Averaging magnitude squared coherence across multiple time series

1. What is magnitude-squared coherence?
2. What is multiple coherence?
3. What is Mscohere in Matlab?
4. How to calculate coherence?

What is magnitude-squared coherence?

The magnitude-squared coherence (MSC) is a measure that estimates the extent to which one real- or complex-valued signal can be predicted from another real- or complex-valued signal using a linear model. It is also used as a measure of the similarities in the frequency content of two signals.

What is multiple coherence?

The multiple coherence is a spectral analysis tool allowing the estimation of the contribution of several, possibly partially, coherent inputs to one or several outputs.

What is Mscohere in Matlab?

cxy = mscohere( x , y ) finds the magnitude-squared coherence estimate, cxy , of the input signals, x and y . If x and y are both vectors, they must have the same length. If one of the signals is a matrix and the other is a vector, then the length of the vector must equal the number of rows in the matrix.

How to calculate coherence?

Coherence as a measure of confidence in transfer function H1

If a system is linear time-invariant with frequency response (Sxy(ω) = H(ω) Sxx(ω) ), then H(ω) = Sxy(ω)/Sxx(ω).