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Memristive Neuromorphic Systems

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If you have a question about this talk, please contact Wiesia R Hsissen.

Nanoscale memristors promise to be fabricated over CMOS substrates with densities of over 4×1012 elements per cm2 (which corresponds to a 50nm pitch). This would provide an overwhelming memory density very tightly coupled to CMOS computing elements. There are many fields where this disruptive advantage can be exploited. One of them is neuromorphic computing and learning systems. In this talk we present some ideas on how to exploit this technological possibility for implementing hybrid memristive-CMOS systems. We will start by introducing event-driven spiking neural systems, how they can learn through Spike-Timing-Dependent-Plasticity (STDP), and how this can be exploited with combined memristor-CMOS chips. Recent state-of-the-art results will be shown.

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