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Telecommunication and Internet Engineering, School of Engineering, South Bank University. Digital signal Processing ECI-3-832. Semester 1 2003 /2004. Coordinator. Dr. Z. Zhao Room: T409 Tel: 0207 815 6340 Email: zhaoza@lsbu.ac.uk. Textbook.

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Digital signal processing eci 3 832

Telecommunication and Internet Engineering, School of Engineering,

South Bank University

Digital signal ProcessingECI-3-832

Semester 1 2003/2004


Coordinator
Coordinator Engineering,

  • Dr. Z. Zhao

  • Room: T409

  • Tel: 0207 815 6340

  • Email: zhaoza@lsbu.ac.uk


Textbook
Textbook Engineering,

  • Alan V. Oppenheim, Ronald W. Schafer, Discrete-time Signal Processing, 2ed, Prentice Hall, ISBN: 0-13-083443-2


Unit structure
Unit Structure Engineering,

  • 1.    Introduction to DSP

  • 2.    Discrete-time signals

  • 3.    Discrete-time systems

  • 4.    The z-transform and the Fourier transforms of discrete-time signals

  • 5.    The discrete Fourier transform (DFT) and its efficient computation (FFT)

  • 6.    Digital filters


Unit calendar
Unit Calendar Engineering,

(Changes possible)

  • Introduction to DSP 1

  • Discrete-time signals 1-2

  • Discrete-time systems 3-4

  • The z-transform and the Fourier transforms 5-7

    of discrete-time signals

  • The discrete Fourier transform (DFT) and 8-10

    its efficient computation (FFT)

  • Digital filters 12

  • Revision 13

  • Examination 14-15


Teaching and learning methods
Teaching and Learning Methods Engineering,

  • Lecture: 2 hour each week

  • Tutorial: 2 hour on Even weeks

  • Laboratory work (Matlab exercises):2 hour of on odd weeks

  • Self learning: 102 hours


Assessment
Assessment Engineering,

  • 3-hour written examination: 75%

  • Workshop assignment: 25%

    1. log book

    2. formal written reports

    3. Submit: J200 between 10:00 and 16:00, following the standard school procedure.


Introduction to dsp
Introduction to DSP Engineering,

1.1 What is DSP?

DSP, or Digital Signal Processing,

is concerned with the use of programmable digital hardware and software (digital systems) to perform mathematical operations on a sequence of discrete numbers (a digital signal).


Introduction to dsp1

Anti-aliasing filter Engineering,

DSP

A/D

Reconstruction filter

D/A

Introduction to DSP

1.2 A General DSP System

Analog

signal

Analog

signal

Digital

signal

Digital

signal

Analog

signal

Analog

signal


An Example Engineering,


Introduction to dsp2
Introduction to DSP Engineering,

1.3 Advantages:

  • Programmable

  • Well-defined, stable, and repeatable

  • Manipulating data in the digital domian provides high immunity from noise

  • Use of computer algorithms allows implementation of functions and features that are impossible with analog methods


Introduction to dsp3
Introduction to DSP Engineering,

1.4 Disadvantages:

  • Relatively low bandwidths

  • Signal resolution is limited by the D/A and A/D converters.


Introduction to dsp4
Introduction to DSP Engineering,

1.5 Applications:

  • digital sound recording such as CD and DAT

  • speech and compression for telecommucation and storage

  • implementation of wireline and radio modems

  • image enhancement and compression

  • speech synthesis and speech recognition


What is dsp used for
What is DSP Used For? Engineering,

…And much more!


Speech recognition system

Word Engineering,

pronunciation

Phoneme

models

Semantic

knowledge

Feature

extraction

Phoneme

recognition

Word

recognition

Sentence

recognition

speech

decision

Dialogue

knowledge

Syntactic

knowledge

Speech Recognition System


Text to speech synthesis

To be or Engineering,

not to be

that is the

question

Input

text

Tu bee awr

nawt tu bee

dhat iz dhe

kwestchun

phonetic form

Text

normalization

Parsing

Pronunciation

semantic &

syntactic ‘parts

of speech’

analysis of text

phonetic description

of each word, dictionary

with letter-to-sound

rules as a back up

expands

abbreviations

dates, times,

money..etc

Prosody

rules

Waveform

generation

Synthesized

speech

Apply word

stress, duration

and pitch

Phonetic-to-

acoustic

transformation

Text-to-Speech Synthesis


Speech coding vocoder

Encoder Engineering,

Original Speech

  • Analysis:

  • Voiced/Unvoiced decision

  • Pitch Period (voiced only)

  • Signal power (Gain)

Decoder

PitchPeriod

Signal Power

Pulse Train

V/U

Vocal TractModel

Synthesized Speech

LPC-10:

Random Noise

Speech Coding – Vocoder


Jpeg example

Original Engineering,

JPEG (4:1)

JPEG (100:1)

JPEG Example


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