Lecture 1 Signals. notation and meaning. common signals. size of a signal. qualitative properties of signals. impulsive signals

Similar documents
Lecture 2 ELE 301: Signals and Systems

April 24, 2012 (Tue) Lecture 19: Impulse Function and its Laplace Transform ( 6.5)

Section 6.5 Impulse Functions

1. SINGULARITY FUNCTIONS

2.161 Signal Processing: Continuous and Discrete Fall 2008

Chapter 1 Fundamental Concepts

Lecture 9 Time-domain properties of convolution systems

Chapter 1 Fundamental Concepts

Figure 1.1 (a) Model of a communication system, and (b) signal processing functions.

06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 1

Analysis III for D-BAUG, Fall 2017 Lecture 10

ECEN 420 LINEAR CONTROL SYSTEMS. Lecture 2 Laplace Transform I 1/52

1.4 Unit Step & Unit Impulse Functions

Linear dynamical systems with inputs & outputs

Lecture Notes for Math 251: ODE and PDE. Lecture 22: 6.5 Dirac Delta and Laplace Transforms

Lecture 1 From Continuous-Time to Discrete-Time

Lecture 7: Laplace Transform and Its Applications Dr.-Ing. Sudchai Boonto

Fourier Transform for Continuous Functions

2.161 Signal Processing: Continuous and Discrete Fall 2008

The (Fast) Fourier Transform

Generalized sources (Sect. 6.5). The Dirac delta generalized function. Definition Consider the sequence of functions for n 1, Remarks:

e st f (t) dt = e st tf(t) dt = L {t f(t)} s

Ordinary differential equations

GATE EE Topic wise Questions SIGNALS & SYSTEMS

Electric Circuits. Overview. Hani Mehrpouyan,

Time Response of Systems

Chapter 33. Alternating Current Circuits

Physics 208: Electricity and Magnetism Final Exam, Secs May 2003 IMPORTANT. Read these directions carefully:

EEE105 Teori Litar I Chapter 7 Lecture #3. Dr. Shahrel Azmin Suandi Emel:

Series FOURIER SERIES. Graham S McDonald. A self-contained Tutorial Module for learning the technique of Fourier series analysis

(an improper integral)

Math 221 Topics since the second exam

20.3. Further Laplace Transforms. Introduction. Prerequisites. Learning Outcomes

ENGIN 211, Engineering Math. Laplace Transforms

EE102 Homework 2, 3, and 4 Solutions

12. Introduction and Chapter Objectives

Continuous-time Signals. (AKA analog signals)

First and Second Order Circuits. Claudio Talarico, Gonzaga University Spring 2015

Driven RLC Circuits Challenge Problem Solutions

Energy Storage Elements: Capacitors and Inductors

Laplace Transform Part 1: Introduction (I&N Chap 13)

Physics 116A Notes Fall 2004

LOPE3202: Communication Systems 10/18/2017 2

6: Fourier Transform

EA2.3 - Electronics 2 1

Basics of Network Theory (Part-I)

0 t < 0 1 t 1. u(t) =

Signals and Systems Lecture Notes

ENSC327 Communications Systems 2: Fourier Representations. Jie Liang School of Engineering Science Simon Fraser University

Sinusoidal Steady State Analysis (AC Analysis) Part II

The Laplace Transform

Basic Electronics. Introductory Lecture Course for. Technology and Instrumentation in Particle Physics Chicago, Illinois June 9-14, 2011

17. Impulses and generalized functions

ECE2262 Electric Circuits. Chapter 6: Capacitance and Inductance

Problem Set 5 Solutions

E40M Capacitors. M. Horowitz, J. Plummer, R. Howe

2.004 Dynamics and Control II Spring 2008

Communication Theory II

ORDINARY DIFFERENTIAL EQUATIONS

Introduction to AC Circuits (Capacitors and Inductors)

Problem Set 4 Solutions

ECE2262 Electric Circuits. Chapter 6: Capacitance and Inductance

Signal Processing and Linear Systems1 Lecture 4: Characterizing Systems

16.362: Signals and Systems: 1.0

EE292: Fundamentals of ECE

Control Systems I. Lecture 6: Poles and Zeros. Readings: Emilio Frazzoli. Institute for Dynamic Systems and Control D-MAVT ETH Zürich

Chapter 7. Digital Control Systems

A system that is both linear and time-invariant is called linear time-invariant (LTI).

