Results 101 to 110 of about 76,325 (312)
, 2017 Emulating spiking neural networks on analog neuromorphic hardware offers several advantages over simulating them on conventional computers, particularly in terms of speed and energy consumption.
Bellec, Guillaume +28 more
core +1 more source
SNNAX - Spiking Neural Networks in JAX
2024 International Conference on Neuromorphic Systems (ICONS)Spiking Neural Networks (SNNs) simulators are essential tools to prototype biologically inspired models and neuromorphic hardware architectures and predict their performance. For such a tool, ease of use and flexibility are critical, but so is simulation speed especially given the complexity inherent to simulating SNN.
Lohoff, Jamie +2 more
openaire +3 more sources
, 2020 Utilizing quantum computers to deploy artificial neural networks (ANNs) will bring the potential of significant advancements in both speed and scale. In this paper, we propose a kind of quantum spike neural networks (SNNs) as well as comprehensively evaluate and give a detailed mathematical proof for the quantum SNNs, including its successful ...
Chen, Yanhu +4 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won +3 more
wiley +1 more source
Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing
Advanced Functional Materials, EarlyView.A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann +8 more
wiley +1 more source
Fast learning without synaptic plasticity in spiking neural networks
Scientific ReportsSpiking neural networks are of high current interest, both from the perspective of modelling neural networks of the brain and for porting their fast learning capability and energy efficiency into neuromorphic hardware. But so far we have not been able to
Anand Subramoney +4 more
doaj +1 more source
Low Precision Quantization-aware Training in Spiking Neural Networks with Differentiable Quantization Function [PDF]
, 2023 Ayan Shymyrbay +2 more
openalex +1 more source
Advanced Healthcare Materials, EarlyView.Membrane fusion‐inspired nanomaterials offer transformative potential in diagnostics by mimicking natural fusion processes to achieve highly sensitive and specific detection of disease biomarkers. This review highlights recent advancements in nanomaterial functionalization strategies, signal amplification systems, and stimuli‐responsive fusion designs,
Sojeong Lee +9 more
wiley +1 more source
Advanced Healthcare Materials, EarlyView.This study introduces an innovative approach to treating intervertebral disc degeneration using ultrasound‐triggered in situ hydrogel formation. Proof‐of‐concept experiments using optimized biomaterial and ultrasound parameters demonstrate partial restoration of biomechanical function and successful integration into degenerated disc tissue, offering a ...
Veerle A. Brans +11 more
wiley +1 more source
Advanced Healthcare Materials, EarlyView.This study presents the first human neural organoid culture model capable of rapidly exhibiting long‐distance neural network propagation, thus delivering a system to experimentally investigate large‐scale communication during normal and diseased states.
Megh Dipak Patel +6 more
wiley +1 more source