Latest Publications & Patents on Neuromorphic Computing

Publications & Patents on Neuromorphic Computing

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Neuromorphic computing is an interdisciplinary field that designs hardware and software systems inspired by the structure and function of biological neural networks, particularly the human brain. It employs non-von Neumann architectures, wherein processors and memory are closely integrated, enabling massively parallel computation, event-driven information processing, and low-power operation. Utilizing elements such as artificial spiking neurons and synapses, neuromorphic systems mimic the brain’s mechanisms for learning, adaptation, and sensory processing.

This is our latest selection of worldwide publications and patents in english on Neuromorphic Computing, between many scientific online journals, classified and focused on neuromorphic computing, spiking neural network, leaky integrate-and-fire neuron, memristor, neuromorphic, synaptic plasticity, axonal delay, silicon neuron, analog VLSI, Hebbian learning and spiking neural.

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    Topics covered: Neuromorphic computing, spiking neural network, leaky integrate-and-fire neuron, memristor, synaptic plasticity, axonal delay, silicon neuron, analog VLSI, Hebbian learning, non-von Neumann architectures, event-driven information processing, massively parallel computation, ISO/IEC 30170, IEEE 802154, IEC 61966-2-1, ISO/IEC 24765, and ISO 26262..

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