# mscohere

Estimates the mean squared coherence of time domain signals.

## 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.
`window`- The window size, or the window vector.
`overlap`- The number of overlapping points in adjacent windows.
`nfft`- The size of the fft.
`fs`- The sampling frequency.
`range`- The spectrum type: 'onesided' or 'twosided'.

## Outputs

- msc
- The mean squared coherence.
- freq
- The vector of frequencies corresponding to the coherence values.

## 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);
```

## Comments

With no return arguments, the function will automatically plot.

The 'onesided' output has a length of `nfft/2+1` if `nfft` is even,
or `(nfft+1)/2` if `nfft` is odd.

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

`window`- A Hamming window with the largest length that produces eight data segments.
`overlap`- One half of the window length.
`nfft`- The window length. A larger value will pad zeros to each block of windowed data.
`fs`- 1.0 Hz.
`range`- 'onesided'