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Prediction of Potentially Suitable Distributions of Codonopsis pilosula in China Based on an Optimized MaxEnt Model 期刊论文
FRONTIERS IN ECOLOGY AND EVOLUTION, 2021, 卷号: 9, 页码: 17
作者:  Yan, Huyong;  He, Jiao;  Xu, Xiaochuan;  Yao, Xinyu;  Wang, Guoyin;  Tang, Lianggui;  Feng, Lei;  Zou, Limin;  Gu, Xiaolong;  Qu, Yingfei;  Qu, Linfa
收藏  |  浏览/下载:48/0  |  提交时间:2022/08/22
optimized MaxEnt  Codonopsis pilosula  regularization multiplier  feature combination  potential distribution  multivariate environmental similarity surface analysis  
A theoretical model of a flexible capacitive pressure sensor with microstructured electrodes for highly sensitive electronic skin 期刊论文
Journal of Physics D: Applied Physics, 2021, 卷号: 55, 期号: 9
作者:  Yang,Weidong;  Ding,Wenxuan;  Liu,Menglong;  Yang,Jun;  Li,Mao
收藏  |  浏览/下载:115/0  |  提交时间:2021/12/23
electronic skin  theoretical modeling  sensitivity  capacitive pressure sensor  microstructured electrode  
Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Luo, Xin;  Liu, Zhigang;  Jin, Long;  Zhou, Yue;  Zhou, MengChu
收藏  |  浏览/下载:53/0  |  提交时间:2022/08/22
Detectors  Convergence  Symmetric matrices  Social networking (online)  Analytical models  Tuning  Computational modeling  Community detection  convergence analysis  graph regularization  nonnegative multiplicative update (NMU)  social network analysis  symmetric and nonnegative matrix factorization (SNMF)  
Recurrent Neural Dynamics Models for Perturbed Nonstationary Quadratic Programs: A Control-Theoretical Perspective 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Qi, Yimeng;  Jin, Long;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载:47/0  |  提交时间:2022/08/22
Computational modeling  Mathematical model  Neural networks  Control theory  Analytical models  Real-time systems  Numerical models  Control-theoretical techniques  perturbed nonstationary quadratic program (QP)  recurrent neural dynamics  robustness theoretical analysis