Input Function x(t) Output Function y(t) T[ ] System InputSignal O utputSignal -A collection ofitem sthattogetherperform sa function -M odifies/transform san inputto give an output System Represented by
Dec 13, 2015
SystemInput Signal Output Signal
- A collection of items that together performs a function - Modifies / transforms an input to give an output
System
Represented by
Input Function x(t)
Output Function y(t)
T[ ]
Consider The following Input/Output relations
i(t)
RRV ( )t
RV ( ) ( )t Ri t
i(t)
C CV ( )t
C
1V ( ) ( )
t
t i dC
i(t)
L LV ( )t
L( )
V ( )di t
t Ldt
In general we can represent the simple relation between the input and output as:
x( )t
Input
y( )t
Output y(t) = T[ x(t) ]
Were T[ ] is an operator that map the function x(t) to another function y(t) .( Function to Function mapping)
T[ ]
Example
Let the input x(t) = 2sin(4pt) then the output y(t) be
T[ ] = d [ ]dt
Let the operator Differential Operator
T[x(y(t) = t)] = 2sin(4d [ ]dt
)t = 8cos(4 )t
Function 2sin(4pt) mapped Function 8cos(4pt)
( ) ( )x t Ri V tc
C
R
( )x t
( )i t
( )V tC
( )( )
dV tci t Cdt
( )
( ) ( )dV tcx t RC V tcdt
Input Input
Output
The operator or relation T can be defined as
- Linear / Non linear
- Time Invariant / Time Variant
- Continuous-Time / Discrete-Time
- Causal / Non Causal
Representation of a general system
y(t) = T[x(t)]
where the notation T[x(t)] indicates a transformation or mapping
This notation T[.] does not indicate a function
that is, T[x(t)] is not a mathematical function into which we substitutex(t) and directly calculate y(t).
The explicit set of equations relating the input x(t) and the output y(t) is called the mathematical model, or simply, the model, of the system
( )i t[ ]S time shift
( ) [ ( )]C
V t S i t 1 ( )t
i dC
1( ) ( )
o
C
t t
oV t t i dC
time shift
( )i t ( )oi t t[ ]S
1[ ( )] ( )t
o oS i t t i t dC
1The capacitor is time-invariant if [ ( )] ( ) ( )C
t
o o oS i t t V t t i t dC
1 1( ) ( )
ot tt
oi t d i dC C
OR
1Is the capacitor is time-invariant ? ( ) ( )C
t
V t i dC
both output of the block diagram are equal
both output of the block diagram are equal The capacitor is time-invariant
Is ( ) = ( ) time-invariant ?t
z t x d
let = ot [ ( )]= ( )ot t
oS x t t x d
( )oz t t time-invariant
are they equal ?
0
Is ( ) = ( ) time-invariant ?t
z t x d
let = ot [ ( )]= ( )o
o
t t
ot
S x t t x d
time-variant
are they equal ?
