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Sleep Stage Classification using NeuCube on SpiNNaker: a Preliminary Study
2020 International Joint Conference on Neural Networks (IJCNN), 2020This paper studies sleep stage classification using NeuCube, a Spiking Neural Network (SNN) architecture, simulated on SpiNNaker, a neuromorphic computer. The sleep electroencephalogram (EEG) time series is converted to spikes and provided as an input to NeuCube. Relevant feature vectors are extracted at different stages of training.
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An Online Intrusion Detection System to Cloud Computing Based on Neucube Algorithms
International Journal of Cloud Applications and Computing, 2018This article describes how as network traffic grows, attacks on traffic become more complicated and harder to detect. Recently, researchers have begun to explore machine learning techniques with cloud computing technologies to classify network threats. So, new and creative ways are needed to enhance intrusion detection system.
Ammar Almomani +4 more
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During the 1940s John Atanasoff with the help of one of his students Clifford E. Berry, in Iowa State College, created the ABC (Atanasoff-Berry Computer) that was the first electronic digital computer. The ABC computer was not a general-purpose one, but still, it was the first to implement three of the most important ideas used in computers nowadays ...
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Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks
International Conference on Interaction Design and Children, 2018This paper presents a new approach for spatio-temporal road traffic forecasting that relies on the adoption of the NeuCube architecture based on spiking neural networks. The NeuCube platform was originally conceived and designed to process electroencephalographic (EEG) signals considering their temporal component and their spatial source within the ...
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Feasibility of NeuCube spiking neural network architecture for EMG pattern recognition
2015 International Conference on Advanced Mechatronic Systems (ICAMechS), 2015Multichannel electromyography (EMG) signals have been used as human-machine interface (HMI) for the control of pattern-recognition based prosthetic system in recent years. This paper is a feasibility analysis of using recently proposed NeuCube spiking neural network (SNN) architecture for a 6-class recognition problem of hand motions.
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