## EE 251, Mathematical Engineering

**Course number and name:** EE 251, 251L, Mathematical Engineering

**Credits and contact hours:** 3 credits

**Specific course information:**

- Brief description of the content of the course:
- Standard programming languages in engineering are applied to data acquisition, data analysis and mathematical computations. Fundamental concepts in Matlab and C are used to develop programming skills and techniques by addressing problems related to electrical engineering.
- Typical topics include programming hardware, collection and manipulation of large data sets; signal and noise analysis; data fitting; numerical solutions to problems; basics of image processing; data encryption; stenography; and signal acquisition and extraction using Matlab toolboxes with commonly available hardware.

- Prerequisites or Co-requisites:
- Prerequisites: None
- Co-requisite: MATH 131 (Calculus I)

- Indicate whether a required or elective course in the program:
- Required

**Specific goals for the course:**

- Specific Outcomes addressed by the course:
- Students will learn basic concepts of mathematical modeling relevant to electrical engineering
- Students will learn programming concepts and tools, debugging, and analysis techniques
- Students will be able to use programming languages to solve engineering problems

- Student Outcomes addressed by the course:
- This course is not directly used as part of the electrical engineering department’s student learning outcomes assessment program.

**Brief list of topics to be covered:**

- Lecture
- Introduction to Linux based operating systems
- Using terminals and command line
- C Programming
- a. Data types and operators
- b. Control flow
- c. Functions
- d. Input/output
- e. Strings
- f. Preprocessor
- g. Arrays
- h. Pointers
- i. Memory allocation
- j. Data files

- MATLAB
- a. Variables and arrays
- b. Multidimensional arrays
- c. Data files
- d. Plotting
- e. Vector math
- f. Control flow
- g. User-defined functions

- Laboratory
- Data analysis
- Design a strategy game with user/computer interaction
- Data/file processing, e.g., filtering, signal quality analysis, mean squared error, etc.
- Data visualization