  The optimal wavelet basis is used to develop quantitative, experimentally
applicable criteria for self-organization. The choice of the optimal wavelet is
based on the model of self-organization in the wavelet tree. The framework of
the model is founded on the wavelet-domain hidden Markov model and the optimal
wavelet basis criterion for self-organization which assumes inherent increase
in statistical complexity, the information content necessary for maximally
accurate prediction of the system's dynamics. At the same time the method,
presented here for the one-dimensional data of any type, performs superior
denoising and may be easily generalized to higher dimensions.
