Lectures, Labs (using MATLAB), Assignments
- Introduction to MATLAB
- Flow control and Data structures
- Plotting in MATLAB
- Strings and file input/output
- Complex numbers
- Combinatorics
- Linear Algebra
- Statistics and Data Analysis
- Polynomial approximation and curve fitting
- Root finding and numerical differentiation
- Numerical integration
- MATLAB executable files
Upon completion of ENGR 1180 the student should gain enough familiarity with MATLAB to:
- understand basic input and output syntax
- create different object types such as variables, vectors, arrays, matrices and structures
- perform operations on different object types using built-in commands
- write scripts and functions to execute and simplify multiple commands
- understand flow control including: if-then, for, while, break, try/catch, switch
- create various plots types used in science and engineering, such as: 2D plots, 3D plots, subplots, overlaid plots, piecewise plots, bar plots, vector fields
- use object handles to automate the task of modifying and formatting plots
- understand strings; perform basic operations on them
- import, export, read and write various file types such as: text, binary, Excel, image and video
- understand the need for, and the use of, MEX files
- understand various toolboxes used in engineering analysis
- perform arithmetic operations on complex numbers; work with complex valued objects
- compute permutations and combinations
- perform arithmetic operations on vectors and matrices; calculate numerically the determinant and inverse of a matrix
- solve numerically systems of linear and non-linear equations; solve numerically practical problems containing systems of equations
- perform computations with the Binomial and Poisson probability mass functions for discrete random variables, the Normal probability density function and cumulative distribution function for continuous random variables
- compute the mean, variance and standard deviation for a sample data set
- perform linear regression and correlation analysis on a sample data set
- perform polynomial interpolation on a sample data set
- determine numerically the solutions to non-linear equations using the bisection method or the Newton-Raphson method
- compute numerically the derivative of a function using finite-differences
- compute numerically the value of an integral using various numerical quadrature methods: midpoint, trapezoid, Simpson’s rule, adaptive methods
Evaluation will be carried out in accordance with Douglas College policy. The instructor will present a written course outline with specific evaluation criteria at the beginning of the semester. Evaluation will be based on some of the following criteria:
- Labs 0 – 25%
- Tests 20 – 60%
- Assignments/Group work 0 – 20%
- Attendance 0 – 5%
- Course Project 0 - 20%
- Final examination 30 – 40%
The use of a textbook is left to the discretion of the instructor. The instructor will either provide detailed course notes or require the use of a textbook. Consult the Douglas College bookstore for the current textbook. Examples of appropriate textbooks include:
Hanselman, Duane and Littlefield, Bruce, Mastering MATLAB, current edition, Pearson
Note: While MATLAB is the software used for the course, it is left to the discretion of the instructor whether open-source versions of MATLAB (such as GNU Octave) are acceptable for student use.
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