Design of a robust memristive spiking neuromorphic system with unsupervised learning in hardware
MM Adnan, S Sayyaparaju, SD Brown… - ACM Journal on …, 2021 - dl.acm.org
Spiking neural networks (SNN) offer a power efficient, biologically plausible learning
paradigm by encoding information into spikes. The discovery of the memristor has …
paradigm by encoding information into spikes. The discovery of the memristor has …
Choose your tools carefully: a comparative evaluation of deterministic vs. stochastic and binary vs. analog neuron models for implementing emerging computing …
Neuromorphic computing, commonly understood as a computing approach built upon
neurons, synapses, and their dynamics, as opposed to Boolean gates, is gaining large …
neurons, synapses, and their dynamics, as opposed to Boolean gates, is gaining large …
Bio-Inspired Memory Device Based Physical Reservoir Computing System to Solve Temporal and Classification Problems
MR Hossain - 2023 - search.proquest.com
In recent years, technological advancements in the field of computing have been limited by
the slowing down of Moore's law, which predicts the doubling of the number of transistors on …
the slowing down of Moore's law, which predicts the doubling of the number of transistors on …