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BP-Neural Network based- characterization of Electrographic Magnetohydrodynamic Signals in MR

机译：基于Bp神经网络的mR中电子磁流体动力学信号的表征

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Yurong Xu; Zhifeng Wang; Fillia S. Makedon; Justin D. Pearlman;
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年度 2008
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1. Signal reachability facilitates characterization of probabilistic signaling networks [J] . Haitham Gabr, Tamer Kahveci BMC Bioinformatics . 2015,第SUPPLEMENTa17期

机译：信号可达性有助于描述概率信号网络
2. Classification of modulation signals using statistical signal characterization and artificial neural networks [J] . Abdulnasir Hossen, Fakhri Al-Wadahi, Joseph A. Jervase Engineering Applications of Artificial Intelligence . 2007,第4期

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3. Optical Amplifier Response Estimation Considering Non-Flat Input Signals Characterization Based on Artificial Neural Networks [J] . Erick de Andrade Barboza, Allan Amaro Bezerra da Silva, José Carlos Pinheiro Filho, Journal of Lightwave Technology . 2021,第1期

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4. Characterization of the Magnetohydrodynamic Effect as a Signal from the Surface Electrocardiogram during Cardiac Magnetic Resonance Imaging [C] . G. M. Nijm, S. Swiryn, A. C. Larson, Conference on Computers in Cardiology . 2006

机译：心脏流体动力学效应作为心脏磁共振成像期间表面心电图的信号
5. Characterization of Cyclic-GMP-AMP Signaling and Novel Gene Networks in the Vibrio Seventh Pandemic Islands of El Tor Vibrio cholerae [D] . Severin, Geoffrey BlaineGraessley. 2020

机译：Cycrio-GMP-AMP信号传导和新型基因网络的特征在El vibrio Cholerae的vibrio第七大流行群中
6. Signal reachability facilitates characterization of probabilistic signaling networks [O] . Haitham Gabr, Tamer Kahveci 2015

机译：信号可达性有助于描述概率信号网络
7. Signal reachability facilitates characterization of probabilistic signaling networks [O] . 2015

机译：信号可达性有助于描述概率信号网络
8. Characterization of Radar Signals Using Neural Networks. [R] . Zahirniak, D. R. 1990

机译：用神经网络表征雷达信号。

BP-Neural Network based- characterization of Electrographic Magnetohydrodynamic Signals in MR

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