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A sequence machine built with an asynchronous spiking neural network

In this paper we present the design of a sequence machine, a finite state automaton that can learn and predict sequences of symbols, built out of a network of asynchronous spiking neurons. We concentrate on aspects of building synchronous systems out of asynchronous neural components, such as stability and coherence of spike bursts forming symbols.