Introduction

ADC ES MUET 1

Course Description

Title of Subject : Analog & Digital Communication

Disciplines : Electronic Engineering

Term : (6th Term)

Effective : 09ES-Batch and onwards

Pre-requisites : - Co-requisite: -

Assessment :

Sessional Work: 20% Written Examination: 80%

Marks : Theory: 100 Practical: 50

Credit Hours : 4 2

Minimum Contact

Hours : 52 26

ADC ES MUET 2

Sessional Work

?? Quizzes

?? Assignments

2 Class tests

(Aims & objectives of this course + recommended

books available on the website:

http://www.muet.edu.pk/departments/electronics-

engineering/course-outline)

ADC ES MUET 3

About me

Khuhed Memon

(Lecturer Dept of ES MUET)

MS Signal Processing (Nanyang Technological

University, Singapore)

BE Electronics (Pakistan Navy Engineering

College, National University of Sciences &

Technology, Pakistan)

ADC ES MUET 4

Class style

Interactive:

Discussions + questions in class, email,

office..

ADC ES MUET 5

Contact Info:

Office: OIC Basic Electronics Lab

E-mail: khuhedkk@hotmail.com

*best way to communicate : e-mail

ADC ES MUET 6

Enjoy the course

ADC ES MUET 7

ADC ES MUET 8

This lecture

Concept of Signal Processing

Introduction to Signals

Classification of Signals

Basic elements of SP System

Analog to Digital Conversion Sampling

Quantization

Nyquist Theorem

Applications of Signal Processing

ADC ES MUET 9

Signal Processing

Representation, transformation,

manipulation of signals and the information

they contain.

Classification:

Depends upon the type of signal to be

processed. Analog Signal Processing

Digital Signal Processing

ADC ES MUET 10

Signal Processing

Analog SP

Continuous time signals are processed.

Digital SP

Discrete - time discrete - valued signals

processed by digital computers or other data

processing machines.

ADC ES MUET 11

Signal??

Any indication / information

A change in which some information is

residing

ADC ES MUET 12

Classification of Signals

Continuous-time / Discrete-time Signals

Continuous-valued / Discrete-valued

Signals

Deterministic / Random Signals

One-dimensional / Multi-dimensional

Signals

ADC ES MUET 13

Fundamental SP system

Most signals Analog in nature.

Analog to Digital Converter is used as an

interface between analog signal and Digital

Signal Processor.

A/D Converter D/A ConverterDigital Signal

Processor

Analog

Input Signal

Analog

Output Signal

ADC ES MUET 14

A-D Conversion

1. Sampling

First step in going from analog to digital.

In signal processing, sampling is the reduction of a continuous signal to a discrete signal. A common example is the conversion of a sound wave (a continuous-time signal) to a sequence of samples (a discrete-time signal).

ADC ES MUET 15

Sampling

ADC ES MUET 16

ADC ES MUET 17

ADC ES MUET 18

Nyquist Theorem

In order the samples represent correctly the

analog signal, the sampling frequency must

be greater than twice the maximum

frequency of the analog signal:

fs2FM

The limiting frequency 2FM is called

Nyquist rate.

ADC ES MUET 19

Aliasing (Time Domain)

ADC ES MUET 20

Aliasing (Frequency Domain)

ADC ES MUET 21

Methods of avoiding Aliasing

To avoid aliasing, there are two approaches:

One is to raise the sampling frequency to satisfy the sampling theorem.

The other is to filter off the unnecessary high-frequency components from the continuous-time signal. We limit the signal frequency by an effective low-pass filter, called anti-aliasing prefilter, so that the highest frequency left in the signal is less than half of the intended sampling rate.

ADC ES MUET 22

General DSP System

ADC ES MUET 23

Quantization

Slide 143 CCN module 2

MIT OCW

Companding or Non-linear

Encoding

Companding = compressing + expanding

Why companding?

Quantization levels not evenly spaced

Reduces overall signal distortion

Can also be done by companding

ADC 24ES MUET

ADC 25ES MUET

ADC 26ES MUET

ADC 27ES MUET

ADC 28ES MUET

ADC ES MUET 29

Applications of SP

RADAR

SONAR

Medical

Image Processing Pattern recognition

Edge detection

Audio Signal Processing Speech generation

Speech recognition

Speaker identification

Telecommunications Multiplexing

Compression

Echo control