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Oscillatory nonlinear networks represent a circuit architecture for image and information processing. It has been shown that they can be exploited to implement associative and dynamic memories. It has also been shown that phase noise play an important role as a limiting key factor for the performances of oscillatory cells. A tool of paramount importance for the design of oscillatory networks and the...
We present a deterministic continuous-time recurrent neural network similar to CNN models, which can solve Boolean satisfiability (k-SAT) problems without getting trapped in non-solution fixed points. The model can be implemented by analog circuits, in which case the algorithm would take a single operation: the template (connection weights) is set by the k-SAT instance and starting from any initial...
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