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Explore the promising potential of memristive devices in neuromorphic systems in this 31-minute conference talk by Victor Erokhin at DSC EUROPE 24. Discover key features of memristor architecture, materials, production technologies, and properties. Learn how neuromorphic systems differ from traditional electronic circuits, including how challenges like noise and cross-talk actually benefit neuromorphic computing rather than hindering it. Understand the difficulties in hardware implementation of "classic" artificial neural networks (perceptrons) and the limitations of software-based approaches, particularly regarding power efficiency. Examine various artificial neural networks realized on memristive devices, including perceptrons, spiking neuron networks, and reservoir computing, with their respective advantages and limitations. See a demonstration of a memristive circuit that mimics Pavlov's dog learning through the STDP (Spike Timing Dependent Plasticity) algorithm, and learn about potential applications for neuro-prostheses, especially for patients with spinal cord injuries. This talk was presented on November 20th at DSC EUROPE 24 in Belgrade.