0
( ) = ( )t
oz t t x d
0
[ ( )] = ( )t
o oS x t t x t d
( )oz t t 0
( )t
x d
Examples of Nonlinear systems
We can stop here and imply the system is non linear
violates Additivity due to the cross terms
To satisfy homogeneity [ ( )] ( ) ( )S cx t cy t cx t ca
( )cx t ca
We can stop here and imply the system is non linear
1( )x t
[ ]S
To check additivity
1 1[ ( )] = ( )S x t x t a
2( )x t 2 2[ ( )] = ( )S x t x t a
1 2( ) ( )x t x t 1 2 1 2[ ( ) ( )] = ( ) ( )S x t x t x t x t a
1 2[ ( )]+ [ ( )]S x t S x t
( )x t ( )y tx(t)H[ ]
( ) ( )x dt
H
Linear –Time Invariant
( ) ( )y(t) = H x dt
Operator with respect to t Integration with respect to l
( ) ( )H= x t d
constant with respect to t
( ) ( )H= x t d
() )(= h t dx
( )t( )h t(t)H[ ]
The convolution integral
Sep 2 : make the moving function in terms of l
6t 4t
Sep 2 : add t to to form ( t )
t t
( )x t
Moving to the right
0 0
10
1
( ) cos sinnn
n n
x t n ta a b n t
0
0
0
1 ( )T
x t dtT
a The average of x(t)
0
00
cos2 ( ) 0n
T
a n tx t dt nT
00
0sin2 ( )n
T
b nx t dt tT
Chapter 3 The Fourier Series0jn t
n
nX e
0
00
1 ( ) jn t
T
n x t e dtT
X
Let ( ) = ( ) + y t Ax t B
Known
0
kyjk t
k
C e
unknown
what are the coefficients interms of the coefficientsky kxC CQuestion unknown known
Writing y(t) as
0
y
C
ky
C
0 0y xC AC B 0
ky kxC AC k
Let ( ) be as shownx t
Let ( ) = ( ) + y t Ax t B
Let ( ) be as showny t
one to one
one to onewhat are and
oy kyC C
0( ) kyjk t
k
Cy t e
unknown
We wish to find the Fourier series for the sawtooth signal ( ) y t
First, note that the total amplitude variation of ( ) is while the total variation of ( ) is 4. x t X y to4Also note that we invert x(t) to get y(t), yielding =
o
AX
4 ( ) = ( ) + ( ) + 1o
y t Ax t B x tX
one to one
one to onewhat are and
oy kyC C
0( ) kyjk t
k
Cy t e
unknown
4 ( ) = ( ) + ( ) + 1o
y t Ax t B x tX
( ) ( ) j tx t X e d
1( ) ( )2
j tX x t e dt
Fourier Transform Pairs
Sufficient conditions for the existence of the Fourier transform are
On any finite interval, a. ( ) is bounded; b. ( ) has a finite number of maxima
f tf t
( Dirichlet conditions )
1.
and minima; and c. ( ) has a finite number of discontinuities.
f (t) is absolutely integrable; that is, ( )
Note that these are conditions and not condi
f t
f t dt
2.
sufficient necessary tions
you can have a function that is not absolutely integrable however it has Fourier Transform like cos( ) (will be shown later)tNote
0)()( atuetx at
( )
0( ) ( )at j t a j tX j e u t e dt e dt
Finding the Fourier Transform
1a
( )
0
1
( )a j te
a j
1
( )a j
0)()( atuetx at 1( )
( )X j
a j
Example Find the Fourier Transform for the following function
aa( ) ( ) j tX x t e dt
1
1
j te dt
1
1
j tej
2sinc( )
j je ej
22
j je ej
2 sin( )
sin( )2
(1) ( 1)j je ej
Example
0
b( )x t
t1 1
1
1bb( ) ( ) j tX x t e dt
0 1
1 0
(1) ( 1) j t te dt e dt
2sinc
2j
bb
( )| ( )|( ) jXX e
b2sin| |
2) c(X
0
b( )x t
t1 1
1
1
2b ( ) sinc
2X f j
2
f0
( )f
2
2
2b ( ) sinc
2X j
bb
( )| ( )|( ) jXX e
oAlways 0 it add no angle (0 )
