Independent component analysis: algorithms and applications
Neural Networks
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A new strategy to identify the independent dynamics of spatially extended nonlinear networks is proposed. Starting from spatial modes theory an index has been defined as the number of relevant spatial modes and therefore identifies the system degree of freedom. The proposed methodology is validated by quantifying self-synchronization in three pattern-oriented systems: bidimensional Chua's circuit arrays, Hindmarsh-Rose neurons networks and fuzzy oscillators' lattices.