A.15  Fourier Analysis: Properties

In the sequel, it is assumed that X(f), Y (f) and Z(f) are the Fourier transforms of x(t), y(t) and z(t), respectively. A pair (time / frequency) is denoted by . The following discussion assumes the Fourier transform, but the properties are valid for all four Fourier tools with subtle distinctions.

Linearity: if a signal x(t) = αy(t) + z(t) is obtained by multiplying y(t) by a constant α and summing the result to z(t), its transform is X(f) = αY (f) + Z(f). Linearity can be stated as:

αx(t) + βy(t) ⇔ αX(f) + βY (f).
(A.37)

Linearity can be decomposed into two properties: a) homogeneity and b) additivity, which correspond to the properties αx(t) ⇔ αX(f) and x(t) + y(t) ⇔ X(f) + Y (f), respectively.

Time-shift:

x(t − t0) ⇔ X(f)e−j2πft0 .
(A.38)

Scaling:

x(at) ⇔ 1 |a|X(f∕a).
(A.39)

Time-reversal (scaling with a = −1):

x(−t) ⇔ X(−f).
(A.40)

Complex-conjugate:

x(t) ⇔ X(−f).
(A.41)

Combined time-reversal and complex-conjugate:

x(−t) ⇔ X(f).
(A.42)

Multiplication:

x(t)y(t) ⇔ X(f)∗Y (f).
(A.43)

Frequency-shift:

x(t)ej2πf0t ⇔ X(f − f 0).
(A.44)

Convolution:

x(t)∗y(t) ⇔ X(f)Y (f).
(A.45)

Duality:

X(t) ⇔ x(−f).
(A.46)

Example: rect(t) ⇔sinc(f), then by duality sinc(t) ⇔rect(−f) = rect(f) (because rect(⋅) is an even function).

Energy and power conservation (Plancherel / Parseval theorem).
For energy signals:

E =−∞|x(t)|2dt =−∞|X(f)|2df.
(A.47)

For periodic (power) signals with fundamental period T0:

P = 1 T0<T0>|x(t)|2dt = k=−∞|c k|2,
(A.48)

where ck are the coefficients of the Fourier series of x(t).

Autocorrelation (Wiener-Khinchin theorem):

Rx(τ) =−∞x(t + τ)x(t)dt ⇔ X(f)X(f) = |X(f)|2.
(A.49)