Introduction

DIGITAL SIGNAL PROCESSING

Course information

INSTRUCTOR

• Khalida Noori• Khalida.noori@seecs.ed

u.pk

CONSULTATION HOURS

• Wednesday 11:00-01:00 hrs

BOOKS

• Discrete Time Signal Processing byAlan V. Oppenheim, Ronald W. Schafer with John R. Buck, 2nd Edition, Prentice Hall

• Digital Sinal Processing-A computer based approach by S.K. Mitra, Mc Graw-Hill, 1998

• Digital Signal Processing – Principles, Algorithms and Applications – Third Edition by John G.Proakis and Dimitris G.Manolakis

MATERIAL RESOURCES

• http://www.seecs.edu.pk/~khalida.noori/courses

PRE_REQUISITS

•Basic concepts in signals & systems•Frequency response of linear systems

•Laplace, Z and Fourier Transforms

Course information(C0ntd..)

GRADING POLICES

• One hour test 30%

• Final 40%• Quizzes 10%• Assignments and Lab work

10%• Semester Project

10%

Discrete Time signal

• Sequence x[n] as opposed to continuous time signals x(t)

Discrete in Nature• Population statistics

• Stock market indices

Sampled continuos time (analog) signals

o Example• Speech

Applications•R

ecognition, synthesis(e.g Automatic speakers)

Speech

•Recording, playback, mixing, storage (e.g CD player)

Music

•2-D filtering, enhancement, compression, pattern recognition (e.g satellite images)

Image Processing

•Dagnosis, patient monitoring (e.g ECG analysis, X-Ray storage/enhancement)

Bio Medicine

•filtering, detection, feature extraction, localization, tracking, identification (e.g air traffic control, military)

Communication and Multimedia

•signal generation, transmission, modulation and compression, echo cancellation, data protection via error correcting signal coding (e.g digital modems, digital TV, mobile phones, video conferencing & internet, digital cameras)

Radar

Speech Processing

Original speech

Down sample

High pass

Low pass

Up sample

Image Processing

Video Processing

MotionAnalysis

VideoSynthesis

Object 1

Object 2

General Concept:

ApplicationsAnalysis

Discrete-Time System

x (n) T y(n)

y(n)=T{x(n)}

Why DTSP? Discrete Time Signal Processing of Continuous

SignalsC/D

• C/D

DTSP

• DTSP

D/C

x (t)

y(t)x (n)

y (n)

Why DTSP?Digital Signal Processing (DSP) is derived from DTSP

A/D

DSP

D/A

x(t) x(n) y(n) y(n)

Discrete Time Signal

Where Not?

DSP COMPONENTS

• Converting analog signal into digital sequence.• Performing all signal processing operations in digital in digital

form.• If necessary converting the digital information back to analog

signal.

• A TYPICAL DSP SCHEME

DACDSP

Processor

ADCAnalog Filter

Analog Filter

WHY DSP?

Flexibility Reproducibility

Reliability Complexity

Frequency Selective Filtering

Echo Cancellation

DSP SOLUTION TO EC

Equalization

Speech Transmission

Image Processing

Image Processing

DSP in real time embedded systems

Comparison of Chips

ASIC

FPGA

DSP

µP

FLEXIBILITY

POWER

CONSUMPTION

Comparison of ChipsASIC FPGA µP/µC DSP

Processor

Flexibility None Limited High High

Design Time Long Medium Short Short

Power Consumption

Low Low- Medium Medium- High

Low- Medium

Performance High High Low Medium Medium-High

Development Cost

High Medium Low Low

Production Cost

Low Low- Medium Medium-High Low-Medium

Course Outline1

• Review of discrete time signal and system; Discrete Time Fourier Transform (DTFT);z-Transform; sampling of continuous time signals

2 • More about sampling: DT/digital processing of analog signal; multirate DTSP

3 • Frequency domain analysis of LTI system

4 • Structure for DT system: signal flow graphs, implementation and noise issues

5 • Design of DT filters

6 • Practical computation of DTFT: the discrete Fourier transform(DFT), computation of the DFT (FFT)

Course Outline

Course Outline• DSP: A/D,D/A• System Design and Implementation

• Practical computation of F