Spectral entropy formula

Spectral entropy is still: H = − ∑ m = 1 N P ( m ) log 2 P ( m ) . To compute the instantaneous spectral entropy given a time-frequency power spectrogram S(t,f), the probability distribution at time t is: P ( t , m ) = S ( t , m ) ∑ f S ( t , f ) .

1. What is spectral entropy in EEG?
2. How do you calculate spectral flatness?
3. How to calculate Shannon entropy in Matlab?
4. How to calculate entropy in Matlab?

What is spectral entropy in EEG?

Spectral Entropy, a normalised form of Shannon's entropy, which uses the power spectrum amplitude components of the time series for entropy evaluation [86,34]. It quantifies the spectral complexity of the EEG signal.

How do you calculate spectral flatness?

The spectral flatness is calculated by dividing the geometric mean of the power spectrum by the arithmetic mean of the power spectrum, i.e.: where x(n) represents the magnitude of bin number n.

How to calculate Shannon entropy in Matlab?

Shannon Entropy

Specify a one-level wavelet transform, use the default wavelet and wavelet transform. Obtain the unscaled Shannon entropy. Divide the entropy by log(n) , where n is the length of the signal. Confirm the result equals the scaled entropy.

How to calculate entropy in Matlab?

Entropy is defined as -sum(p. *log2(p)) , where p contains the normalized histogram counts returned from imhist .