EE 430 Fall 2011                         

 

Course Name: EE430, Digital Signal Processing

Course Description: Building upon the basic theory of signals and systems analysis, this course introduces the student to the theory and applications of digital signal processing. Topics covered include the representation of discrete-time signals, frequency domain and Z-domain analysis of discrete-time signals and systems, discrete Fourier transform, sampling, A/D, and D/A conversion, discrete-time feedback systems and system structures, difference equations and transfer functions, minimum, maximum and linear-phase systems, design of FIR and IIR filters, window based FIR filter design, digital filtering of signals, FFT algorithm and structures, FFT based power spectrum analysis, discrete Hilbert transform and homomorphic signal processing.  Experience in the design, implementation and application of DSP techniques is acquired by the Matlab homeworks.

 

Lecturers: Dr.Aydın Alatan, Dr.T. Engin Tuncer

LectureHours:Sec1:Wed.10:40,Fri.13:40-15:30(EA307-208),Sec2:Wed.13:40-15:30,Fri.11:40(EA310-307)

Grading:  Homework 15 %, 2 Midterms 25 %, Final 35%

Textbook: Discrete-time Signal Processing 2nd edition by Oppenheim and Schafer.

Course Assistants: U. Orguner, A.Koz

Course Outline

  1. Introduction to DSP- What, Why and How.
  2. Signals and Systems Review
  3. Z-transformation
  4. Discrete Fourier Transform, DFT
  5. Sampling, A/D, D/A conversion, Decimation and Interpolation, Multirate Signal Processing
  6. Transform Analysis of LTI Systems
  7. Structures for DT Systems
  8. Filter Design Techniques, IIR and FIR filter design
  9. Fast Fourier Transform, FFT
  10. Discrete Hilbert Transform
  11. Applications of Signal Processing

 

Homeworks:

Usually there will be a homework for every week. Homeworks will have two parts, namely the written part and a Matlab part. The process of actively struggling with an assignment is one of the most important educational experiences that you will have in this course. Your main incentive for consistently doing the assignments should be to enhance your comprehension of the material. Written homework will be assigned related to the topics covered during the lectures. It is very beneficiary for the student to put some individual work on these. Late homework will not be accepted.

 

We will extensively use Matlab which is a programming language and data visualization tool. It is widely used in Signal Processing and Communications Systems designs. Matlab problems will enhance your understanding of the course material. In addition, it will give you a concrete idea of the practical applications and use of Signal Processing theory. Matlab assignments will be returned by submitting :

  1. A hard copy of the .m files
  2. A hard copy of the results of the .m files (plots, tables, matrices, etc.)

Expectations:

We expect you to make an honest effort to do the homework and submit on time. Also we expect that the work you submit to us under your name is yours. Interactions of students on the problems are useful and are encouraged, but each person should work out his/her solution. Copying from others is immature, dishonest and waste of everyone’s time.