Spectral Analysis
coherence(vx, vy, n, r, [w])—Returns the coherence of vectors vx and vy. The signal vectors are divided into n overlapping intervals with fraction of overlap r. Each data segment is windowed with taper w.
The coherence function measures the linear dependence of one signal on another, and is equal to the squared magnitude of the cross spectrum of two signals divided by both power spectra, and ranges in value from zero to one. Values of 1 for the coherence function tend to indicate that both signals have strong noise-free components in that frequency band, while values of 0 indicate that there is mostly noise in that frequency band.
cspectrum(vx, vy, n, r, [w])—Returns the cross spectrum of vectors vx and vy. The signal vectors are divided into n overlapping intervals with fraction of overlap r. Each data segment is windowed with taper w.
pspectrum(v, n, r, [w])—Returns the power spectrum of v, computed by dividing v into n overlapping segments with overlap fraction r. Each data segment is windowed with taper w.
snr(vx, vy, n, r, [w])—Returns the signal-to-noise ratio for vx and vy. The signal vectors are divided into n overlapping segments with fraction of overlap r. Each data segment is windowed with taper w.
Arguments
v, vy, and vy are complex-valued signal vectors.
n is an integer between 1 and length(vx) representing the subdivisions of the input signals.
r is the fractional overlap between subdivisions, expressed as a number 0 ≤ r < 1.
w (optional) is an integer representing a windowing function index. A rectangular window is used if w is 0 or not specified.
The following table shows values for w and the windows they correspond to:
Value of w
Window
0
current default window
1
rectangular (default)
2
tapered rectangular
3
triangular
4
Hanning
5
Hamming
6
Blackman
7
Nuttall