Signals & Systems B-Tech (Hons)

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

Course Details  Text Book: Discrete Time Signal Processing by Alan V. Oppenheim & Ronald W. Schafer  Course Instructor: Kashif Shahzad Cell:  Course homepage:

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

DSP Introduction Application of mathematical operations to digitally represented signals INOUT A/DD/ADSP x[0] x[1] n

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

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

Example Sampled continuous-time (analog) signals - Speech

Digital Images 2-D arrays (matrices) of numbers

Typical DSP Applications

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

An Embedded System

Example Embedded System

SDR Board Design

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 QAM OFDM

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

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.

Course Outline

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

Historical Perspective Who is who of DSP

Cooley and Tuckey

Inventors: Oppenhiam, Schaffer...

Inventors: Parks & McCllelan

Inventors: Gold and Rader

Inventor: J. Kaiser

Inventor: Haskell

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

Inventor: James G. Dunn

DSP Components

Signals Basic Types

Basic Types of Digital Signals

sindemo Basic Types of Digital Signals

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;

operations Basic Operations

Operations in Matlab xn1 = [ ]; xn2 = [ ]; yn = xn1 + xn2;