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تحميل الدليل التدريبي

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CEN 543

First Semester 1437-1438H

Digital Signal Processing 

 

CEN 543 – Digital Signal Processing (3-0-0), Masters Course

Course Description (catalog):

 Review of linear time invariant systems, discrete time signals, discrete Fourier transforms (DFT), Fast Fourier transforms (FFT), Z-transforms, design of finite impulse response filter (FIR) and Infinite impulse response filter (IIR), adaptive filters, application on audio and image processing.

Textbook(s) and/or Other Required Materials:

Primary:               A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing, Third Edition, Prentice Hall.

Supplementary: (1) Li Tan, Digital Signal Processing: Fundamentals and Applications, 2008, AP, Elsevier, (2) Steven W. Smith, The Scientist and Engineer's Guide to Digital Signal Processing, 1997, California Technical Publishing.

Pre-requisite: CEN 340 Signals and systems.

Course Learning Objectives:  This course is designed to help the student:

1)     Realize sampling and quantization on digital signals.

2)     Perform discrete convolution and correlation.

3)     Analyze signals using DFT and FFT.

4)     Analyze signals using Z-transform.

5)     Implement digital filters.

6)     Apply filters in speech and image signal processing.

Course Grade

Homework & Unannounced Quizzes

10%

Midterm exam  

30%

Project

20%

Final Exam

40%

Announcement:

Z-Transform

Mid-Term: Monday 11/4/2016 from 1:00 PM-3:45 PM.

All registered students should have the background for this course which is either they have successfully passed the prerequisite CEN340 (Signal and Systems) or   their B.Sc. is in the computer engineering (or in the electrical engineering).

Projects:

Project Title

Using Kalman filter for object tracking

Noise removal and smoothing in digital images (Spatial Domain)

Noise removal and smoothing in digital images (Frequency  Domain)

Speech processing (filtering)

Design and simulation of Direct sequence spread spectrum (DSSS) system using MATLAB

image compression using Huffman coding

"Object Detection and Identification Based on Feature Matching"

Steps of the project:

1.      Introduction to the problem to be studied+ Literature review,

2.      Proposed solution,

3.      Experiment results,

4.      Analyze the results,

5.      Conclusion,

6.      References.

https://www.adelaide.edu.au/writingcentre/learning_guides/learningGuide_writingAResearchReport.pdf

Handout

Chapter 1:

 Chapter 2

Chapter 3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 
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