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 departmentís 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