Digital Signal Processing
CSE - 610
Lecture # 1: Introduction
Dr. Muhammad Shehzad Hanif
shehzad.hanif@uet.edu.pk
Department of Mechatronics and Control Engineering
University of Engineering and Technology, Lahore
What is a signal?
A signal conveys information about the state or
behavior of a physical system
It is a measured quantity that varies with time (or
position)
Examples:
Voltage: Represented as a function over time 1D signal
Image signal: Represented as an intensity function of two spatial
variables 2D signal
Video signal: A sequence of images spanning over a period of time
3D signal
2
Signal Processing
Signal processing is concerned with the
representation, transformation, and manipulation of
signals and the information they contain.
3
Types of signals
Continuous-Time (CT) or Analog signal:
Example: Voltage, Current, Speech signal, etc.
Discrete-Time (DT) signal:
Example: Daily stock market price, Daily average
temperature, Sampled continuous signals
4
Discrete-Time (DT) signal: Example
Stock market data
Population
5
Discrete-Time (DT) signal: Example
Temperature measurements
6
Discrete-Time (DT) signal: Example
Sampled continuous time signal
Speech signal and its sampled version
7
Discrete Time Signal
Discrete time signal x[n]
8
Discrete Time System
9
Discrete Time Signal Processing
(DTSP)
Discrete time processing of continuous signals
10
Digital Signal Processing (DSP)
Digital signals processing (DSP) is derived from
DTSP
11
Discrete Time Signal
12
Digital Signal = Discrete Time
Discrete Amplitude Signal
13
Sampling of Signal: Ambiguity
14
DSP Scheme
Converting analog signal into a digital signal
Perform signal processing operations in the digital
form
Convert back the digital signal to analog one when
necessary
Analog Analog
Input Output
Analog DSP Analog
ADC DAC Filter
Filter Processor
15
Why Process The Signals Digitally?
Digital data storage and transmission is more effective than in
the analog form
Flexibility: Processing function can be modified or adjusted
Can implement very complex processing functions
Speed of digital operations tends to grow rapidly with the years
of technical progress
A very high accuracy and reliability is possible
Dynamic range can be increased
Simultaneous (Parallel) processing
16
DSP Market
DSP Revenues
25 34.7% CAGR 50%
20 40%
Revenue ($B)
% Change
15 30%
10 20%
5 10%
0 0%
98 99 00 01 02 03 04
Year
Revenue ($B) % Change
17
Source: http://bwrc.eecs.berkeley.edu/People/Grad_Students/czhong/documents/Opportunity%20in%20DSP%20ver%204.doc
Why Do DSP Processors Need to Do
Well?
Most DSP tasks require:
Repetitive numeric calculations
Attention to numeric fidelity
Fixed- vs. floating-point
Standards
High memory bandwidth
Streaming data
Real-time processing
Processors must perform these tasks efficiently while
minimizing:
Cost
Power consumption
Memory use
Development time
18
Benchmark
Implementation of Complex Block FIR Filter
DSP vs. High Performance CPU
(lower is better)
19
Example DSP Applications
Digital cell phones Satellite communications
Automated inspection Seismic analysis
Vehicle collision Secure communications
avoidance Tapeless answering
Voice -over-Internet machines
Motor control Sonar
Consumer audio Cordless phones
Voice mail Digital cameras
Navigation equipment Modems (POTS, ISDN,
Audio production cable, ...)
Videoconferencing Noise cancellation
Toys, games consoles Medical ultrasound
Music synthesis, effects Patient monitoring
Radar
20
And more to come...
Original speech signal
Speech Processing
Lowpass filter
Downsample
Highpass filter
21
Echo Cancellation
Echo-path in switched telephony network
Echo-path in hands-free communication
22
Echo Cancellation (2)
Solution: Recreate the echo signal and subtract it
from the sent signal
23
Equalization
Selectively enhance/attenuate
some parts of the frequency
spectrum
Applications
Coding & compression
Room simulation
Echo or chorus effects
24
Time Series Prediction
Predict the next value of a time series from its
past samples:
x[n 1] f ( x[0], x[1], , x[n])
Solution: Prediction filter
25
Speech Transmission
26
Image Processing
27
Image Processing
28
Signal Interpretation
The objective of the processing is not to obtain an
output signal but to obtain a characterization of
the input signal
Example: Speaker Identification
Database of
Attributes
Signal Attribute
Attributes
Interpretation Matching
Complete System = Signal Processing + Pattern Recognition
Speaker
29
Course Outline
Introduction: Continuous Time (CT) and Discrete Time (DT)
signals and systems
Basics of signal conditioning & processing
Signal representation
Sampling of CT signals (A/D and D/A conversion, Multi-rate signal
processing)
Linear Time Invariant (LTI) systems
Convolution
Fourier Transform
Z- Transforms
Analysis of LTI systems
Filter design techniques and implementation (FIR and IIR filter
structures)
Discrete Fourier Transform (DFT)
Computation via FFT
Applications of DFT
30
Course Outline
Pre-requisite: Introductory knowledge of signals and systems
Course meeting times
Lectures: 1 session/week (3 hours on Wednesday 2pm - 5pm)
Course teacher
Dr. Muhammad Shehzad Hanif
Mechatronics Lab, 1st Floor, Research Center,
University of Engineering and Technology, Lahore, Pakistan.
Email: shehzad.hanif@uet.edu.pk
Office hours
Monday - Saturday 0800 – 1500 HRS
31
Group for Course
Subscribe to digital signal processing group by sending an
email to cse_610_fall_2010-subscribe@yahoogroups.com
Group website is
http://groups.yahoo.com/group/cse_610_fall_2010/
Lectures slides, assignments (computer/written), solution
to problems, research papers, projects, and
announcements will be uploaded to group repository and
will be notified to all group members through email
32
Grading & Evaluation
Activities Percentage
Quizzes 20%
Mid Term 30%
Final 40%
Homework 5%
Computer Assignments 5%
A minimum of 75% attendance is necessary in order to avoid
drop-out from the course
Homework: Problem sets will be assigned every one to two
weeks, to be turned in at the beginning of the class when they
are due
Computer assignments: A component of the homework will be
computer assignments using MATLAB. You are required to send
your MATLAB codes and results to shehzad.hanif@uet.edu.pk
when they are due
33
Text and Reference Books
Text book
Discrete-Time Signal Processing
by Alan V. Oppenheim, Ronald W. Schafer & John R. Buck. 2nd
Edition, Pearson Education - Prentice Hall, 1999
(Local edition is available)
Reference books
Digital Signal Processing: Principles, Algorithms and
Applications
by J. G. Proakis and D. G. Manolakis. 3rd Edition, Prentice-
Hall, 1995
Digital Signal Processing, A Computer-Based Approach
by S. K. Mitra. 2nd Edition, McGraw-Hill, 2001 (contains
many MATLAB examples)
34
References
Chapter # 1, Discrete-Time Signal Processing
by Alan V. Oppenheim, Ronald W. Schafer &
John R. Buck. 2nd Edition, Pearson Education -
Prentice Hall, 1999
50
