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Just because some of us can read and write and do a little math, that doesn't mean we deserve to conquer the Universe.

—Kurt Vonnegut, Hocus Pocus , 1990

This appendix gathers together all of the math facts used in the text. They are divided into six categories:

  • Trigonometric identities
  • Fourier transforms and properties
  • Energy and power
  • Z-transforms and properties
  • Integral and derivative formulas
  • Matrix algebra

So, with no motivation or interpretation, just labels, here they are:

Trigonometric identities

  • Euler's relation
    e ± j x = cos ( x ) ± j sin ( x )
  • Exponential definition of a cosine
    cos ( x ) = 1 2 e j x + e - j x
  • Exponential definition of a sine
    sin ( x ) = 1 2 j e j x - e - j x
  • Cosine squared
    cos 2 ( x ) = 1 2 1 + cos ( 2 x )
  • Sine squared
    sin 2 ( x ) = 1 2 1 - cos ( 2 x )
  • Sine and Cosine as phase shifts of each other
    sin ( x ) = cos π 2 - x = cos x - π 2 cos ( x ) = sin π 2 - x = - sin x - π 2
  • Sine–cosine product
    sin ( x ) cos ( y ) = 1 2 sin ( x - y ) + sin ( x + y )
  • Cosine–cosine product
    cos ( x ) cos ( y ) = 1 2 cos ( x - y ) + cos ( x + y )
  • Sine–sine product
    sin ( x ) sin ( y ) = 1 2 cos ( x - y ) - cos ( x + y )
  • Odd symmetry of the sine
    sin ( - x ) = - sin ( x )
  • Even symmetry of the cosine
    cos ( - x ) = cos ( x )
  • Cosine angle sum
    cos ( x ± y ) = cos ( x ) cos ( y ) sin ( x ) sin ( y )
  • Sine angle sum
    sin ( x ± y ) = sin ( x ) cos ( y ) ± cos ( x ) sin ( y )

Fourier transforms and properties

  • Definition of Fourier transform
    W ( f ) = - w ( t ) e - j 2 π f t d t
  • Definition of Inverse Fourier transform
    w ( t ) = - W ( f ) e j 2 π f t d f
  • Fourier transform of a sine
    F { A sin ( 2 π f 0 t + Φ ) } = j A 2 - e j Φ δ ( f - f 0 ) + e - j Φ δ ( f + f 0 )
  • Fourier transform of a cosine
    F { A cos ( 2 π f 0 t + Φ ) } = A 2 e j Φ δ ( f - f 0 ) + e - j Φ δ ( f + f 0 )
  • Fourier transform of impulse
    F { δ ( t ) } = 1
  • Fourier transform of rectangular pulse
  • With
    Π ( t ) = 1 - T / 2 t T / 2 0 otherwise ,
    F { Π ( t ) } = T sin ( π f T ) π f T T sinc ( f T ) .
  • Fourier transform of sinc function
    F { sinc ( 2 W t ) } = 1 2 W Π f 2 W
  • Fourier transform of raised cosine
  • With
    w ( t ) = 2 f 0 sin ( 2 π f 0 t ) 2 π f 0 t cos ( 2 π f Δ t ) 1 - ( 4 f Δ t ) 2 ,
    F { w ( t ) } = 1 | f | < f 1 1 2 1 + cos π ( | f | - f 1 ) 2 f Δ f 1 < | f | < B 0 | f | > B ,
    with the rolloff factor defined as β = f Δ / f 0 .
  • Fourier transform of square-root raised cosine (SRRC)
  • With w ( t ) given by
    1 T sin ( π ( 1 - β ) t / T ) + ( 4 β t / T ) cos ( π ( 1 + β ) t / T ) ( π t / T ) ( 1 - ( 4 β t / T ) 2 ) t 0 , ± T 4 β 1 T ( 1 - β + ( 4 β / π ) ) t = 0 β 2 T 1 + 2 π sin π 4 β + 1 - 2 π cos π 4 β t = ± T 4 β ,
    F { w ( t ) } = 1 | f | < f 1 1 2 1 + cos π ( | f | - f 1 ) 2 f Δ 1 / 2 f 1 < | f | < B 0 | f | > B .
  • Fourier transform of periodic impulse sampled signal
  • With
    F { w ( t ) } = W ( f ) ,
    and
    w s ( t ) = w ( t ) k = - δ ( t - k T s ) , F { w s ( t ) } = 1 T s n = - W ( f - ( n / T s ) ) .
  • Fourier transform of a step
  • With
    w ( t ) = A t > 0 0 t < 0 , F { w ( t ) } = A δ ( f ) 2 + 1 j 2 π f .
  • Fourier transform of ideal π / 2 phase shifter (Hilbert transformer) filterimpulse response
  • With
    w ( t ) = 1 π t t > 0 0 t < 0 , F { w ( t ) } = - j f > 0 j f < 0 .
  • Linearity property
  • With F { w i ( t ) } = W i ( f ) ,
    F { a w 1 ( t ) + b w 2 ( t ) } = a W 1 ( f ) + b W 2 ( f ) .
  • Duality property With F { w ( t ) } = W ( f ) ,
    F { W ( t ) } = w ( - f ) .
  • Cosine modulation frequency shift property
  • With F { w ( t ) } = W ( f ) ,
    F { w ( t ) cos ( 2 π f c t + θ ) } = 1 2 e j θ W ( f - f c ) + e - j θ W ( f + f c ) .
  • Exponential modulation frequency shift property
  • With F { w ( t ) } = W ( f ) ,
    F { w ( t ) e j 2 π f 0 t } = W ( f - f 0 ) .
  • Complex conjugation (symmetry) property If w ( t ) is real valued,
    W * ( f ) = W ( - f ) ,
    where the superscript * denotes complex conjugation (i.e.,  ( a + j b ) * = a - j b ) . In particular, | W ( f ) | is even and W ( f ) is odd.
  • Symmetry property for real signals Suppose w ( t ) is real.
    If w ( t ) = w ( - t ) , then W ( f ) is real. If w ( t ) = - w ( - t ) , W ( f ) is purely imaginary.
  • Time shift property
  • With F { w ( t ) } = W ( f ) ,
    F { w ( t - t 0 ) } = W ( f ) e - j 2 π f t 0 .
  • Frequency scale property
  • With F { w ( t ) } = W ( f ) ,
    F { w ( a t ) } = 1 a W ( f a ) .
  • Differentiation property
  • With F { w ( t ) } = W ( f ) ,
    d w ( t ) d t = j 2 π f W ( f ) .
  • Convolution multiplication property
  • With F { w i ( t ) } = W i ( f ) ,
    F { w 1 ( t ) * w 2 ( t ) } = W 1 ( f ) W 2 ( f )
    and
    F { w 1 ( t ) w 2 ( t ) } = W 1 ( f ) * W 2 ( f ) ,
    where the convolution operator “ * ” is defined via
    x ( α ) * y ( α ) - x ( λ ) y ( α - λ ) d λ .
  • Parseval's theorem
  • With F { w i ( t ) } = W i ( f ) ,
    - w 1 ( t ) w 2 * ( t ) d t = - W 1 ( f ) W 2 * ( f ) d f .
  • Final value theorem
  • With lim t - w ( t ) = 0 and w ( t ) bounded,
    lim t w ( t ) = lim f 0 j 2 π f W ( f ) ,
    where F { w ( t ) } = W ( f ) .

