Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage [PDF]
Brain SciencesBackground: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing ...
Yongqiang Zhang +5 more
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Free-space optical spiking neural network [PDF]
PLoS ONENeuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter challenges related to processing speed and thermal dissipation.
Reyhane Ahmadi +2 more
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Bio-Inspired Neural Network Dynamics-Aware Reinforcement Learning for Spiking Neural Network [PDF]
BiomimeticsArtificial Intelligence (AI) has seen rapid advancements in recent times, finding applications across various sectors and achieving notable successes. However, current AI models based on Deep Convolutional Neural Networks (DNNs) face numerous challenges,
Yu Zheng +3 more
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Study and Evaluation of Spiking Neural Network Model Based on Bee Colony Optimization [PDF]
Jisuanji kexue, 2023 In order to improve the training ability of Spiking neural network,this paper takes multi-label classification problem as the research breakthrough point and adopts bee colony algorithm to optimize the model.There are many neural network models based on ...
MA Weiwei, ZHENG Qinhong, LIU Shanshan
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Combinatorial optimization solving by coherent Ising machines based on spiking neural networks [PDF]
Quantum, 2023 Spiking neural network is a kind of neuromorphic computing that is believed to improve the level of intelligence and provide advantages for quantum computing.
Bo Lu, Yong-Pan Gao, Kai Wen, Chuan Wang
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Spiking Neural Network Model for Brain-like Computing and Progress of Its Learning Algorithm [PDF]
Jisuanji kexue, 2023 With the increasingly prominent limitations of deep neural networks in practical applications,brain-like computing spiking neural networks with biological interpretability have become the focus of research.The uncertainty and complex diversity of ...
HUANG Zenan, LIU Xiaojie, ZHAO Chenhui, DENG Yabin, GUO Donghui
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Accelerating spiking neural network simulations with PymoNNto and PymoNNtorch [PDF]
Frontiers in NeuroinformaticsSpiking neural network simulations are a central tool in Computational Neuroscience, Artificial Intelligence, and Neuromorphic Engineering research. A broad range of simulators and software frameworks for such simulations exist with different target ...
Marius Vieth +4 more
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Spiking Neural Network Based on Multi-Scale Saliency Fusion for Breast Cancer Detection
Entropy, 2022 Deep neural networks have been successfully applied in the field of image recognition and object detection, and the recognition results are close to or even superior to those from human beings.
Qiang Fu, Hongbin Dong
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Financial time series prediction using spiking neural networks. [PDF]
PLoS ONE, 2014 In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction.
David Reid +2 more
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A Bandwidth-Efficient Emulator of Biologically-Relevant Spiking Neural Networks on FPGA
IEEE Access, 2022 Closed-loop experiments involving biological and artificial neural networks would improve the understanding of neural cells functioning principles and lead to the development of new generation neuroprosthesis.
Gianluca Leone +2 more
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