written 7.8 years ago by | • modified 7.8 years ago |
**Mumbai University > Electronics and Telecommunication Engineering > Sem 5 > Random Signal Analysis
Marks: 10M
Year: Dec 2015
written 7.8 years ago by | • modified 7.8 years ago |
**Mumbai University > Electronics and Telecommunication Engineering > Sem 5 > Random Signal Analysis
Marks: 10M
Year: Dec 2015
written 7.8 years ago by |
Power Spectral Density
Definition:
If {X (t)} is a stationary process (either in a strict sense or wide sense) with autocorrelation function R(τ), then the Fourier transform of R(τ) is called the power spectral density function of {X(t)} and denoted as $S_{xx}$ (ω) or $S_x$ (ω).
Thus $S_x$ (ω)=$∫_{-∞}^∞ R(τ) e^{-iωτ} dτ$
Or $S_x$ (f)=$∫_{-∞}^∞ R(τ) {e^{-i2πfτ}} dτ$
Significance:
Power Spectral Density (PSD) is the frequency response of a random or periodic signal. It tells us where the average power is distributed as a function of frequency.
The PSD is deterministic, and for certain types of random signals is independent of time (The signal has to be stationary, which means that the statistics do not change as a function of time) .This is useful because the Fourier transform of a random time signal is itself random, and therefore of little use calculating transfer relationships (i.e., finding the output of a filter when the input is random.