We assume that all signals are white, zero-mean, Gaussian wide-sense stationary, and employ the independence assumption [7] under a steady-state condition, where the constraint violation is constant and the transform-domain weights are mutually uncorrelated (which occurs as the filter size N grows large [16]).
where the frequency non-selective channel fading coefficients hi as well as the AWGN samples wiare mutually uncorrelated zero-mean circularly symmetric complex Gaussian random variables.
As PCs are mutually uncorrelated, PCA is a practical method to aggregate correlated variables.
This model best reflects the association between frailty, its indicators and its underlying factors, in that particular indicators are explained by both a dominant general factor, (i.e. frailty), as well as seven specific factors, and these factors are mutually uncorrelated (see Figure 2).
As the signals are zero-mean and mutually uncorrelated, the following holds boldsymbol{Phi}_{boldsymbol{y}} t,k) = boldsymbol{Phi}_{boldsymbol{s}} t,k) + boldsymbol{Phi}{boldsymbol{i} t,k)} + boldsymbol{Phi}_{boldsymbol{v}} t,k).
Here, a simple movement model like the one drawn from mutually uncorrelated zero-mean white Gaussian noise processes, or more accurate movement model as of [27], can be used.
Thus, CSLVs are interpreted as mutually orthogonal space time evolutions in data, of which the amplitude time series are mutually uncorrelated.
{x k } are mutually uncorrelated of each other.
It is assumed that and are mutually uncorrelated and sound source signals are mutually independent.
We assume that the components of x u are mutually uncorrelated.
