Transcript Slide 1

C H A P T E R
2
SIGNALS AND SIGNAL SPACE
Description of a Signal
Amplitude
Radian Frequency
Phase Angle
Period
Size of a Signal
Signal Energy
Signal Power:
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Examples of signals: (a) signal with finite energy;
(b) signal with finite power.
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Example
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Classification of Signals
•Continuous time and
discrete time signals
•Analog and digital signals
•Periodic and aperiodic
signals
•Energy and power signals
•Deterministic and radaom
signals
•Physical description is known
completely in either
mathematical or graphical form
•Probabilistic description such
as mean value, mean squared
value and distributions
a) Continuous time and (b) discrete time signals.
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Analog and continuous time
Digital and continuous time
Analog and discrete time
Digital and discrete time
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g(t)=g(t+T0) for all t
Periodic signal of period T0.
Energy signal: a signal with finite energy
Power signal: a signal with finite power
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Signal Operations
Time shifting a signal.
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Time scaling a signal.
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Examples of time compression and time expansion of signals.
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g(-t)?
Time inversion (reflection) of a signal.
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Example of time inversion.
g(-t)?
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(
a) Unit impulse and (b) its approximation.
Multiplication of a Function
by an Impulse
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a) Unit step function u(t). (b) Causal exponential function e−atu(t).
Causal signal: a signal starts after t=0
Question: how to convert any signal to a causal signal?
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Signals Versus Vectors
Vector:
Magnitude and Direction
<x,x>=?
Component (projection) of a vector along another vector.
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Component of a Vector along Another Vector
Approximations of a vector in terms of another vector.
g=cx+e=c1x+e1=c2x+e2
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Decomposition of a Signal and Signal Components
Approximation of square signal in terms of a single sinusoid.
Find the component in
g(t) of the form sin(t) to
make the energy of the
error signal is minimum
Hint:
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Correlation of Signals
Correlation coefficient
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Signals for Example 2.6.
b:1, c:1, d:-1,e:
0.961,f:0.628, f:0
Application to Signal Detection
Physical explanation of the auto-correlation function.
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Representation of a vector in
three-dimensional space.
Parseval’s Theorem
Orthogonal Signal Space
Generalized Fourier Series
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The energy of the sum of
orthogonal signal is equal to
the sum of their energies.
Trigonometric Fourier Series
Compact Trigonometric Fourier
Series
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Amplitude spectrum
Phase spectrum
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(a, b) Periodic signal and (c, d) its Fourier spectra.
Figure 2.20 (a) Square pulse periodic signal and (b) its Fourier spectrum.
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Bipolar square pulse periodic signal.
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(a) Impulse train and (b) its Fourier spectrum.
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Exponential Fourier Series
Exponential Fourier spectra for the signal
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