Results 21 to 30 of about 28,095 (262)
Fractional diffusion theory of balanced heterogeneous neural networks
Physical Review Research, 2021 Interactions of large numbers of spiking neurons give rise to complex neural dynamics with fluctuations occurring at multiple scales. Understanding the dynamical mechanisms underlying such complex neural dynamics is a long-standing topic of interest in ...
Asem Wardak, Pulin Gong
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Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
Sensors, 2023 A spiking neural network (SNN) is a type of artificial neural network that operates based on discrete spikes to process timing information, similar to the manner in which the human brain processes real-world problems.
Geunbo Yang +7 more
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Energy-Efficient Spiking Segmenter for Frame and Event-Based Images
Biomimetics, 2023 Semantic segmentation predicts dense pixel-wise semantic labels, which is crucial for autonomous environment perception systems. For applications on mobile devices, current research focuses on energy-efficient segmenters for both frame and event-based ...
Hong Zhang, Xiongfei Fan, Yu Zhang
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Models developed for spiking neural networks
MethodsX, 2023 Emergence of deep neural networks (DNNs) has raised enormous attention towards artificial neural networks (ANNs) once again. They have become the state-of-the-art models and have won different machine learning challenges. Although these networks are inspired by the brain, they lack biological plausibility, and they have structural differences compared ...
Shahriar Rezghi Shirsavar +2 more
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SpikeGoogle: Spiking Neural Networks with GoogLeNet‐like inception module
CAAI Transactions on Intelligence Technology, 2022 Spiking Neural Network is known as the third‐generation artificial neural network whose development has great potential. With the help of Spike Layer Error Reassignment in Time for error back‐propagation, this work presents a new network called ...
Xuan Wang +6 more
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Long-Tailed Characteristics of Neural Activity Induced by Structural Network Properties
Frontiers in Applied Mathematics and Statistics, 2022 Over the past few decades, neuroscience studies have elucidated the structural/anatomical network characteristics in the brain and their associations with functional networks and the dynamics of neural activity.
Sou Nobukawa, Sou Nobukawa
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Bifurcation Spiking Neural Network
J. Mach. Learn. Res., 2019 Spiking neural networks (SNNs) has attracted much attention due to its great potential of modeling time-dependent signals. The firing rate of spiking neurons is decided by control rate which is fixed manually in advance, and thus, whether the firing rate is adequate for modeling actual time series relies on fortune.
Shao-Qun Zhang +2 more
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HF-SNN: High-Frequency Spiking Neural Network
IEEE Access, 2021 As the third generation of neural networks, spiking neural network (SNN) motivated by neurophysiology enjoys considerable advances due to integrating different information, such as time and space.
Jing Su, Jing Li
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An Implementation of Actor-Critic Algorithm on Spiking Neural Network Using Temporal Coding Method
Applied Sciences, 2022 Taking advantage of faster speed, less resource consumption and better biological interpretability of spiking neural networks, this paper developed a novel spiking neural network reinforcement learning method using actor-critic architecture and temporal ...
Junqi Lu +4 more
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Building Logistic Spiking Neuron Models Using Analytical Approach
IEEE Access, 2019 Spiking neuron models are inspired by biological neurons. They can simulate the neuronal activities of the mammalian brains, such as spiking (integrator) and periodic oscillation (resonator).
Lei Zhang
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