spectrogrampsd#
[f, t, Sxx] = spectrogrampsd(x, fs, SegmentSize, OverlapSize, WindowName, nfft, outtype, OutputSmoothSize, dispout)
Description#
Calculate spectrogram following Welch’s method without averaging
Inputs#
- x
Input data
- fs=2;
Sampling frequency that data collected at in (Hz)
- SegmentSize=256;
Segment size, data are divided into the segments each has a total element equal to SegmentSize
- OverlapSize=0;
- Number of data points that are overlaped with data in previous segmentsOverlapSize is recomneded to be half of the SegmentSize
- WindowName=’hamming’;
- Window name, define if multiplying input data by window function or not (‘none’: not multiplying)‘none’,’rectangular’,’triangular’,’welch’,’hanning’,’hamming’,’gaussian’,’blackman’,’nuttall’,’blackmanharris’
- nfft=length(x);
Total number of points between 0 and fs that spectrum reports at is (nfft+1)
- outtype=’psd’;
- Define output type‘psd’: power spectral density, ‘db’: decibel
- OutputSmoothSize=0;
Window size for smoothing calculated spectrum (0, 1 or 2: not smoothing, reports original Welch spectrum)
- dispout=’no’;
Define to display outputs or not (‘yes’: display, ‘no’: not display)
Outputs#
- f
Frequency in (Hz)
- Sxx
Spectrogram (m^2/Hz) or (dB/Hz)
- t
Time at midpoint of each section (s)
Examples#
x(:,1)=detrend(0.5.*cos(2*pi*0.2*linspace(0,1023.5,2048))+(-0.1+(0.1-(-0.1))).*rand(1,1024*2));
[f,t,Sxx]=spectrogrampsd(x,2,256,128,'hamming',2048,'psd',0,'yes');
x(:,1)= chirp([0:0.001:4],50,2,150,'quadratic');
[f,t,Sxx]=spectrogrampsd(x,1000,128,64,'hamming',128,'db',0,'yes');