1 21 1 1 1 1 2[ ( ) ( ) ] ( ) + ( )F a x t a x t a X a X 1-Linearity
Properties of the Fourier Transform
( )X 1( )X 2( )X
(1)(4)sinc(4 ) (2)(2)sinc(2 ) +
( )sinc( )A T T
4sinc(4 ) 4sinc(2 )+
Using Fourier Transform Properties
) 2sinc( )(aX
2(2sinc(2 ))
what is the fourier transform of
Let
11
21 2 ( ) aX X
since ( )1 2
a
tx t x
2 2 )(aX
4sinc(2 )
Example Find the Fourier Transform of the pulse function
0
( )x t
t2
1
Solution
From previous Example
a ( ) 2sin (2 )X c
Since ( ) ( )1ax t x t 1( )
2sinc(2 ) = e j
2sinc(2 ) = e j
0 ( ) ( )e a
tjX X
If ( ) ( ) ( ) 2 ) (Xx t tX x then
2W
2W
2W
t
2 sinc(2 ) W Wt
Find the of 2 sinc(2 ) W WtF.T
5-Duality ازدواجية
2W
2W
2W
t
12 sinc(2 ) ( ) ( 4 )2
W Wt X t W
2
sinc2
( ) = X
2
Step 1 from Known transform from the F.T Table
Step 2
t
2
0
1
t
( ) = rectt
x t
2
2W0
1
rect4W
2W
rect4W
Even Function
( ) 2 ( )tX x
1 ( ) ( )2
2 x x
2 21 1( ) ( ) ( ( ) )x t x t X X
6- The convolution Theorem
2 21 11( ) ( ) ) ( )
2( Xx t x t X
The multiplication Theorem
rect rectt t
Find the Fourier Transform of following
Solution
Since rect
t
t
2
2 0
rect
t
t
2
2 0
trit
t 0
convolution
Time
sinc( )f sinc( )f 2 2sinc ( )f Frequencymultiplication
System Analysis with Fourier Transform
= ( ) ( ) x h t d
( )x t
( )h ty(t) = ( ( ) )x t h t
( )X ( )H ( )Y ( ) ( )X H
( ) ) ) ( (Y X H y(t) = ( ( ) )x t h t
convolution in time
multiplication in Frequency
impulse response
convolution in timemultiplication in Frequency
Find the Transfer Function for the following RC circuit
C
R
( )x t
( )y t
( ) ( ) ( ) dy tRC y t x t t
dt
C
R
( )t
( )h t
( ) ( ) ( )dh tRC h t t
dt
1( ) ( )t
R Ch t e u tR C
we can find h(t) by solving differential equation as follows
Method 1
C
R
( )x t
( )y t
( ) ( ) ( )dy tRC y t x t
dt
( )FT ( ) FT ( ) dy tRC y t x t
dt
( ) ( ) ( ) ( ) RC j Y Y X
( ) 1 ( ) ( ) j RC Y X
( )( )
( ) Y
HX
1( ) 1j RC
We will find h(t) using Fourier Transform Method rather than solving differential equation as follows
Method 2
C
R
( )x t
( )y t
( ) ( ) ( )dy tRC y t x t
dt
( )( )
( ) Y
HX
1( ) 1j RC
(1/ )( ) (1/ )
RCj RC
1( ) ( ) > 0 tx t e u tj
1( ) ( )t
R Ch t e u tR C
From Table 4-2
C
R
( )x t
( )y t
Method 3
R
( )X
( )Y
1j C
Fourier Transform
1
( ) ( )1
j CY f X
Rj C
1( )
1X
j RC
( ) 1( )
( ) 1
YH
X j RC
1( ) ( )t
R Ch t e u tR C
C
R
( )x t
( )y t
R
( )X
( )Y
1j C
Fourier Transform
( ) 1( )
( ) 1
YH
X j RC
2
1| ( ) |
1 ( )H
RC
( )H | ( ) |H
( )H 1tan ( )RC
C
R
( )x t
( )y t
Find y(t) if the input x(t) is
( ) ( )tx t A e u t
Method 1 ( convolution method)
Using the time domain ( convolution method , Chapter 3)
y( ) = ( ) ) (t x t h t
1( ) ( )t
R Ch t e u tR C
Example
C
R
( )x t
( )y t
( ) ( )tx t A e u t
/ ( )(1/ )
A RCj RC j
1 1( ) 1/1AY jRC jRC
Using partial fraction expansion (will be shown later)
From Table 5-2 /( ) ( )1
t RC tAy t e e u tRC
( ) AXj
1( ) ( )t
R Ch t e u tR C
(1/ )( )
(1/ ) ( )RCH
RC j
( ) ) ( ( )Y X H
Method 2 Fourier Transform
Sine Y(w) is not on the Fourier Transform Table 5-2