Articles with "spiking neural" as a keyword



A Sparse and Spike‐Timing‐Based Adaptive Photoencoder for Augmenting Machine Vision for Spiking Neural Networks

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Published in 2022 at "Advanced Materials"

DOI: 10.1002/adma.202202535

Abstract: The representation of external stimuli in the form of action potentials or spikes constitutes the basis of energy efficient neural computation that emerging spiking neural networks (SNNs) aspire to imitate. With recent evidence suggesting that… read more here.

Keywords: spike; photoencoder; spiking neural; timing based ... See more keywords

Timing-Dependent Spiking Neural Network: Board-Level Hardware Implementation with Photoelectroactive Van der Waals Synapses.

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Published in 2025 at "Advanced materials"

DOI: 10.1002/adma.202517613

Abstract: The rapid growth of unstructured data in applications such as autonomous systems and edge AI underscores the urgent need for energy-efficient, real-time computing exemplified by biological brains, where synaptic weights are adjusted according to the… read more here.

Keywords: hardware; spiking neural; dependent spiking; level ... See more keywords

All‐Ferroelectric Spiking Neural Networks via Morphotropic Phase Boundary Neurons

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Published in 2024 at "Advanced Science"

DOI: 10.1002/advs.202407870

Abstract: Artificial neurons and synapses are crucial for efficiently implementing spiking neural networks (SNNs) in hardware. The distinct functional requirements of artificial neurons and synapses present significant challenges in the implementation of area‐ and energy‐efficient SNNs.… read more here.

Keywords: phase boundary; spiking neural; neural networks; morphotropic phase ... See more keywords

Advancing Neural Networks: Innovations and Impacts on Energy Consumption

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Published in 2024 at "Advanced Electronic Materials"

DOI: 10.1002/aelm.202400258

Abstract: The energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level. Spiking Neural Networks (SNNs) are strongly suggested as… read more here.

Keywords: advancing neural; energy consumption; spiking neural; neural networks ... See more keywords

The maximum points-based supervised learning rule for spiking neural networks

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Published in 2019 at "Soft Computing"

DOI: 10.1007/s00500-018-3576-0

Abstract: As the third generation of neural networks, Spiking Neural Networks (SNNs) have made great success in pattern recognition fields. However, the existing training methods for SNNs are not efficient enough because of the temporal encoding… read more here.

Keywords: based supervised; maximum points; neural networks; supervised learning ... See more keywords
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Research on learning mechanism designing for equilibrated bipolar spiking neural networks

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Published in 2020 at "Artificial Intelligence Review"

DOI: 10.1007/s10462-020-09818-5

Abstract: Artificial Intelligence (AI) has become very popular due to both the increasing demands from applications and the booming of computer techniques. Spiking Neural Network (SNN), as the third generation of Artificial Neural Network, receives more… read more here.

Keywords: neural networks; equilibrated bipolar; spiking neural; learning mechanism ... See more keywords
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Logic Negation with Spiking Neural P Systems

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Published in 2020 at "Neural Processing Letters"

DOI: 10.1007/s11063-020-10324-6

Abstract: Nowadays, the success of neural networks as reasoning systems is doubtless. Nonetheless, one of the drawbacks of such reasoning systems is that they work as black-boxes and the acquired knowledge is not human readable. In… read more here.

Keywords: reasoning systems; spiking neural; logic negation; negation spiking ... See more keywords
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Training a Hidden Markov Model with a Bayesian Spiking Neural Network

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Published in 2018 at "Journal of Signal Processing Systems"

DOI: 10.1007/s11265-016-1153-2

Abstract: It is of some interest to understand how statistically based mechanisms for signal processing might be integrated with biologically motivated mechanisms such as neural networks. This paper explores a novel hybrid approach for classifying segments… read more here.

Keywords: hidden markov; markov model; model; spiking neural ... See more keywords

Design of spiking neural networks for blood pressure prediction during general anesthesia: considerations for optimizing results

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Published in 2017 at "Evolving Systems"

DOI: 10.1007/s12530-017-9176-x

Abstract: The ability to predict blood pressure changes during general anesthesia would assist anesthetists minimize the risk of complications due to hypotensive events. However, such prediction is not trivial. Evolving spiking neural networks are a relatively… read more here.

Keywords: spiking neural; prediction; blood pressure; design ... See more keywords

Low power, ultrafast synaptic plasticity in 1R-ferroelectric tunnel memristive structure for spiking neural networks

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Published in 2019 at "AEU - International Journal of Electronics and Communications"

DOI: 10.1016/j.aeue.2019.01.003

Abstract: Abstract This paper presents the design and implementation of a low power and ultrafast spike-timing dependent plasticity (STDP) of the spiking neural network (SNN) in a crossbar structure based on the ferroelectric tunnel memristor (FTM)… read more here.

Keywords: plasticity; power; low power; structure ... See more keywords
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A new scalable parallel adder based on spiking neural P systems, dendritic behavior, rules on the synapses and astrocyte-like control to compute multiple signed numbers

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Published in 2018 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.08.076

Abstract: Abstract This brief presents a scalable parallel neural adder circuit based on spiking neural P systems along with dendritic delays, dendritic feedback, rules on the synapses and astrocyte-like control to create a compact and highly… read more here.

Keywords: adder; based spiking; rules synapses; spiking neural ... See more keywords