Digital Signal ProcessingUsing MATLAB®V.4

Associate Prof. Supervisor of Master Degree StudentLILIOffice: Room 402, Electromechanic BuildingEmail: lili7312@gmail.com

Teaching method on SP Simple “lecture-only” Integrated “lecture-laboratory” Computer-based explanations, examples and exercises

Matlab software Developed by Math Works Inc. De facto standard for numerical computation in the SP Available on all computing platform

PREFACE

PREFACE

This book Integrating Matlab with traditional topics on DSP Use Matlab to explore difficult topics and solve

problems to gain insight Matlab provides a convenient tool so that many

scenarios can be tried with ease Enhance the learning process Assume that the student is familiar with the

fundamental of MATLAB

PREFACE Organization of the Book

Chapter 1, Introduction Chapter 2, Discrete-time Signals and Systems Chapter 3, The Discrete-time Fourier Analysis Chapter 4, The Z-Transform Chapter 5, The Discrete Fourier Transform Chapter 6, Digital Filter Structures Chapter 7, FIR Filter Design Chapter 8, IIR Filter Design

INTRODUCTION The field of DSP has grown to be important

both theoretically and technologically. Development and use of low-cost software and hardware New tech. and app. take advantage of DSP algorithms Make DSP an integral part of any E.E. curriculum

256Hz Audio

EEG

Why signals should be processed?

Signals are carriers of information Useful and unwanted Extracting, enhancing, storing and transmitting

the useful information How signals are being processed?---

Analog Signal Processing vs. Digital Signal Processing

DSP

PrF ADC DSP DAC PoFAnalog Analog

Equivalent analog signal processor

PrF: antialiasing filtering

PoF: smooth out the staircase waveform

Comparison of DSP over ASP

-Advantages Developed Using Software on Computer; Working Extremely Stable; Easily Modified in Real Time ; Low Cost and Portable;

-Disdvantages Lower Speed and Lower Frequency

The two categories of DSP Tasks Signal Analysis:

Measurement of signal properties Spectrum(frequency/phase) analysis Target detection, verification, recognition

Signal Filtering Signal-in-signal-out, filter Removal of noise/interference Separation of frequency bands

> load handel; %the signal is in y and sampling freq in Fssound (y,Fs);pause(10);% play the original soundalpha=0.9;D=4196;% Echo parametersb=[1,zeros(1,D),alpha];% Filter parametersx=filter(b,1,y);%Generate sound plus its echosound(x,Fs);%Play sound with echo

Matlab example1: Echo generation

[ ] [ ] [ ]x n y n y n D

>w=filter(1,b,x);sound(w,Fs)

Matlab example2: Echo removal

[ ] [ ] [ ]n n D x n

Grading Policy

80% from Project and Class presentation -- see description below

20% from Homework, Lab, etc. Project: A team-oriented class project will be assigned in the latter

half of the semester in order to provide students with the opportunity to explore fundamental issues, key technologies, and emerging challenges in data and computer communications. Students will be permitted to select their project topic, and their team membership, both subject to instructor approval. Several options for project topics are anticipated through experimental, simulative, or analytical means. The final results of the project must include paper (for one group) and oral presentation (for each student).