Department of Electrical and Computer Engineering

ECE 102: Engineering Computation

Catalog Description

Applying the principles of engineering analysis. Presenting technical content. Utilizing engineering software and writing scripts. Controlling external hardware via programming. Weekly lab.

Credit hours: 4 (3 lecture + 1 lab)

Goals

Students will have the ability to apply appropriate engineering and programming practices to simple electrical engineering problems and designs.

Course Coordinator and Committee

Branimir Pejčinović (coordinator)
Melinda Holtzman
Phillip Wong

Textbooks

Required:
Programming in MATLAB, zyBook interactive textbook, Zyante Inc.

The course instructor may choose to use a different textbook. Please check with your instructor before purchasing.

Prerequisites

ECE 101 or equivalent. Mth 112 with a grade of C or better or passing at the necessary level on the mathematics placement test (see PSU Math Department webpage at pdx.edu/math for information).

Corequisite

ECE 102L

Course Learning Outcomes

At the end of this course, students will have the ability to:

  • Solve engineering problems by applying the engineering method.
  • Analyze basic DC circuits using Ohm's law, Kirchhoff's laws, and the node voltage method.
  • Develop algorithms in MATLAB to solve simple engineering problems.
  • Use MATLAB programming for data acquisition and control.
  • Communicate technical information in written and graphical format.
  • Participate effectively as a team member on a design project.

Topical Outline

  • Introduction to MATLAB operators, variables and scripts
  • Console I/O, arrays, basic plots
  • Functions and matrices
  • File I/O
  • Logical / relational statements and translating word problems into logical /relational statements
  • Selection (branches)
  • Loops
  • Strings and structures
  • Writing larger, modular programs
  • Basic DC electric circuits (series & parallel connection, voltage and current dividers)
  • Circuit analysis (focus on node voltage method)
  • Unit conversion
  • Error analysis (significant figures, ranges of values, min/max or best/worst case analysis)
  • Systematic engineering problem solving
  • Data presentation (tables and advanced plots)

Course Structure and Grading Criteria

Structure:

  • Two 90-minute weekly lectures
  • One 180-minute weekly lab

Grading Criteria:

  • In-class participation (using e.g. Learning Catalytics)
  • Textbook readings & exercises (zyBook)
  • Homework assignments (Standard and MATLAB)
  • Lab participation and reports
  • Project (includes demo)
  • Exams (traditional, in-class exams; make-up at Instructor’s discretion.)
  • MATLAB Competency Tests (CT), P/NP. Not passing CT results in automatic F grade for the class.

Grading criteria may vary with instructor. Refer to the individual instructor’s syllabus for information on the grading breakdown (i.e., percentage weight for each category) and the grading scheme.

Relevant Program Outcomes

The following student program outcomes are supported by this course:

(1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
(3) An ability to communicate effectively with a range of audiences
(5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives

Prepared By: Branimir Pejcinovic
Last revised: 5/25/20