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  • 1

    EE3054

    Signals and Systems

    Continuous Time Signals & Systems: Part I

    Yao Wang

    Polytechnic University

    Some slides included are extracted from lecture presentations prepared by McClellan and Schafer

    3/12/2008 © 2003, JH McClellan & RW Schafer 2

    License Info for SPFirst Slides

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  • 2

    LECTURE OBJECTIVES

    � Bye bye to D-T Systems for a while

    � The UNIT IMPULSE signal

    � Definition

    � Properties

    � Continuous-time systems

    � Example systems and their impulse response

    �� LLinearity and TTime-IInvariant (LTI) systems

    � Convolution integral

    3/12/2008 © 2003, JH McClellan & RW Schafer 4

    ANALOG SIGNALS x(t)

    � INFINITE LENGTH� SINUSOIDS: (t = time in secs)

    � PERIODIC SIGNALS

    � ONE-SIDED, e.g., for t>0� UNIT STEP: u(t)

    � FINITE LENGTH� SQUARE PULSE

    � IMPULSE SIGNAL: δδδδ(t)

    � DISCRETE-TIME: x[n] is list of numbers

  • 3

    3/12/2008 © 2003, JH McClellan & RW Schafer 5

    CT Signals: PERIODIC

    x(t) = 10cos(200πt)Sinusoidal signal

    Square Wave INFINITE DURATION

    3/12/2008 © 2003, JH McClellan & RW Schafer 6

    CT Signals: ONE-SIDED

    v(t) = e−tu(t)

    Unit step signalu(t) =1 t > 0

    0 t < 0

    One-Sided

    Sinusoid

    “Suddenly applied”

    Exponential

  • 4

    3/12/2008 © 2003, JH McClellan & RW Schafer 7

    CT Signals: FINITE LENGTH

    Square Pulse signal

    p(t) = u(t − 2) −u(t − 4)

    Sinusoid multiplied

    by a square pulse

    3/12/2008 © 2003, JH McClellan & RW Schafer 8

    What is an Impulse?

    � A signal that is “concentrated” at one point.

    lim∆→0

    δ∆ (t) = δ (t)δ∆ (t)dt = 1

    −∞

  • 5

    3/12/2008 © 2003, JH McClellan & RW Schafer 9

    � Assume the properties apply to the limit:

    � One “INTUITIVE” definition is:

    Defining the Impulse

    Unit areaδ(τ )dτ−∞

    ∫ =1

    Concentrated at t=0δ(t) = 0, t ≠ 0

    lim∆→0

    δ∆ (t) = δ (t)

    3/12/2008 © 2003, JH McClellan & RW Schafer 10

    Sampling Property

    f (t)δ (t) = f (0)δ (t)

    f (t)δ∆ (t) ≈ f (0)δ∆ (t)

  • 6

    3/12/2008 © 2003, JH McClellan & RW Schafer 11

    General Sampling Property

    f (t)δ (t − t0 ) = f (t0 )δ (t − t0 )

    3/12/2008 © 2003, JH McClellan & RW Schafer 12

    Properties of the Impulse

    Concentrated at one time

    Sampling Property

    Unit area

    Extract one value of f(t)

    Derivative of unit step

    f (t)δ(t − t0 ) = f (t0 )δ(t − t0)

    δ( t − t0 )dt−∞

    ∫ = 1

    δ(t − t0 ) = 0, t ≠ t0

    f (t)δ(t − t0 )dt−∞

    ∫ = f (t0 )

    du( t)

    dt= δ(t)

  • 7

    Representing any signal using

    impulse

    ∆−≈−= ∑∫ ∆∞

    ∞−

    )()()()()( kk txdtxtx τδτττδτ

    3/12/2008 © 2003, JH McClellan & RW Schafer 14

    Continuous-Time Systems

    � Examples:

    � Delay

    � Modulator

    � Integrator

    x(t) ֏ y(t)

    y(t) = x(t − td )

    y(t) = [A + x(t)]cosωct

    y(t) = x(τ−∞

    t

    ∫ )dτ

    Input

    Output

  • 8

    3/12/2008 © 2003, JH McClellan & RW Schafer 15

    Impulse Response

    � Output when the input is δ(t)

    � Denoted by h(t)

    3/12/2008 © 2003, JH McClellan & RW Schafer 16

    Ideal Delay:

    � Mathematical Definition:

    � To find the IMPULSE RESPONSE, h(t),let x(t) be an impulse, so

    h(t) = δ (t − td )

    y(t) = x(t − td )

  • 9

    3/12/2008 © 2003, JH McClellan & RW Schafer 17

    Output of Ideal Delay of 1 sec

    x(t) = e−tu(t)

    y(t) = x(t −1) = e−(t−1)u(t −1)

    3/12/2008 © 2003, JH McClellan & RW Schafer 18

    Integrator:

    � Mathematical Definition:

    � To find the IMPULSE RESPONSE, h(t),let x(t) be an impulse, so

    y(t) = x(τ−∞

    t

    ∫ )dτ

    h(t) = δ(τ−∞

    t

    ∫ )dτ = u(t)

    Running Integral

  • 10

    3/12/2008 © 2003, JH McClellan & RW Schafer 19

    Integrator:

