Placing trainable nonlinear functions on connections in analogue networks enables efficient representation of smooth continuous targets with hardware transfer at projected 30 microwatt power.
The missing memristor found.Nature, 453(7191):80–83
8 Pith papers cite this work. Polarity classification is still indexing.
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A neuron-astrocyte network with dual-timescale memory reduces median path lengths up to sixfold in partially observable grid-world navigation tasks.
Rigid single-molecule junctions show memristive hysteresis from extrinsic mechanical rearrangements at contacts, not internal molecular states.
Annealing-optimized Ag/HZO memristors demonstrate artificial neurons with TTFS, spike-count, and firing-rate coding modes using minimal circuitry.
Gate-tunable analog memcapacitance is demonstrated in LaAlO3/SrTiO3 interface devices, originating from lateral floating gate charge localization with a supporting model.
Self-organising memristive networks exhibit collective nonlinear dynamics that can support physical learning with parallels to biological plasticity and potential for energy-efficient edge intelligence.
citing papers explorer
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Low-power analogue neural networks with trainable nonlinear connections for continuous control
Placing trainable nonlinear functions on connections in analogue networks enables efficient representation of smooth continuous targets with hardware transfer at projected 30 microwatt power.
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Dual-Timescale Memory in a Spiking Neuron-Astrocyte Network for Efficient Navigation
A neuron-astrocyte network with dual-timescale memory reduces median path lengths up to sixfold in partially observable grid-world navigation tasks.
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Memristive Switches in Rigid Conjugated Single-Molecule Junctions
Rigid single-molecule junctions show memristive hysteresis from extrinsic mechanical rearrangements at contacts, not internal molecular states.
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Multiple spiking functionalities in annealing-optimized Ag/Hf$_{0.5}$Zr$_{0.5}$O$_2$-based memristive neurons
Annealing-optimized Ag/HZO memristors demonstrate artificial neurons with TTFS, spike-count, and firing-rate coding modes using minimal circuitry.
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Gate-controlled analog memcapacitance in LaAlO3/SrTiO3 interface-based devices
Gate-tunable analog memcapacitance is demonstrated in LaAlO3/SrTiO3 interface devices, originating from lateral floating gate charge localization with a supporting model.
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Self-Organising Memristive Networks as Physical Learning Systems
Self-organising memristive networks exhibit collective nonlinear dynamics that can support physical learning with parallels to biological plasticity and potential for energy-efficient edge intelligence.
- Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations
- Beyond Silicon: Materials, Mechanisms, and Methods for Physical Neural Computing