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Numerical Methods for Engineers
Category:
Academic Curricula>Mechanical Engineering
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http://web.cecs.pdx.edu/~gerry/class/ME352/
ME 352 is a required course for the BSME program, and it is typically taken in the third year. The primary goal is to provide mechanical engineering majors with a basic knowledge of numerical methods including: root-finding, elementary numerical linear algebra, solving systems of linear equations, curve fitting, and numerical solution to ordinary differential equations. MATLAB is the software environment used for implementation and application of these numerical methods. The numerical techniques learned in this course enable students to work with mathematical models of technology and systems.
Course: ME 352 (Mechanical Engineering)
Professor: Gerald Recktenwald
University: Portland State University
Prerequisites:
Sophomore course in Differential Equations, Sophomore Course in linear algebra
The curriculum material includes:
- Course outline
- Lecture slides
- Homework problems / projects
- Required/recommended textbook
- Downloadable M-files and PDF files
Submitted Jan 23, 2008
by Gerald Recktenwald
Updated Mar 12, 2008
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Control Tutorials for MATLAB (Undergraduate 2nd year)
Category:
Academic Curricula>Electrical Engineering
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http://www.engin.umich.edu/group/ctm/
These tutorials are designed to illustrate how to use MATLAB and Simulink for the analysis and design of automatic control systems. They cover the basics of MATLAB and Simulink, the most common classical control design techniques (PID, root locus, and frequency response), as well as some modern (state-space) control design. The Control Systems Toolbox is used extensively in these tutorials.
Course Level:
Senior undergraduate
Graduate
Type of content:
MATLAB Primer/Tutorial
Simulink Primer/Tutorial
Prerequisite(s) / Target Audience:
Students who need to learn or brush up on Matlab/Simulink. MathWorks Toolboxes or Blocksets used: Control Systems toolbox and Simulink Professor Name: Bill Messner (CMU) & Dawn Tilbury (UofM)
Department: Mechanical Engineering
University: Carnegie Mellon and University of Michigan
Submitted Mar 11, 2008
by Bill Messner & Dawn Tilbury
Updated Mar 12, 2008
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Physical Modeling
Category:
Model-Based Design
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http://physical-modeling.mathworks.com
Accelerate system-level analysis and control design with accurate and intuitive models of your physical system
The design of engineering systems requires tight integration of many engineering disciplines. To be successful, teams of engineers must collaborate using a wide array of diverse technologies. Software, in the form of control algorithms and signal processing algorithms, plays an ever increasing role in these systems. Developing software alongside the physical system results in optimized designs and the detection of errors earlier in the design process.
Submitted Mar 19, 2008
by Steve Miller
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N/A
(1 Ratings)
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MathWorks - Parallel Computing Toolbox
Category:
Parallel and Distributed
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http://www.mathworks.com/products/distribtb/
Parallel Computing Toolbox? enables you to use MATLAB? and Simulink? to harness multiprocessing hardware for solving computationally and data-intensive problems. The Parallel Computing Toolbox software extends the MATLAB language with high-level parallel processing constructs such as parallel for-loops, distributed arrays, parallel numerical algorithms, and message-passing functions that let you exploit data and task parallelism in your applications. You can transition from serial MATLAB programs to parallel MATLAB programs without making significant changes to existing code or learning a low-level parallel language.
Submitted Nov 08, 2004
Updated Mar 14, 2008
by Gaurav Sharma
Rating:
(8 Ratings)
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CS 522: Computational Methods for Finance (Graduate)
Category:
Academic Curricula>Economics and Finance
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http://www.cs.cornell.edu/Courses/cs522/2005sp/
Computational finance is an interdisciplinary subject of probability theory, finance, and numerical analysis. The emphasis of this course is on computational methods and mathematical models for various derivative pricing and risk management problems. Standard as well as exotic derivatives on equities, indices, and interest rate will be introduced; different computational methods are used for their pricing and hedging.
Professor Name: Tibor Janosi
Department: Computer Science
University: Cornell University
Submitted Aug 23, 2007
by Tibor Janosi
Rating:
(6 Ratings)
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