    � Integrate the impulse

    � IF t0, we get one

    � Thus we have h(t) = u(t) for the integrator

    y(t) = x(τ−∞

    t

    ∫ )dτ

    δ(τ−∞

    t

    ∫ )dτ = u(t)

    3/12/2008 © 2003, JH McClellan & RW Schafer 20

    Graphical Representation

    δ(t) =du(t)

    dt

    u(t) = δ (τ )dτ =1 t > 0

    0 t < 0

    −∞

    t

  • 11

    3/12/2008 © 2003, JH McClellan & RW Schafer 21

    Output of Integrator

    )()(

    )()(

    tutx

    dxty

    t

    ∗=

    = ∫∞−

    ττ

    )()1(25.1

    0)(

    00

    )()(

    8.0

    0

    8.0

    8.0

    tue

    tdue

    t

    duety

    t

    t

    t

    ∞−

    −=

    <=

    =

    ττ

    ττ

    τ

    τ

    )()( 8.0 tuetx t−=

    3/12/2008 © 2003, JH McClellan & RW Schafer 22

    Differentiator:

    � Mathematical Definition:

    � To find h(t), let x(t) be an impulse, so

    y(t) =dx(t)

    dt

    h(t) =dδ (t)dt

    = δ (1)(t) Doublet

  • 12

    3/12/2008 © 2003, JH McClellan & RW Schafer 23

    Differentiator Output: y(t) =dx(t)

    dt

    )1()( )1(2 −= −− tuetx t

    ( )

    )1(1)1(2

    )1()1(2

    )1()(

    )1(2

    )1(2)1(2

    )1(2

    −+−−=

    −+−−=

    −=

    −−

    −−−−

    −−

    ttue

    tetue

    tuedt

    dty

    t

    tt

    t

    δ

    δ

    Linear and Time-Invariant

    (LTI) Systems

    � Recall LTI property of discrete time

    system

    � Can be similarly defined for continuous

    time systems

  • 13

    3/12/2008 © 2003, JH McClellan & RW Schafer 25

    Testing for Linearity

    x1(t)

    x2 (t)

    y1(t)

    y2 (t)

    w(t)

    y(t)x(t)

    x2 (t)

    x1(t)w(t)

    y(t)

    3/12/2008 © 2003, JH McClellan & RW Schafer 26

    Testing Time-Invariance

    x(t) x(t − t0 )

    y(t)

    w(t)

    y(t − t0 )

    t0

    w(t) y(t − t0 )

    t0

  • 14

    3/12/2008 © 2003, JH McClellan & RW Schafer 27

    Ideal Delay:

    � Linear

    � and Time-Invariant

    y(t) = x(t − td )

    ax1( t − td ) + bx2(t − td ) = ay1 (t) + by2 (t)

    ))(())(()(

    ))(()(

    000

    0

    dd

    d

    tttxtttxtty

    tttxtw

    −−=−−=−

    −−=

    3/12/2008 © 2003, JH McClellan & RW Schafer 28

    Integrator:

    � Linear

    � And Time-Invariant

    y(t) = x(τ−∞

    t

    ∫ )dτ

    [ax1(τ−∞

    t

    ∫ ) + bx2 (τ )]dτ = ay1(t) + by2 (t)

    w(t) = x(τ − t0−∞

    t

    ∫ )dτ let σ = τ − t0

    ⇒ w( t) = x(σ )dσ−∞

    t−t 0

    ∫ = y(t - t0 )

  • 15

    3/12/2008 © 2003, JH McClellan & RW Schafer 29

    Modulator:

    �� NotNot linear--obvious because

    �� NotNot time-invariant

    y(t) = [A + x(t)]cosωct

    w(t) = [A + x(t − t0 )]cosωct ≠ y(t − t0 )

    [A + ax1(t) + bx2 (t)]≠

    [A + ax1(t)]+ [A + bx2 (t)]

    3/12/2008 © 2003, JH McClellan & RW Schafer 30

    Continuous Time Convolution

    � If a continuous-time system is both linear and

    time-invariant, then the output y(t) is related to

    the input x(t) by a convolution integralconvolution integral

    where h(t) is the impulse responseimpulse response of the system.

    y(t) = x(τ )h(t − τ )dτ = x(t)∗h(t)−∞

  • 16

    Proof

    � Representing x(t) using δ(t), using LTI property!

    ∆−≈−= ∑∫ ∆∞

    ∞−

    )()()()()( kk txdtxtx τδτττδτ

    Ideal Delay:

    � Recall

    � Show y(t)=x(t)*h(t)

    � Another important property of δ(t):� x(t)*δ(t-t0)=x(t-t0)

    h(t) = δ (t − td )

    y(t) = x(t − td )

  • 17

    Integrator:

    � Recall

    � Show: y(t)=x(t)*h(t)

    y(t) = x(τ−∞

    t

    ∫ )dτ

    h(t) = δ(τ−∞

    t

    ∫ )dτ = u(t)

    READING ASSIGNMENTS

    � This Lecture:

    � Chapter 9, Sects 9-1 to 9-5

    � Next Lecture:

    � Chapter 9, Sects 9-6 to 9-8

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