In stationary subspace analysis (SSA) one assumes that the observable p-variate time series is a linear mixture of k-variate nonstationary and (p−k)-variate series. The aim then to estimate unmixing matrix which transforms observed multivariate onto components. classical approach data are projected subspaces by minimizing Kullback–Leibler divergence between Gaussian distributions, method only d...