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Department of Electrical Engineering
EE 4623 Digital Filtering (Credit 3)
Catalog Description:
4623 Digital Filtering
(3-0) 3 hours credit. Prereuisites: EE 3523 or concurrent enrollment in EE 3523
Design and implementation of FIR and IIR filters, hardware, and software; and topics from adaptive filtering, neural networks, and image processing.
Prerequisites:
- EE 3523 Signals and Systems II (Require grade of C or better)
Textbook(s) and/or required material:
Textbook: Sophocles J. Orfanidis “ Introduction to Signal Processing” Prentice Hall Pub. 1996
Reference:
- S. Haykin “Adaptive Filter Theory”, Prentice Hall Pub. 1996
- C. Lin, G Lee “Neural Fuzzy Systems: A Neuro_Fuzzy Synergism to Intelligent Systems” Prentice Hall Pub. 1996
- Agaian’s Lecture Notes
Major preprequisite by topic:
- Continuous and discrete time signals and systems
- Fourier series and Fourier transform
- Properties of discrete-time signals and systems
- Convolution
- The Z-Transform
Familiarity with Matlab (or willingness to learn!).
Course objectives: This course will help the students to:
- Learn the design procedures for Finite Impulse Response (FIR), Infinite Impulse Response(IIR) filters.
- Appreciate relationships between rectangular, Hamming, Mann, Cesaro, and Kaiser windowing methods;
- Appreciate relationships between first order low pass, and high pass filters, and between second-order Peaking and Notching filters;
- Use classical Butterworth and Chebyshev filters
- Learn the design procedures for filter bank
- Familiarize students with structure and classification of digital filters
- Enable students to design digital filter, by using appropriate design approaches
- Learn the basic principles of Neural Network and adaptive filtering.
- Enhance problem-solving skills
- Enhance written communication.
Lectures cover digital filtering topics relevant to the lab_Matlab exercises. The focus of the course is a series of project_experiments, which provide practical knowledge in processing real signals, with examples from cardiology, speech, and image processing.
Topics:
- Fourier transforms, DFT/FFT algorithms (matrix form), Linear System, and convolution
- Fourier technique based FIR digital Filters design methods (including windowing method: Rectangular, Humming, and Kaiser)
(Project 1)
- IIR digital filter design (Bilinear transformation, First order low pass, and high pass filters, second-order Peaking and Notching filters), high order filter design (classical Butterworth and Chebyshev filters)
(Project 2)
- Nonlinear filters.
- Adaptive filters and neural networks
(Project 3)
Contribution of course to meet the professional component:
This course prepares students to work professionally in the area of digital filtering.
Relationship to EE program objectives and outcomes:
This course primarily contributes to Electrical Engineering program outcomes that develop students abilities to:
- Use the principles from statistics and mathematics in engineering applications
- Use computer-based tools for engineering applications
- Identify, formulate, and solve engineering problems.
Course Outcomes: Students will
- Have the fundamental digital filter design skills by using appropriate design approaches (A3).
- Have an ability to identify, formulate and solve filtering problems (B1).
- Have an ability to utilize computer applications for solving practical engineering problems (B2).
- Have an ability to work effectively in multi-disciplinary teams (B4).
- Have the ability to present technical information clearly in both oral and written formats (c-2).
- be aware of the need for continuing professional education (c-4).
- develop creative and innovative designs that achieve desired performance criteria within specified objectives and constraints.
Evaluation method:
- Design projects:
First Project ……….30%
Second Project …….30%
Third Project ………40%
Project Description:
There are three major steps in the project:
- Design and implement your filtering routine in MATLAB based on the provided special signals and images and ground truth data.
- Test your routine with the training images by the evaluation program.
- Performance of your routine will be tested in the class presentation with a test image by the same evaluation program.
Possible Projects:
Project-1 (Computer or hardware implementation, samples)
- Develop a program that implements the discrete Fourier transform and verify (experimentally) the basic properties of Fourier transform. Display the results
- Generate the class of noises. Display the results
- Develop a program for computing the discrete Fourier and windowing Fourier transform of a signal. Display the results
- Develop a program that implements the Fourier series based on FIR filters, (including Cesaro, and Vallee Poussin filters), and use the program for signal filtering. Display the results
Project-2 (Computer or hardware implementation, samples)
- Develop the programs that implement the first_order lowpass, and highpass filters. Display the results
- Develop a program that implements the second-order Peaking and Notching filters. Display the results
- Verify (experimentally) the basic properties of the Chebyshev system. Develop a program that implements the Chebyshev filters. Display the results
- Verity (experimentally) the basic properties of the Butterworth system. Develop a program that implements the classical Butterworth filter. Display the results
Project-3 (Computer or hardware implementation, samples)
- Develop a program that implements the nonlinear filters
- Develop a program that implements an adaptive filter
The purpose of these projects is to gain a practical understanding the visual phenomena of the digital filters.
Project Report and Presentation
Nonlinear Digital filtering with Weighted Median Filters
(Sample)
Abstract: Develop the program that implement the Positive and Negative weighted Median. A variety of 1-dimensional signals and 2-dimensional images, polluted with various types and percentages of noise, are filtered.
Contents
Abstract …………………………………………
Introduction ……………………………………..
Background ……………………………………..
Filter Design …………………………………….
Computer Simulations …………………………..
Experiments Performance Evaluation Conclusion …………….
References ……………………………………….
Matlab Code ……………………………………..
Or,
A Comparison of the Effectiveness of an IIR Notch Filter vs. Fourier Series FIR Notch Filter on Low Frequency Sinusoidal Noise in Images
Abstract: The primary goal of this project is to measure the difference between the ability of a second order Infinite Impulse Response (IIR) Digital Notch Filter and a Fourier Series Finite Impulse Response (FIR) Notch Filter Implementation to remove low frequency sinusoidal noise from a grayscale Image. The effectiveness of the filters will be measured using the Mean Square Error method and the Max Error method.
Table of Contents
Abstract …………………………………………
Introduction ……………………………………..
Background ……………………………………..
Filter Design …………………………………….
Computer Simulations …………………………..
Experiments Performance Evaluation Conclusion …………….
References ……………………………………….
Matlab Code ……………………………………..
Abstract:Maximum 200 words
Introduction: clearly explain the nature of the problem, purpose, and contribution of the project. Diagrams and Images must be computer-designed and submitted as embedded images in your document (MS Word format). Keep in mind that black and white drawings reproduce far better than drawings with grey tones. Digitized photographs in 256 grayscale are recommended. Images in TIFF or JPEG format are preferred. If converting native images to a JPEG, 200 dpi at a quality of 8 is recommended.
Conclusion: should be clearly indicate advantages, limitations and possible applications.
References: must be numbered in the order cited in the manuscript and indicated in the text by a number in square brackets (e.g., [1]).
The correct format for references is:
Papers: Author, paper title, journal name (in italics), volume & issue numbers, year, inclusive pages e.g.
[1] T.C. Hsia, Simple robust schemes for space control of robot manipulators, Int. J. of Robotics and Automation, 9(4), 1994, 167-174
Books: Author, title (in italics), location of publisher, year e.g. [2] M. Kayston and W.R. Fried, Avionic Navigation Systems (New York: John Wiley and Sons Inc., 1969)
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