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An Attempt to Analyze a Human Nervous System Algorithm for Sensing Earthquake Precursors
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作者 Da Cao 《Open Journal of Earthquake Research》 2023年第1期1-25,共25页
We statistically validate the 2011-2022 earthquake prediction records of Ada, the sixth finalist of the 2nd China AETA in 2021, who made 147 earthquake predictions (including 60% of magnitude 5.5 earthquakes) with a p... We statistically validate the 2011-2022 earthquake prediction records of Ada, the sixth finalist of the 2nd China AETA in 2021, who made 147 earthquake predictions (including 60% of magnitude 5.5 earthquakes) with a prediction accuracy higher than 70% and a confidence level of 95% over a 12-year period. Since the reliable earthquake precursor signals described by Ada and the characteristics of Alfvén waves match quite well, this paper proposes a hypothesis on how earthquakes are triggered based on the Alfvén (Q G) torsional wave model of Gillette et al. When the plume of the upper mantle column intrudes into the magma and lithosphere of the soft flow layer during the exchange of hot and cold molten material masses deep inside the Earth’s interior during ascent and descent, it is possible to form body and surface plasma sheets under certain conditions to form Alfven nonlinear isolated waves, and Alfven waves often perturb the geomagnetic field, releasing huge heat and kinetic energy thus triggering earthquakes. To explain the complex phenomenon of how Ada senses Alvfen waves and how to locate epicenters, we venture to speculate that special magnetosensory cells in a few human bodies can sense earthquake precursors and attempt to hypothesize an algorithm that analyzes how the human biological nervous system encodes and decodes earthquake precursors and explains how human magnetosensory cells can solve complex problems such as predicting earthquake magnitude and locating epicenters. 展开更多
关键词 Earthquake Prediction Earthquake Precursors Mantle Column Plume ASTHENOSPHERE Alfven Isolated Waves Human Magnetic Induction Cells neuronal spikes Bayesian Algorithm
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基于奇异谱熵的神经元峰电位分类技术研究
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作者 钟华 范影乐 +2 位作者 杨勇 杨文伟 李轶 《航天医学与医学工程》 CAS CSCD 北大核心 2011年第1期65-70,共6页
目的实现神经元峰电位(spike)的准确检测和分类,为神经信号的后续分析和解码提供前提条件。方法采用改进的阈值法,从植入式多电极阵列采集的含噪神经电信号中检测出有效的峰电位;并提出利用奇异谱熵,来描述在奇异值分解下峰电位特征;通... 目的实现神经元峰电位(spike)的准确检测和分类,为神经信号的后续分析和解码提供前提条件。方法采用改进的阈值法,从植入式多电极阵列采集的含噪神经电信号中检测出有效的峰电位;并提出利用奇异谱熵,来描述在奇异值分解下峰电位特征;通过Kolmogorov-Smirnov检验降低特征维数,采用交互式方式挑选聚类性能较佳的二维特征向量;最后结合C均值聚类算法实现峰电位分类。结果本文提出的峰电位奇异谱熵特征使多组仿真和真实神经电生理信号获得了较为理想的聚类效果,且仿真数据分类准确率几乎都达到98%以上。结论基于奇异谱熵的峰电位特征提取,能够较好地表达和区分各类别峰电位的动态特性,可以作为峰电位有效的分类依据。 展开更多
关键词 峰电位分类 奇异谱熵 Kolmogorov-Smirnov检验
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