2. Digital Signal Processing Using MATLAB®V.4 Associate Prof. Supervisor of Master Degree Student LILI Office: Room 402, Electromechanic Building Email: lili7312@gmail.com

3. 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

4. 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

5. 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

6. 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

8. 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

9. DSP PrF: antialiasing filtering PoF: smooth out the staircase waveform

10. 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

11. 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

12. > load handel; %the signal is in y and sampling freq in Fs sound (y,Fs);pause(10);% play the original sound alpha=0.9;D=4196;% Echo parameters b=[1,zeros(1,D),alpha];% Filter parameters x=filter(b,1,y);%Generate sound plus its echo sound(x,Fs);%Play sound with echo Matlab example1: Echo generation

13. >w=filter(1,b,x); sound(w,Fs) Matlab example2: Echo removal

14. 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).