Circuit Analysis-III. Circuit Analysis-II Lecture # 3 Friday 06 th April, 18

EE 261 The Fourier Transform and its Applications Fall 2007 Problem Set Eight Solutions

Besides resistors, capacitors are one of the most common electronic components that you will encounter. Sometimes capacitors are components that one

Fourier Analysis Fourier Series C H A P T E R 1 1

Convolution. Define a mathematical operation on discrete-time signals called convolution, represented by *. Given two discrete-time signals x 1, x 2,

Transient response of RC and RL circuits ENGR 40M lecture notes July 26, 2017 Chuan-Zheng Lee, Stanford University

EE -213 BASIC CIRCUIT ANALYSIS LAB MANUAL

Mid-Chapter Quiz: Lessons 1-1 through 1-4

Introduction to Controls

3.2 Complex Sinusoids and Frequency Response of LTI Systems

Aspects of Continuous- and Discrete-Time Signals and Systems

Wave Phenomena Physics 15c. Lecture 10 Fourier Transform

Capacitors. Chapter How capacitors work Inside a capacitor

Second order Unit Impulse Response. 1. Effect of a Unit Impulse on a Second order System

= lim. (1 + h) 1 = lim. = lim. = lim = 1 2. lim

x(t) = t[u(t 1) u(t 2)] + 1[u(t 2) u(t 3)]

Solved Problems. Electric Circuits & Components. 1-1 Write the KVL equation for the circuit shown.

Review of Fourier Transform

Control System Design

Lecture 28 Continuous-Time Fourier Transform 2

A3. Frequency Representation of Continuous Time and Discrete Time Signals

Kirchhoff's Laws I 2 I 3. junc. loop. loop -IR +IR 2 2 V P I V I R R R R R C C C. eff R R R C C C. eff 3.0

Lecture 6: Time-Domain Analysis of Continuous-Time Systems Dr.-Ing. Sudchai Boonto

AC analysis. EE 201 AC analysis 1

Laboratory I: Impedance

Today s goals So far Today 2.004

Lecture Notes of EE 714

9.2 The Input-Output Description of a System

15-884/484 Electric Power Systems 1: DC and AC Circuits

Tutorial Sheet #2 discrete vs. continuous functions, periodicity, sampling

Source-Free RC Circuit

EE (082) Ch. II: Intro. to Signals Lecture 2 Dr. Wajih Abu-Al-Saud

Transcription:

EE102 spring 2002 Handout #2 Lecture 1 Signals notation and meaning common signals size of a signal qualitative properties of signals impulsive signals 1 1

Signals a signal is a function of time, e.g., f is the force on some mass v out is the output voltage of some circuit p is the acoustic pressure at some point notation: f, v out, p or f( ), v out ( ), p( ) refer to the whole signal or function f(t), v out (1.2), p(t +2)refer to the value of the signals at times t, 1.2, and t +2,respectively for times we usually use symbols like t, τ, t 1,... Signals 1 2

Example 1 p(t) (Pa) 0 1 1 0 1 2 3 t (msec) Signals 1 3

Domain of a signal domain of a signal: t s for which it is defined some common domains: all t, i.e., R nonnegative t: t 0 (here t =0just means some starting time of interest) t in some interval: a t b t at uniformly sampled points: t = kh + t 0, k =0, ±1, ±2,... discrete-time signals are defined for integer t, i.e., t =0, ±1, ±2,... (here t means sample time or epoch, not real time in seconds) we ll usually study signals defined on all reals, or for nonnegative reals Signals 1 4

