Course Program:
Introduction to discrete and continuous time signals and systems with computer engineering applications. Time-domain signal representations, impulse response of linear time-invariant systems; convolution. Fourier series. Spectrum representation of signals. Fourier transform. Digital signals and sampling. Reconstruction. Filtering. Z-transform representation. Discrete Fourier transform. Algorithms for signal processing. Floating point and quantization errors. Exercises with applications in audio and image processing.
Prerequisites: MATH 202
Course Objectives: As part of this course, students:
1. will understand mathematical representation of discrete-time and continuous-time signals.
2. will be introduced to signal processing and characterization techniques, such as filtering, frequency response
3. Gain laboratory experience in computer-based signal processing.
Textbook: McClellan, Shafer, and Yoder, Signal Processing First, Prentice Hall, 2003.
MATLAB: http://www.mathworks.com/help/pdf_doc/matlab/getstart.pdf
Read: A. V. Openheim, A. S. Willsky, Signals and Systems (2ed), Prentice Hall 1996
Instructor: Fatih.Alagozboun.edu.tr; TA: Beyza.Ermis
boun.edu.tr, VA: Gul.varol
boun.edu.tr
Tel: 359 6652, ETA Room 42
Topics:
• Introduction
• Signal processing applications in computer engineering
• Basics of continuous-time and discrete-time signals and systems.
• Floating point representation, quantization errors
• Linear time-invariant systems; Convolution.
• Fourier Series representation of continuous-time and discrete-time Periodic signals; properties of Fourier series; filtering concepts.
• The continuous time Fourier transform and its properties
• The Fourier transform for periodic signals.
• Sampling and discretization of continuous-time signals.
• The z-transform and its properties
• Analysis of discrete-time systems using z-transform
• The discrete-time Fourier transform and its properties
• Algorithms for signal and image processing
• Applications
Grading: 5-6 sets of homework problems, which contain laboratory exercises based on MATLAB, in addition to regular homework exercises. There are two in-class mid-term exams and a final exam.
Tentative Grading Policy: 30% of (Projects, Homeworks, Quiz), 20% of Midterm1, 20% of Midterm2, and 30% of Final exam.
IMPORTANT NOTE:
Score 1 = (0.30×(Projects and/or HWs and/or Quiz) + 0.40 × Midterm Exams Result) / 0.70
Score 1 values will be used to rank students. Students who get reasonably high Score 1 values will earn the right to take the final exam. Students who get low Score 1 values will not earn the right to take the final exam and will automatically receive F from this course.
Score 1 = (0.30×Projects,HWs,Quiz Average + 0.40×Midterm Exams Result+ 0.30xFinal Exam Result
Score 2 values will be used to rank the students who receive the final exam. Students who get reasonably high Score 2 values will manage to earn a passing letter grade such as AA, BA, BB, CB, CC, DC, or DD. Students who get low Score 2 values will receive F. Students who receive F based on their Score 2 values will have the right to attend to the final make-up exam (bütünleme). The students who earn the right, but do not attend to the final exam will also have the right to take the final make-up exam given that they have a valid reason.
Prepared by: Prof. Dr. Fatih Alagoz
Date: February 2013