What is wavelet coherence?
Wavelet Coherence. Coherence is one of the most widely used methods for measuring linear interactions. It is based on the Pearson correlation coefficient used in statistics but in frequency and time domain. It measures the mean resultant vector length (or consistency) of the cross-spectral density between two signals.
How do you calculate wavelet coherence?
The coherence is computed using the analytic Morlet wavelet. [ wcoh , wcs ] = wcoherence( x , y ) returns the wavelet cross-spectrum of x and y . You can use the phase of the wavelet cross-spectrum values to identify the relative lag between the input signals.
What is cross wavelet?
Cross wavelet analysis is a technique that was developed in the 1980s for the simultaneous analysis of two signals in the frequency domain and in the time domain. It is mainly used in fields such as oceanography (Jevrejeva et al., 2003), meteorology (Torrence and Compo, 1998), and econometrics (Rua and Nunes, 2009).
What is wavelet correlation?
Wavelet cross-correlation is simply a scale-localized version of the usual cross-correlation between two signals. In cross-correlation, you determine the similarity between two sequences by shifting one relative to the other, multiplying the shifted sequences element by element and summing the result.
How does Matlab calculate coherence?
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.
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 do wavelets do?
A wavelet is a mathematical function used to divide a given function or continuous-time signal into different scale components. Usually one can assign a frequency range to each scale component. Each scale component can then be studied with a resolution that matches its scale.
What is coherence Matlab?
The magnitude-squared coherence estimate is a function of frequency with values between 0 and 1. These values indicate how well x corresponds to y at each frequency.