Before revision:  Moreover, the dynamical network can be viewed as a time series of a non-stationary signal  and as such  can be partitioned for the automatic identification of key regions using well-established techniques for time series analysis and change point detection . Based on this interpretation we introduce a key-finding algorithm that does not rely on comparisons with pre-determined reference sets , as in the Krumhansl-Schmuckler model, or extensive corpora , as in machine-learning approaches .
After revision:  Moreover, the dynamical network can be viewed as a time series of a non-stationary signal and as such can be partitioned for the automatic identification of key regions using well-established techniques for time series analysis and change point detection . Based on this interpretation we introduce a key-finding algorithm that does not rely on comparisons with pre-determined reference sets , as in the Krumhansl-Schmuckler model, or extensive corpora . We demonstrate that the essential features of tonal harmony, centricity, referentiality, directedness and hierarchy, emerge naturally from the network topology and its scale-free properties .