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Conversion of a single-layer ANN to photonic SNN for pattern recognition
This work presents a complete conversion scheme for photonic spiking neural networks (SNNs). We verified that the output of an artificial neural...
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Error-Aware Conversion from ANN to SNN via Post-training Parameter Calibration
Spiking Neural Network (SNN), originating from the neural behavior in biology, has been recognized as one of the next-generation neural networks....
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CIRM-SNN: Certainty Interval Reset Mechanism Spiking Neuron for Enabling High Accuracy Spiking Neural Network
Spiking neural network (SNN) based on sparse trigger and event-driven information processing has the advantages of ultra-low power consumption and...
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Grid Search Optimization of Novel SNN-ESN Classifier on a Supercomputer Platform
This work is demonstrating the use of a supercomputer platform to optimise hyper-parameters of a proposed by the team novel SNN-ESN computational...
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Real-Time Adaptive Physical Sensor Processing with SNN Hardware
Spiking Neural Networks (SNNs) offer bioinspired computation based on local adaptation and plasticity as well as close biological compatibility. In...
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Accelerated Optimization for Simulation of Brain Spiking Neural Network on GPGPUs
As the application scenarios for large-scale spiking neural networks (SNN) increase, efficient SNN simulation becomes more essential. However,...
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DNM-SNN: Spiking Neural Network Based on Dual Network Model
In recent years, deep neural network (DNN) has shown excellent performance in many applications. However, the huge energy consumption leads to many...
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N-Neuron Simulation Using Multiprocessor Cluster
A growing number of research effort has been made to make the Simulation of the astonishing biophysical activities of the massively interconnected...
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Research Progress of spiking neural network in image classification: a review
Spiking neural network (SNN) is a new generation of artificial neural networks (ANNs), which is more analogous with the brain. It has been widely...
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GPU4SNN: GPU-Based Acceleration for Spiking Neural Network Simulations
Spiking Neural Networks (SNNs) are the most common and widely used artificial neural network models in bio-inspired computing. However, SNN...
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Spatiotemporal Backpropagation based on Channel Reward for Training High-Precision Spiking Neural Network
Spiking neural network (SNN) has attracted much attention due to its spatial–temporal information processing ability and high biological reliability....
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A generalized hardware architecture for real-time spiking neural networks
This article presents an area- and power-efficient hardware architecture for the brain-implantable spiking neural networks (SNNs). The proposed...
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Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision
Event-based vision sensors encode local pixel-wise brightness changes in streams of events rather than full image frames and yield sparse,...
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Cycle sampling neural network algorithms and applications
Two improved sampling neural network (SNN) algorithms, Cycle SNN (CSNN) and Rolling-Cycle SNN (RSNN), are proposed and optimized in this study, to...
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Biomimetic oculomotor control with spiking neural networks
Spiking neural networks (SNNs) are comprised of artificial neurons that, like their biological counterparts, communicate via electrical spikes. SNNs...
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SPMD-Based Neural Network Simulation with Golang
This paper describes the design and implementation of parallel neural networks (PNNs) with the novel programming language Golang. We follow in our...
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RMPE:Reducing Residual Membrane Potential Error for Enabling High-Accuracy and Ultra-low-latency Spiking Neural Networks
Spiking neural networks (SNNs) have attracted great attention due to their distinctive properties of low power consumption and high computing...
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Ebola optimization based spiking neural network for automatic hate speech recognition
In this paper, efficient machine learning technique is introduced to develop efficient machine learning model for hate speech recognition from the...
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A novel learning approach in deep spiking neural networks with multi-objective optimization algorithms for automatic digit speech recognition
Here, a new layered spiking neural network (SNN) learning framework is proposed using optimization algorithms for rapid and efficient pattern...
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Emergent communication enhances foraging behavior in evolved swarms controlled by spiking neural networks
Social insects such as ants and termites communicate via pheromones which allow them to coordinate their activity and solve complex tasks as a swarm,...
