  
Description: This course explores models that arise in biology and chemistry and how they're analyzed using modern mathematical and computational techniques. Topics covered are statistical models, discrete- and continuous- time dynamical models, and stochastic models. Applications will sample a wide range of scales, from biomolecules to population dynamics, with an emphasis on common mathematical concepts and computational techniques. Throughout, themes will include interpretation of existing data and predictions for new experiments.
Course material created by Professor Eric Shea-Brown.
Target audience: Advanced undergraduate (3rd or 4th year)
Institution: University of Washington
Materials available: Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files
Products: MATLAB

Submitted: Jul 30, 2008
Introduction to Computational Neuroscience  
Description: This course focuses on mathematical concepts and techniques used in computational neuroscience. It is designed to provide students with necessary mathematical background for formulating, simulating, and analyzing models of individual neurons and neural networks. The course will serve as an introduction to the theory of nonlinear differential equations and applied dynamical systems in the context of neuronal modeling. The topics to be covered include a review of basic facts about the electrophysiology of neural cells, analysis of the conductance based models, neural excitability, bursting, models for synaptically coupled cells, and compartmental models, as well as a number of mathematical techniques such as phase plane analysis, fast-slow decomposition, and elements of the bifurcation theory. The students will learn basic models of excitable membranes such as Hodgkin-Huxley, Morris-Lecar, and FitzHugh-Nagumo models.
Course material created by Professor Georgi Medvedev.
Target audience: Graduate
Institution: Drexel University
Materials available: Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files
Products: MATLAB

Submitted: Jul 30, 2008
Computational Methods in Geological Sciences  
Description: This course covers topics essential to understanding geophysical data processing, many related to time series analysis. These include: data processing concepts; frequency domain methods, the discrete Fourier transform; time domain methods and linear filters; random variables; and least squares.
Course material created by Professor Clark R. Wilson
Target audience: Advanced undergraduate (3rd or 4th year)
Institution: University of Texas
Materials available: Problem sets or projects, Course outline or syllabus
Products: MATLAB

Submitted: Aug 06, 2008
Wavelets, Filter Banks and Applications  
Description: The course will consist of lectures, homework assignments and a project on a topic related to the student's area of interest. We will aim for the right balance of theory and "applications". The course has no specific prerequisites, although a basic knowledge of Fourier transforms is recommended. We start with time-invariant filters and basic wavelets. The text gives an overall perspective of the field -- which has grown with amazing speed. The topics will include
- Analysis of Filter Banks and Wavelets
- Design Methods
- Applications
- Hands-on Experience with Software
Target audience: Graduate
Institution: MIT
Materials available: Problem sets or projects, Presentations, Course outline or syllabus, Textbook recommendations, Downloadable code or data files
Products: Wavelet Toolbox
Course material created by Professor Gil Strang
Submitted: Oct 16, 2008



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