Dimension & units of a signal dimension or type of a signal u, e.g., real-valued or scalar signal: u(t) is a real number (scalar) vector signal: u(t) is a vector of some dimension binary signal: u(t) is either 0 or 1 we ll usually encounter scalar signals example: avector-valued signal v = v 1 v 2 v 3 might give the voltage at three places on an antenna physical units of a signal, e.g., V, ma, m/sec sometimes the physical units are 1 (i.e., unitless) or unspecified Signals 1 5

Common signals with names aconstant(or static or DC) signal: u(t) =a, wherea is some constant the unit step signal (sometimes denoted 1(t) or U(t)), u(t) =0for t<0, u(t) =1for t 0 the unit ramp signal, u(t) =0for t<0, u(t) =t for t 0 a rectangular pulse signal, u(t) =1for a t b, u(t) =0otherwise a sinusoidal signal: u(t) =a cos(ωt + φ) a, b, ω, φ are called signal parameters Signals 1 6

Real signals most real signals, e.g., AM radio signal FM radio signal cable TV signal audio signal NTSC video signal 10BT ethernet signal telephone signal aren t given by mathematical formulas, but they do have defining characteristics Signals 1 7

Measuring the size of a signal size of a signal u is measured in many ways for example, if u(t) is defined for t 0: integral square (or total energy): squareroot of total energy integral-absolute value: 0 0 u(t) dt u(t) 2 dt peak or maximum absolute value of a signal: max t 0 u(t) ( ) 1/2 1 T root-mean-square (RMS) value: lim u(t) 2 dt T T 0 average-absolute (AA) value: lim T 1 T T 0 u(t) dt for some signals these measures can be infinite, or undefined Signals 1 8

example: for a sinusoid u(t) =a cos(ωt + φ) for t 0 the peak is a the RMS value is a / 2 0.707 a the AA value is a 2/π 0.636 a the integral square and integral absolute values are the deviation between two signals u and v can be found as the size of the difference, e.g., RMS(u v) Signals 1 9

Qualitative properties of signals u decays if u(t) 0 as t u converges if u(t) a as t (a is some constant) u is bounded if its peak is finite u is unbounded or blows up if its peak is infinite u is periodic if for some T>0, u(t + T )=u(t) holds for all t in practice we are interested in more specific quantitative questions, e.g., how fast does u decay or converge? how large is the peak of u? Signals 1 10

Impulsive signals (Dirac s) delta function or impulse δ is an idealization of a signal that is very large near t =0 is very small away from t =0 has integral 1 for example: ɛ 2ɛ 1/ɛ 1/ɛ t =0 t t =0 t the exact shape of the function doesn t matter ɛ is small (which depends on context) Signals 1 11

on plots δ is shown as a solid arrow: f(t) =δ(t) t =0 t f(t) =t +1+δ(t) t = 1 t =0 t Signals 1 12

Formal properties formally we define δ by the property that b a f(t)δ(t) dt = f(0) provided a<0, b>0, andf is continuous at t =0 idea: δ acts over a time interval very small, over which f(t) f(0) δ(t) =0for t 0 δ(0) isn t really defined b δ(t) dt =1if a<0 and b>0 a b δ(t) dt =0if a>0 or b<0 a Signals 1 13

b a δ(t) dt =0is ambiguous if a =0or b =0 our convention: to avoid confusion we use limits such as a or b+ to denote whether we include the impulse or not for example, 1 0+ δ(t) dt =0, 1 0 δ(t) dt =1, 0 1 δ(t) dt =0, 0+ 1 δ(t) dt =1 Signals 1 14

Scaled impulses αδ(t T ) is sometimes called an impulse at time T,withmagnitude α we have b a αδ(t T )f(t) dt = αf(t ) provided a<t <band f is continuous at T on plots: write magnitude next to the arrow, e.g., for 2δ, 2 0 t Signals 1 15

Sifting property the signal u(t) =δ(t T ) is an impulse function with impulse at t = T for a<t <b,andf continuous at t = T,wehave example: b a f(t)δ(t T ) dt = f(t ) 3 2 f(t)(2 + δ(t +1) 3δ(t 1) + 2δ(t +3))dt = 2 = 2 3 +2 2 3 3 2 f(t) dt + 2 3 2 f(t)δ(t +3))dt f(t)δ(t +1)dt 3 f(t) dt + f( 1) 3f(1) 3 2 f(t)δ(t 1) dt Signals 1 16

