Abstract
A new theoretical approach to graph processing, based on the transformation of a topological graph into a time-dependent periodic melody, is proposed. By using a self-tuning oscillatory dynamical network, graphs can be uniquely reconstructed from their melodies. This opens a perspective for a content-addressable memory invariant under large topology-preserving distortions.

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