1. Signals & Systems B-Tech (Hons)

2. Signals & Systems Lecture # 1 Instructor Engr. Kashif Shahzad 2015

3. Course Details  Text Book: Discrete Time Signal Processing by Alan V. Oppenheim & Ronald W. Schafer  Course Instructor: Kashif Shahzad Email: kashifshahzad31@yahoo.comkashifshahzad31@yahoo.com Cell: +92 333 5186231  Course homepage: http://kashifshahzad31.wordpress.com

4. Course Breakdown  Assignments:10%  Quizzes:10%  Others:05%  Mid Term:25%  Terminal:50%

5. DSP Introduction Application of mathematical operations to digitally represented signals INOUT A/DD/ADSP -3-2 01234 x[0] x[1] n

6. General Introduction Discrete Time Signal sequence x[n] - as opposed to continuous-time signals x(t) - “time” = independent variable

7. Examples Discrete in Nature - stock market indices NasDaq daily closing value from Aug 1995 to Jan 1996 - population statistics Birth in Canada from 1995-1996 to 1999-2000

8. Example Sampled continuous-time (analog) signals - Speech

9. Digital Images 2-D arrays (matrices) of numbers

10. Typical DSP Applications

11. Example: Speech Modeling Impulse Train Generator Noise Generator Pitch Period × u(n) Time- varying digital filter Vocal Tract Parameters s(n) G

12. An Embedded System

13. Example Embedded System

14. SDR Board Design

15. Device 0 Data Waveform 1 Software Defined Radio All configurable HW FPGA Device 4 Device 1 DSP General Purpose Processor Algo4 Proprietary ½ FEC Framer 1 V.35 16 QAM OFDM

16. COTS SDR Platform Key Features 1.DSP core from TI 2.FPGA from Xilinx 3.Dual-channel analog-to-digital converter 4.Dual-channel digital-to-analog converter 5.Bandwidth (5 MHz or 20 MHz) 6.RF module operating between 360 MHz and 960 MHz 7.Ethernet remote access capabilities 8.ARM Processor Design Options 1.Tactical military communications 2.Military communication gateways 3.Handset and man pack systems 4.Vehicular systems

17. Course Objectives  To establish the idea of using computing techniques to alter the properties of a signal for desired effects, via understanding of  Fundamentals of discrete-time, linear, shift- invariant signals and systems in  Representation and Analysis: sampling, quantization, Fourier and z-transform;  Implementation: filtering and transform techniques;  System Design: filter & processing algorithm design.  Efficient computational algorithms and their implementation.

18. Course Outline

20. Prerequisite  A fundamental course in signal and system  Liner System analysis and transform analysis  convolution and filtering  Fourier transforms  Laplace and z transforms

21. Historical Perspective Who is who of DSP

22. Cooley and Tuckey

24. Inventors: Oppenhiam, Schaffer...

25. Inventors: Parks & McCllelan

26. Inventors: Gold and Rader

27. Inventor: J. Kaiser

28. Inventor: Haskell

29. Original Speech Analysis: Voiced/Unvoiced decision Pitch Period (voiced only) Signal power (Gain) G Pulse Train Random Noise Vocal Tract Model V/U Synthesized Speech Decoder Signal Power Pitch Period Encoder Linear Predictive Coding

30. Inventor: James G. Dunn

31. DSP Components

32. Signals Basic Types

33. Basic Types of Digital Signals

34. sindemo Basic Types of Digital Signals

35. Sine and Exp Using Matlab % sine generation: A*sin(omega*n+theta) % exponential generation: A^n n = 0: 1: 50; % amplitude A = 0.87; % phase theta = 0.4; % frequency omega = 2*pi / 20; % sin generation xn1 = A*sin(omega*n+theta); % exp generation xn2 = A.^n;

36. operations Basic Operations

37. Operations in Matlab xn1 = [1 0 3 2 -1 0 0 0 0 0]; xn2 = [1 3 -1 1 0 0 1 2 0 0]; yn = xn1 + xn2;