EE 473   Title: IntroductIon to DIgItal SIgnal ProcessIng   Credits: 3   Catalog Description: Sampling and quantization schemes. Linear shift invariant systems, stability and causality. Two-dimensional systems and sequences. Flow graphs, digital filter design techniques, FIR and IIR filters. Computation of DFT, FFT techniques. Effects of finite register length. Estimation of power spectra. Homomorphic filtering, discrete time random signals and systems.   Coordinator: M. Levent Arslan, Professor of Electrical Engineering   Goals: To learn the necessary tools for analysing digital signals. To learn how to design a digital signal processing system for a  given problem considering the trade offs in the system design process.   Learning Objectives: At the end of this course the students will be able to: Digitize an analog signal with appropriate sampling rate Use FFT to analyse spectrum of a given signal Design a suitable digital filter given specific requirements Textbook: J.G. Proakis & D. Manolakis, Digital Signal Processing, 3rd edition , Prentice Hall.   Reference Texts:  Oppenheim & Schafer, Discrete-Time Signal Processing, 2nd edition , Prentice Hall V.K. Ingle, J.G. Proakis, Digital Signal Processing using MATLAB Prerequisites by Topics: Signals and Systems Calculus Probability Topics: Introduction + MATLAB Tutorial (1 week) Discrete Time Signals and Systems (1 week) Z-Transform (1 week) Frequency Analysis of Signals and Systems (2 weeks) Discrete Fourier Transform (2 weeks) Fast Fourier Transform (1 week) Filter Structures (1 week) Filter Design Techniques (2 weeks) Applications of Digital Signal Processing (1 week) Course Structure:  The class meets for two lectures a week --  one lecture consists of  a two-hour session and the second lecture is a one-hour.  There is also a MATLAB training session at the PC Lab. At the PC lab the students write MATLAB codes on their own as the teaching assistant shows them. They are also asked to solve some of the simple problems on their own. There is a semester project assigned to groups of 2-3 students. In the projects, students are expected to apply the techniques that they learned at the class.   Computer Resources: Homeworks require MATLAB programming Semester project requiring MATLAB or C or C++ programming Laboratory Resources: BUSIM Laboratory & Dağ Özay PC Lab   Grading: Midterm %25 Final exam %35 Semester project %25 Homeworks %15 Semester Project Topics: You can start working on your semester project anytime. Semester project groups are limited to 5 students minimum, 6 students maximum. If there are more students in the group the expectation will be higher in terms of the complexity of the project. You can choose your topic for the semester project. Below are some of the proposed topics: Implementation of a graphic equalizer for music. System Identification for a Pole-Zero system. Noise reduction. Linear Predictive Coding Dual Tone Multifrequency (DTMF) Detection Implementation of a general-purpose filter design package. Implementation of a "sound effects studio package" (i.e., disco, stadium, pop, jazz effects) Image compression Edge Detection Radar Signal Detector Speech coding Outcome Coverage: An ability to apply knowledge of mathematics. Signals and systems and Z-transfrom theory. An ability to analyze and interpret digital signals in terms of their frequency characteristics An ability to design a digital filter that meets specific requirements An ability to communicate effectively. . In the semester projects students are asked to present their work with a Power Point presentation, and also write a project report. Therefore there is a chance to improve both oral and written communication skills. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. This is assessed in the semester project. Project topics require either MATLAB programming or C/C++ programming skills. Prepared By: Levent M. Arslan   Last Revised:  Nov 10, 2003