Physical interpretation impulse functions are used to model physical signals that act over short time intervals whose effect depends on integral of signal example: hammer blow, or bat hitting ball, at t =2 force f acts on mass m between t =1.999 sec and t =2.001 sec 2.001 f(t) dt = I (mechanical impulse, N sec) 1.999 blow induces change in velocity of v(2.001) v(1.999) = 1 m 2.001 1.999 f(τ) dτ = I/m for (most) applications we can model force as an impulse, at t =2,with magnitude I Signals 1 17

example: rapid charging of capacitor t =0 1V v(t) i(t) 1F assuming v(0) = 0, whatisv(t), i(t) for t>0? i(t) is very large, for a very short time a unit charge is transferred to the capacitor almost instantaneously v(t) increases to v(t) =1 almost instantaneously to calculate i, v, weneedamoredetailed model Signals 1 18

for example, include small resistance R i(t) 1V v(t) i(t) = dv(t) dt = 1 v(t) R, v(0) = 0 1 1/R v(t) =1 e t/r i(t) =e t/r /R R as R 0, i approaches an impulse, v approaches a unit step R Signals 1 19

as another example, assume the current delivered by the source is limited: if v(t) < 1, thesource acts as a current source i(t) =I max I max v(t) i(t) i(t) = dv(t) dt = I max, v(0) = 0 1 v(t) I max i(t) 1/I max 1/I max as I max, i approaches an impulse, v approaches a unit step Signals 1 20

in conclusion, large current i acts over very short time between t =0and ɛ total charge transfer is ɛ 0 i(t) dt =1 resulting change in v(t) is v(ɛ) v(0) = 1 can approximate i as impulse at t =0with magnitude 1 modeling current as impulse obscures details of current signal obscures details of voltage change during the rapid charging preserves total change in charge, voltage is reasonable model for time scales ɛ Signals 1 21

Integrals of impulsive functions integral of a function with impulses has jump at each impulse, equal to the magnitude of impulse example: u(t) =1+δ(t 1) 2δ(t 2); definef(t) = t 0 u(τ) dτ 1 u(t) t =1 t =2 t 2 f(t) =t for 0 t<1, f(t) =t+1 for 1 <t<2, f(t) =t 1 for t>2 (f(1) and f(2) are undefined) Signals 1 22

Derivatives of discontinuous functions conversely, derivative of function with discontinuities has impulse at each jump in function derivative of unit step function (see page 1 6) is δ(t) signal f of previous page f(t) 3 2 1 1 2 t f (t) =1+δ(t 1) 2δ(t 2) Signals 1 23

Derivatives of impulse functions integration by parts suggests we define b a δ (t)f(t) dt = δ(t)f(t) b a b a δ(t)f (t) dt = f (0) provided a<0, b>0, andf continuous at t =0 δ is called doublet δ, δ,etc.arecalledhigher-order impulses similar rules for higher-order impulses: b a δ (k) (t)f(t) dt =( 1) k f (k) (0) if f (k) continuous at t =0 Signals 1 24

interpretation of doublet δ :taketwoimpulses with magnitude ±1/ɛ, a distance ɛ apart, and let ɛ 0 1/ɛ t = ɛ t =0 1/ɛ for a<0, b>0, b a ( δ(t) f(t) ɛ ) δ(t ɛ) ɛ dt = f(0) f(ɛ) ɛ converges to f (0) if ɛ 0 Signals 1 25

Caveat there is in fact no such function (Dirac s δ is what is called a distribution) we manipulate impulsive functions as if they were real functions, which they aren t it is safe to use impulsive functions in expressions like b a f(t)δ(t T ) dt, b a f(t)δ (t T ) dt provided f (resp, f )iscontinuous at t = T,anda T, b T some innocent looking expressions don t make any sense at all (e.g., δ(t) 2 or δ(t 2 )) Signals 1 26