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White noise is characterized by -
  • a)
    Gaussian probability density function
  • b)
    Power spectral density η/2δ(f)
  • c)
    Autocorrelation function depends only on delay τ 
  • d)
    Autocorrelation η/2δ(τ)
Correct answer is option 'D'. Can you explain this answer?
Most Upvoted Answer
White noise is characterized by -a)Gaussian probability density functi...
The spectral density of white noise is Uniform and the autocorrelation function of White noise is the Delta function.
The power spectral density is basically the Fourier transform of the autocorrelation function of the power signal, i.e.
Also, the inverse Fourier transform of a constant function is a unit impulse.
The power spectral density of white noise is given by:
SX(f) = η / 2 for all frequency 'f', i.e.
Now auto-correlation is inverse Fourier transform (IFT) of power spectral density function.
The inverse Fourier transform of the power spectrum of white noise will be an impulse as shown:
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Community Answer
White noise is characterized by -a)Gaussian probability density functi...
B) Power spectral density
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White noise is characterized by -a)Gaussian probability density functionb)Power spectral densityη/2δ(f)c)Autocorrelation function depends only on delay τd)Autocorrelationη/2δ(τ)Correct answer is option 'D'. Can you explain this answer?
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