Signal Processing Toolbox

psdplot

Plot power spectral density (PSD) data.

Syntax

psdplot(Pxx,w)
psdplot(Pxx,w,'units')
psdplot(Pxx,w,'units','yscale')
psdplot(Pxx,w,'units','yscale','title')

Description

psdplot(Pxx,w) plots the power spectral density data contained in the vector Pxx at the frequencies specified in the vector w. The vectors Pxx and w must have the same length. The magnitude of the data vector Pxx is plotted in dB per radians per sample versus frequency w on one plot. The units for frequency on the plots are rad/sample.

psdplot(Pxx,w,'units') displays the frequency units according to the string 'units'. This string can be either:

• 'rad/sample' (default)
• 'Hz'

psdplot(Pxx,w,'units','yscale') displays the spectral density magnitude units according to the string 'yscale'. This string can be either:

• 'db' (default), for plotting the PSD in dB per units of frequency
• 'linear', for plotting the PSD in units of power per units of frequency

psdplot(Pxx,w,'units','yscale','title') uses the contents of the string 'title' as the title of the plot.

Examples

t = 0:0.001:0.3;
x = cos(2*pi*t*200) + randn(size(t)); 
[Pxx,w] = periodogram(x,[],'twosided',512);
psdplot(Pxx,w,'','','Sample PSD Plot')

See Also

freqzplot	Plot frequency response data.
pburg	Estimate the power spectral density using the Burg method.
pcov	Estimate the power spectral density using the covariance method.
peig	Estimate the pseudospectrum using the eigenvector method.
periodogram	Estimate the power spectral density using a periodogram.
pmcov	Estimate the power spectral density using the modified covariance method.
pmusic	Estimate the pseudospectrum with the MUSIC algorithm.
pwelch	Estimate the power spectral density using Welch's method.
pyulear	Estimate the power spectral density using the Yule-Walker AR method.

prony

pulstran