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Développement d'un réseau de neurones impulsionnels sur silicium à synapses memristives

Abstract : Supported financially by ANR MHANN project, this work proposes an architecture ofspiking neural network in order to recognize pictures, where traditional processing units are inefficient regarding this. In 2008, a new passive electrical component had been discovered : the memristor. Its resistance can be adjusted by applying a potential between its terminals. Behaving intrinsically as artificial synapses, memristives devices can be used inside artificial neural networks.We measure the variation in resistance of a ferroelectric memristor (obtained from UMjCNRS/Thalès) similar to the biological law STDP (Spike Timing Dependant Plasticity) used with spiking neurons. With our measurements on the memristor and our network simulation (aided by INRIASaclay) we designed successively two versions of the IC. The second IC design is driven by specifications of the first IC with additional functionalists. The second IC contains two layers of a spiking neural network dedicated to learn a picture of 81 pixels. A demonstrator of hybrid neural networks will be achieved by integrating a chip of memristive crossbar interfaced with thesecond IC.
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Submitted on : Monday, March 30, 2015 - 5:23:05 PM
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  • HAL Id : tel-01137492, version 1


Gwendal Lecerf. Développement d'un réseau de neurones impulsionnels sur silicium à synapses memristives. Electronique. Université de Bordeaux, 2014. Français. ⟨NNT : 2014BORD0219⟩. ⟨tel-01137492⟩



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