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Spiking Recurrent Neural Networks Represent Task-Relevant Neural Sequences in Rule-Dependent Computation
Prefrontal cortical neurons play essential roles in performing rule-dependent tasks and working memory-based decision making. Motivated by PFC...
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Astrocyte-Integrated Dynamic Function Exchange in Spiking Neural Networks
This paper presents an innovative methodology for improving the robustness and computational efficiency of Spiking Neural Networks (SNNs), a critical...
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CMCI: A Robust Multimodal Fusion Method for Spiking Neural Networks
Human understand the external world through a variety of perceptual processes such as sight, sound, touch and smell. Simulating such biological...
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Encrypted-SNN: A Privacy-Preserving Method for Converting Artificial Neural Networks to Spiking Neural Networks
The transformation from Artificial Neural Networks (ANNs) to Spiking Neural Networks (SNNs) presents a formidable challenge, particularly in terms of...
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Evolutionary FPGA-Based Spiking Neural Networks for Continual Learning
Spiking Neural Networks (SNNs) constitute a representative example of neuromorphic computing in which event-driven computation is mapped to neuron...
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A tutorial on the formal framework for spiking neural P systems
The model of Spiking Neural P systems (SNP systems) is a widespread computational model in the area of membrane computing. It has numerous...
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Turing universality of sequential spiking neural P systems with polarizations as number accepting devices
To take full advantage of the information transfer mechanism of biological nervous systems, we consider a new computational model of spiking neural P...
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An Analytical Estimation of Spiking Neural Networks Energy Efficiency
Spiking Neural Networks are a type of neural networks where neurons communicate using only spikes. They are often presented as a low-power...
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Evolving Spiking Neural Network as a Classifier: An Experimental Review
The brain-inspired Spiking Neural Networks (SNNs) are considered as the third generation of neural networks for AI applications. The spiking neural...
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Optimization Driven Spike Deep Belief Neural Network classifier: a deep-learning based Multichannel Spike Sorting Neural Signal Processor (NSP) module for high-channel-count Brain Machine Interfaces (BMIs)
An Optimization Driven Spike Deep Belief Neural Networks is a type of neural network that is inspired by the functioning of the human brain. It is a...
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Analytic Investigation for Synchronous Firing Patterns Propagation in Spiking Neural Networks
Based on the moment closure method and mean field theory, a Gaussian random field is constructed to quantitatively and analytically characterize the...
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Conversion of Siamese networks to spiking neural networks for energy-efficient object tracking
Recently, spiking neural networks (SNNs), the third generation of neural networks, have shown remarkable capabilities of energy-efficient computing,...
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Classification of Alzheimer’s Disease Using Deep Convolutional Spiking Neural Network
Diagnosing Alzheimer’s Disease (AD) in older people using magnetic resonance imaging (MRI) is quite hard since it requires the extraction of highly...
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Power-efficient gesture sensing for edge devices: mimicking fourier transforms with spiking neural networks
One of the key design requirements for any portable/mobile device is low power. To enable such a low powered device, we propose an embedded gesture...
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A Spiking Neural Network Based on Neural Manifold for Augmenting Intracortical Brain-Computer Interface Data
Brain-computer interfaces (BCIs), transform neural signals in the brain into instructions to control external devices. However, obtaining sufficient...
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Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks
With the increasing demand for digital products, processes and services the research area of automatic detection of signal outliers in streaming data...
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Binarized spiking neural networks optimized with Nomadic People Optimization-based sentiment analysis for social product recommendation
Big data analytics is essential for many industries that use computing applications, like real-time purchasing and e-commerce. Big data is used to...
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Experimental demonstration of a photonic spiking neuron based on a DFB laser subject to side-mode optical pulse injection
We proposed and experimentally demonstrated a simple and novel photonic spiking neuron based on a distributed feedback (DFB) laser subject to...
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On-FPGA Spiking Neural Networks for Multi-variable End-to-End Neural Decoding
In the field of brain-machine interface (BMI), deep learning algorithms have been steadily advancing as the go-to instrument for the key task of...