mscohere

Syntax

msc=mscohere(x,y)

msc=mscohere(x,y,window)

msc=mscohere(x,y,window,overlap)

msc=mscohere(x,y,window,overlap,nfft)

msc=mscohere(x,y,window,overlap,nfft,fs)

msc=mscohere(x,y,window,overlap,nfft,fs,range)

[msc,freq]=mscohere(...)

Inputs

x

The signal.

Type: double

Dimension: vector

window

The window size, or the window vector.

Type: double | integer

Dimension: scalar | vector

overlap

The number of overlapping points in adjacent windows.

Type: integer

Dimension: scalar

nfft

The size of the fft.

Type: integer

Dimension: scalar

fs

The sampling frequency.

Type: double

Dimension: scalar

range

The spectrum type: 'onesided' or 'twosided'.

Type: string

Outputs

msc

The mean squared coherence.

Type: vector

freq

The vector of frequencies corresponding to the coherence values.

Type: vector

Example

Coherence of two signals sharing common frequency components.

n = 4096;
fs = 256;
ts = 1/fs;
t = [0:ts:(n-1)*ts];
w1 = 2*pi*20;
w2 = 2*pi*32;
w3 = 2*pi*48;
w4 = 2*pi*60;
signal1 = 5*cos(w1*t) + 7*cos(w2*t) + 3*cos(w4*t);
signal2 = 7*cos(w1*t + (pi/2)) + 5*sin(w3*t) + 2*cos(w4*t + pi);
rand('seed', 2019);
signal1 = signal1 + randn(1, n);
signal2 = signal2 + randn(1, n);
window = ones(1, 64);
mscohere(signal1, signal2, window, 0, [], fs);

Figure 1. impz figure 1

Comments

With no return arguments, the function will automatically plot.

It is often recommended to remove the signal means prior to calling mscohere. The function does not remove the mean automatically.