Spiking neural networks, an introduction脉冲神经网络的生物学背景+两种采用脉冲编码的神经元模型概论本文介绍了脉冲神经网络的生物学背景,并将介绍两种采用脉冲编码的脉冲神经元模型。人工神经元的历史第一代:十五年之前McCulloch-Pitts提出,当神经元的加权的输入信号累积值高于阈值时,神经元输出一个二进制的高信号。
Spiking neural networks and dendrite morphological neural networks: an introductionNeural networksSpiking neural networksDendrite morphological neural networksTime-space informationdoi:10.1016/b978-0-12-820125-1.00022-1H. SossaCarlos D. Virgilio-G.
Spiking Neural Networks, an Introduction 来自 Semantic Scholar 喜欢 0 阅读量: 304 作者: J Vreeken 摘要: This paper gives an introduction to spiking neural networks, some biological background, and will present two models of spiking neurons that employ pulse coding. Networks of spiking neurons ...
1. Introduction 2. Spiking neural networks architecture 3. Spiking neural network for supervised learning procedure 4. Enhancements to SpikeProp algorithm 5. Results and discussion 6. Conclusion ReferencesShow full outline Cited by (26) Figures (6) Tables (15) Table 1 Table 2 Table 3 Table 4...
Keywords: Online learning, spiking neural networks 1. Introduction 由于从几乎任何来源收集数据并进行分析以实现基于数据的洞察力,从而实现成本和时间减少、新产品开发、优化产品或智能决策的可行性,大数据一词在过去十年中获得了进步的动力,其中包括利润。在这些大数据场景中,一些特性可能会起到相关作用:存储整个数据集...
A survey of robotics control based on learning-inspired spiking neural networks. Front Neurorobot. 2018;12:35. Article Google Scholar Sutton RS, Barto AG. Reinforcement Learning: An Introduction. Cambridge, MA, USA: MIT press; 2018. Google Scholar Stagsted R, Vitale A, Binz J, Bonde ...
Keywords: Online learning, spiking neural networks 1. Introduction 由于从几乎任何来源收集数据并进行分析以实现基于数据的洞察力,从而实现成本和时间减少、新产品开发、优化产品或智能决策的可行性,大数据一词在过去十年中获得了进步的动力,其中包括利润。在这些大数据场景中,一些特性可能会起到相关作用:存储整个数据集...
(1999). Adaptive neural coding dependent on the time-varying statistics of the somatic input curr... Jonghan,Shin - 《Neural Networks the Official Journal of the International Neural Network Society》 被引量: 52发表: 2001年 Spiking Neural Networks, an Introduction This paper gives an ...
1. Introduction Model accuracy has been the main factor to be enhanced by Machine Learning (ML) and Artificial Intelligence (AI) researchers in recent years with model efficiency being considered as a non-important criterion (García-Martín, Rodrigues, Riley, & Grahn, 2019). Nonetheless, the ...
· Quantization ·Error Propagation · Alexiewicz Norm1 IntroductionSpiking neural networks (SNNs) are artif icial neural networks of interconnected neurons that asynchronously processand transmit spatial-temporal information based on the occurrence of spikes that come from spatially distributed sensoryinput ...