COMM 602

Digital Signal Processing

Lecture 1

Dr. Engy Aly MaherSpring 2020

Course Instructor

• Dr. Engy Aly Maher

• E-mail: engy.aly@guc.edu.eg

• Office: C3-317

• Office Hours: By appointment

Textbook & References

• John G. Proakis, Dimitris Manolakis, “Digital Signal

Processing: Principles, Algorithms and Applications”, 4th

Edition, Prentice Hall

• Steven W. Smith, “The Scientist and Engineer's Guide to Digital

Signal Processing” (available online : http://www.dspguide.com)

• Robert D. Strum and Donald E. Kirk,“First Principles of Discrete

Systems and Digital Signal Processing”, Addison Wesley

• Richard G. Lyons, “Understanding Digital Signal Processing”,

Pearson Education

• Vinay Ingle and John G.Proakis, “Digital Signal Processing Using

MATLAB”, Thomson-Engineering

• Prof. Ahmed ElMahdy – COMM 602 DSP Slides

Course Objectives

By the end of the course, we will develop a solid understanding of DSP

fundamentals including:

• Analog vs. digital signal representation and processing

• Why DSP? advantages, limitations and fundamental tradeoffs

• Relationship between frequency and time representations

• Analysis and processing of signals in the temporal/spatial as well as

in the frequency domain

• Practical applications of DSP

• Implementation of DSP algorithms using MATLAB

Course Topics

• Discrete-time signals and systems

• Linear time-invariant (LTI) systems and their properties

• The Z-transform and its application in the analysis of LTI systems

• Frequency domain representations including Discrete Fourier

transform (DFT) and fast Fourier transform (FFT)

• Design of digital filters (FIR, IIR)

Evaluation

• Assignments: 10%

• Quizzes: 20%

• Matlab Practical Assignment: 5%

• Midterm exam: 25%

• Final Exam: 40%

Introduction to

Digital Signal Processing

DSP Scenario

Why DSP?

• digital data storage and transmission is much moreeffective than in the analogue form

• flexibility: processing functions can be altered oradjusted

• possibility of implementing much more complicatedprocessing functions than in analogue devices

• efficient implementation of fast algorithms and matrix-based processing

• speed of digital operation tends to grow rapidly with theyears of technical progress

• a very high accuracy and reliability is possible toachieve

• dynamic range can be increased

• signal multiplexing: simultaneous (parallel) processing

Applications

• Music: recording, playback, mixing, synthesis, storage (e.g. CD-

players)

• Speech: recognition, synthesis (e.g. automatic speakers)

• Communications and multimedia: signal generation, transmission,

modulation and compression, data protection via error-correcting

signal coding, (e.g. digital modems, TV and telephony, computers,

video conferencing and lnternet)

• Radar: filtering, detection, feature extraction, localization, tracking,

identification (e.g. air-traffic control)

• Image processing: 2D filtering, enhancement, compression, pattern

recognition (e.g. satellite images)

• Biomedicine: diagnosis, patient monitoring, preventive care

Definition

• Signal :

A function of independent variables such as time, distance,

position, temperature and pressure.

Signals are analog in nature (continuous) such as human voice,

electrical signal (voltage or current), radio wave, optical, audio, and so

on which contains a stream of information or data. Or may be discrete

such as temperature, stock, etc.

• Processing :

Operating in some fashion on signal to extract

some useful information

ADC

ADC

Sampling Theorem and Aliasing

Sampling Theorem and Aliasing

Types of Signals

Representation of Discrete Signals

Important Discrete Time Signals

Important Discrete Time Signals

Important Discrete Time Signals

Important Discrete Time Signals

Important Discrete Time Signals

Mathematical Formulas for the

exponential signals

Important Discrete Time Signals

Operations on Signals

Operations on Signals

Operations on Signals

Operations on Signals

Operations on Signals

Example:-

Energy and Power

Periodic Signals

Even & Odd Signals

Discrete System or Digital system

Basic System Properties

Basic System Properties

Basic System Properties

Basic System Properties

Basic System Properties

Basic System Properties

Basic System Properties