Master Course Description

No: EE442

Title: DIGITAL SIGNALS AND FILTERING

Credits: 3

UW Course Catalog Description

Coordinator: Jenq-Neng Hwang, Professor of Electrical Engineering

Goals: To provide students with the fundamental knowledge of digital filter characteristics, design principles, and design specifications. Also to provide the opportunity for the students to actually design digital filters, FIR, IIR and adaptive filters, through the use of Matlab software to solve real world applications.

Learning Objectives:

At the end of this course, students will be able to:

  1. Provide students with the fundamental knowledge of digital filters
  2. Design a digital filter with frequency specifications
  3. Design a digital filter by various techniques and compare the tradeoffs.

Textbook: Vinay K. Ingle and John G. Proakis, Digital Signal Processing using Matlab, 3rd Edition, Cengage Learning, 2011.

Reference Texts:None

Prerequisites by Topic:

  1. Discrete Time Signals and Linear Time Invariant Systems
  2. Fourier Transform (continuous-time & discrete-time)
  3. Laplace Transform
  4. Z-Transform

Topics:

  1. Review of Discrete-Time Fourier Transform (DTFT) and Z Transform
  2. Review of Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT)
  3. Digital Filter Structures
  4. Digital Finite Impulse Response (FIR) Filter Design
  5. Digital Infinite Impulse Response (IIR) Filter Design
  6. Adaptive Filter Design

Course Structure: The class meets for three 50-minute lectures a week. There are weekly homeworks that include some Matlab design projects as well as analytical derivations. The midterm and final exam are all written exams which consist of both analytical and programming questions.

Computer Resources: The course uses Matlab for all the design assignments. The recomended platforms are departmentalPCs with full suite of Matlab, including most toolboxes. It is also possible to use students' own personal computers with Matlab (the Matlab is available to students at academic discount from the University Book Store). The average student will require 6-8 hours of computer work per week.

Laboratory: None

Grading: Weekly homework 24%, Midterm Exam. 32%, Final Exam. 44%

Outcome Coverage:(H): High, (M): Medium, (L): Low, (NA): Not Applicable

(a:) An ability to apply knowledge of mathematics, science and engineering (H)

(b:) An ability to design and conduct experiments, as well as to analyze and interpret data (L)

(c:) An ability to design a system, component or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability (M)

(d:) An ability to function on multi-disciplinary teams (NA)

(e:) An ability to identify, formulate and solve engineering problems (H)

(f:) An understanding of professional and ethical responsibilities (NA)

(g:) An ability to communicate effectively (NA)

(h:) The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental and societal context (NA)

(i:) A recognition of the need for, and an ability to engage in life-long learning (NA)

(j:) Knowledge of contemporary issues (NA)

(k:) An ability to use the techniques, skills and modern engineering tools necessary for engineering practice (H)

Prepared By: Jeng-Neng Hwang

Last revised: 4/21/07