Energy and power

  • Energy of a continuous time signal s ( t ) is
    E ( s ) = - s 2 ( t ) d t
    if the integral is finite.
  • Power of a continuous time signal s ( t ) is
    P ( s ) = lim T 1 T - T / 2 T / 2 s 2 ( t ) d t
    if the limit exists.
  • Energy of a discrete time signal s [ k ] is
    E ( s ) = - s 2 [ k ]
    if the sum is finite.
  • Power of a discrete time signal s [ k ] is
    P ( s ) = lim N 1 2 N k = - N N s 2 [ k ]
    if the limit exists.
  • Power Spectral Density
  • With input and output transforms X ( f ) and Y ( f ) of a linear filter with impulse response transform H ( f ) (such that Y ( f ) = H ( f ) X ( f ) ),
    P y ( f ) = P x ( f ) | H ( f ) | 2 ,
    where the power spectral density (PSD) is defined as
    P x ( f ) = lim T | X T ( f ) | 2 T ( Watts / Hz ) ,
    where F { x T ( t ) } = X T ( f ) and
    x T ( t ) = x ( t ) Π t T ,
    where Π ( · ) is the rectangular pulse [link] .

Z-transforms and properties

  • Definition of the Z-transform
    X ( z ) = Z { x [ k ] } = k = - x [ k ] z - k
  • Time-shift property
  • With Z { x [ k ] } = X ( z ) ,
    Z { x [ k - Δ ] } = z - Δ X ( z ) .
  • Linearity property
  • With Z { x i [ k ] } = X i ( z ) ,
    Z { a x 1 [ k ] + b x 2 [ k ] } = a X 1 ( z ) + b X 2 ( z ) .
  • Final Value Theorem for z -transforms If X ( z ) converges for | z | > 1 and all poles of ( z - 1 ) X ( z ) are inside the unit circle, then
    lim k x [ k ] = lim z 1 ( z - 1 ) X ( z ) .

Integral and derivative formulas

  • Sifting property of impulse
    - w ( t ) δ ( t - t 0 ) d t = w ( t 0 )
  • Schwarz's inequality
    - a ( x ) b ( x ) d x 2 - | a ( x ) | 2 d x - | b ( x ) | 2 d x
    and equality occurs only when a ( x ) = k b * ( x ) , where superscript * indicates complex conjugation (i.e.,  ( a + j b ) * = a - j b ).
  • Leibniz's rule
    d a ( x ) b ( x ) f ( λ , x ) d λ d x = f ( b ( x ) , x ) d b ( x ) d x - f ( a ( x ) , x ) d a ( x ) d x + a ( x ) b ( x ) f ( λ , x ) x d λ
  • Chain rule of differentiation
    d w d x = d w d y d y d x
  • Derivative of a product
    d d x ( w y ) = w d y d x + y d w d x
  • Derivative of signal raised to a power
    d d x ( y n ) = n y n - 1 d y d x
  • Derivative of cosine
    d d x cos ( y ) = - ( sin ( y ) ) d y d x
  • Derivative of sine
    d d x sin ( y ) = ( cos ( y ) ) d y d x

Matrix algebra

  • Transpose transposed
    ( A T ) T = A
  • Transpose of a product
    ( A B ) T = B T A T
  • Transpose and inverse commutativity If A - 1 exists,
    A T - 1 = A - 1 T .
  • Inverse identity If A - 1 exists,
    A - 1 A = A A - 1 = I .

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Source:  OpenStax, Software receiver design. OpenStax CNX. Aug 13, 2013 Download for free at http://cnx.org/content/col11510/1.3
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