Syllabus revised May 30, 2005
Course Name & Number: Voice
and Signal Processing CR310
(SW511,ECE460)
Course Description:
Overview of Digital Audio and its application Current state of streaming Audio on the Internet Digital Audio Processing Fundamentals. This course applies transform concepts and applied multi-media object-oriented programming. Students will apply the theories of Sampling, Spectra, Fast Fourier Transform Class, convolution and frequency space processing, compression and one-dimensional streaming. Students will apply the theories by creating programs that read processing and write audio streams. They are exposed to the elements of multi-media network delivery of data. They learn about a wide class of FFT algorithms and elementary sound synthesis. This course requires substantial programming effort and emphasis is place on good software engineering practices. Students will learn enough signal processing to take Image Processing, the follow-on course.
Prerequisite – CS232, MA 172 or permission of instructor.
Computer Usage: We are using IntelliJ as the IDE, with JDK1.4.
|
Time: |
Tuesdays 4:00pm - 7:00pm |
|
|
Place: |
Norden: on-site |
|
|
Instructors: |
Jeffrey N. Denenberg |
Douglas Lyon |
|
Phone: |
(203) 268-1021 |
(203) 641-6293 |
|
Fax: |
|
(203) 877-4187 |
|
Email: |
||
|
Home Page: |
||
|
Prerequisites: |
CS232, MA 172 or permission of instructor. |
|
|
Office Hours: |
The hour before class on Tuesdays |
|
|
Texts: |
Sanjit J. Mitra, |
Lyon and Rao, |
|
Software: |
MatLab 4.2c (or later), The Mathworks |
|
|
References: |
Phillips and Parr, Signals, Systems, and Transforms, Philips and Parr, Interactive Lecture Notes (Chapters 1-7), EE235 Mitra, 2nd Edition, Lecture Notes, Index Hsu, Analog and Digital Communications, Lathi, Linear Systems and Signals, Soliman and Srinath, Continous and Discrete Signals
and Systems, Lathi, Linear Systems and Signals, Denenberg, Fourier Series Denenberg, Fourier Transform Denenberg, Sampling and Reconstruction Denenberg, Linear Systems Denenberg, Introduction to Noise |
|
This course designed to support the signal processing and computer systems domain in the CE BS degree. When the course is done, Students will have written their own Java applications that demonstrate the ideas presented in the course. This course requires substantial programming effort and emphasis is place on good software engineering practices.
Learning Objectives for Voice and Signal Processing
1. The students will learn the principles of Digital Signal Processing.
2. The students will become proficient with the usage of the Java language.
3. The students will recognize interrelationships among signals and spectra
4. The students will learn enough CS to do basic multi-media programming
5. The students will learn about Object Oriented Design
6. The students will learn how to apply their mathematical background to signal processing
Outcomes:
oc1. Students write a program to display waveforms using a software o-scope.
oc2. Demonstrates the ability to utilize Java in practical signal processing problems.
oc3. Uses appropriate object-oriented design patterns to solve problems.
oc4. Applies transform concepts in programming situations
oc5. Students can perform constructive and destructive synthesis.
oc6. Students perform spectral analysis
|
Student Objective |
Outcome Category |
|
|
|
The students will learn the principles of Digital Signal Processing. 2. 3. 4. |
|
1.5
|
|
|
The students will become proficient with the usage of the Java language. The students will recognize interrelationships among signals and spectra |
|
||
|
Problem Solving |
1.0 |
|
|
|
The students will learn enough CS to do basic multi-media programming |
|
0.5 |
|
|
The students will learn about Object Oriented Design The students will learn how to apply their mathematical background to signal processing |
|
||
Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.
Textbook: Java Digital Signal Processing by Douglas Lyon
Reference Material: Websites to be announced
Course Requirements: The course includes three reporting periods (exam, quiz, project, etc.) and a comprehensive final.
Attendance Policy: Students are responsible to acquire notes and homework assignment from classmates in case of absence.
Grading Policy:
Homework and Laboratory Trials: 1/3
Midterm Exam : 1/3
Final Exam : 1/3
Assignments are due at the beginning of class. Assignments handed in during class lose 5 points, after class 10 points. Late submittals lose 10 points per day including weekends and holidays. Missing a test results in a zero unless a written excuse is presented.
Homework requirements:
Print out a listing of the program. Print out the program input and output. You may need to do this at various levels of detail. Hand in a labeled disk with a printout. Place the disk in a #10 letter envelope and staple the envelope to the printout.
Java Sound Topics by week (schedule is subject to change)
Preliminary topics:
10. Overview of Digital Audio and its application, Current state of streaming Audio on the Internet, Problems and solutions. Midterm Assigned.
11. Digital Audio Processing Fundamentals, Sampling, Spectra
12. Midterm due. AudioStreams, doubleData, ulawData, Audio File Formats/Coding, Audio file formats, u-law companding in the Sun AU files, decoding u-law, encoding u-law, reading, writing, playing,
13. Constructive Synthesis, Sine, Triangle, Square, Sawtooth
14. Spectral Analysis, The Discrete Fourier Transform, The Inverse DFT, The Fast Fourier Transform Class, The Inverse FFT method, Fast Convolution using the FFT, Power Spectral Estimation, Filtering using FFT, Additive vs. Subtractive Synthesis, Frequency shifting using the FFT, Delay, echo vs. reverb spectral impact
Week 15. Final
Week / Text |
Lecturer |
Lecture / Discussion |
Homework/Reference |
|
May 31 |
Lyon
Denenberg |
Course Introduction Java Programming Review
|
Smith: Chapter 1 |
|
June 7 |
Denenberg |
Fourier transform and Convolution Review |
|
|
June 14 |
Denenberg |
Sampling and Reconstruction |
|
|
June 21 |
Denenberg |
The Discrete Fourier Transform (DFT) and the Fast Fourier Transform |
|
|
June 28 |
Denenberg |
The Z-Transform |
|
|
July 5 |
Lyon |
Java Signal Processing |
|
|
July 12 |
Denenberg |
Digital Filter Structures |
|
|
July 19 |
Denenberg |
Digital Filter Design |
|
|
July 26 |
|
Exam 1 |
|
|
August 2 |
Lyon |
Java Signal Processing |
|
|
August 9 |
Lyon |
Java Signal Processing |
|
|
August 16 |
Lyon |
Java Signal Processing |
|
|
August 23 |
Lyon |
|
|
|
August 30 |
Lyon |
Java Signal Processing |
|
|
September 6 |
Lyon |
FINAL EXAM
|
|