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Neural dynamics solver for time-dependent infinity-norm optimization based on ACP framework with robot application 期刊论文
NEUROCOMPUTING, 2024, 卷号: 567, 页码: 9
作者:  Ma, Dexiu;  Liu, Mei;  Shang, Mingsheng
收藏  |  浏览/下载：10/0  |  提交时间：2024/02/23
Neural dynamics (ND)  ACP framework  Time-dependent infinity-norm optimization (TDINO)  Activation functions  
A noise-suppressing discrete-time neural dynamics model for solving time-dependent multi-linear M-tensor equation q 期刊论文
NEUROCOMPUTING, 2023, 卷号: 520, 页码: 240-249
作者:  Liu, Mei;  Wu, Huanmei;  Shang, Mingsheng
收藏  |  浏览/下载：53/0  |  提交时间：2023/02/07
Multi -linear M -tensor equation  Time dependence  Noise -suppressing discrete -time neural  dynamics (NSDTND)  
Modeling and Optimization of Sensitivity and Creep for Multi-Component Sensing Materials 期刊论文
NANOMATERIALS, 2023, 卷号: 13, 期号: 2, 页码: 21
作者:  Bi, Gangping;  Xiao, Bowen;  Lin, Yuanchang;  Yan, Shaoqiu;  Tang, Ying;  He, Songxiying;  Shang, Mingsheng;  He, Guotian
收藏  |  浏览/下载：509/0  |  提交时间：2023/04/06
RSM  SVR  NSGA-II  MWCNTs  MLG  Ni  magnetic field  sensitivity  creep  
Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 卷号: 18, 期号: 9, 页码: 5936-5948
作者:  Liu, Mei;  Zhang, Xiaoyan;  Shang, Mingsheng
收藏  |  浏览/下载：68/0  |  提交时间：2022/08/22
Optimization  Mathematical models  Computational modeling  Neural networks  Numerical models  Informatics  Vehicle dynamics  Equality and inequality constraints  noise-suppressing discrete-time neural dynamics (NSDTND) model  time-variant nonlinear optimization  
Dynamical Conventional Neural Network Channel Pruning by Genetic Wavelet Channel Search for Image Classification 期刊论文
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2021, 卷号: 15, 页码: 11
作者:  Chen, Lin;  Gong, Saijun;  Shi, Xiaoyu;  Shang, Mingsheng
收藏  |  浏览/下载：79/0  |  提交时间：2021/12/28
neural network pruning  neural architecture search  wavelet features  neural network compression  image classification  
Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 8, 页码: 4612-4623
作者:  Xin, Luo;  Yuan, Ye;  Zhou, MengChu;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：130/0  |  提交时间：2021/08/20
beta-divergence  big data  high-dimensional and sparse (HiDS) matrix  industrial application  learning algorithm  non-negative latent factor (NLF) analysis  recommender system  
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 7, 页码: 4285-4296
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Zhou, MengChu
收藏  |  浏览/下载：204/0  |  提交时间：2021/08/20
Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)  
An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 6, 页码: 3522-3532
作者:  Luo, Xin;  Wang, Zidong;  Shang, Mingsheng
收藏  |  浏览/下载：82/0  |  提交时间：2021/08/20
High-dimensional and sparse (HiDS) data  industrial application  instance-frequency  non-negative latent factor analysis (NLFA)  recommender system  regularization  
An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载：42/0  |  提交时间：2022/08/22
High-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  L-1 norm  L-2 norm  recommender system (RS)  
Lower limb movement intention recognition for rehabilitation robot aided with projected recurrent neural network 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2021, 页码: 12
作者:  Liu, Mei;  Peng, Bo;  Shang, Mingsheng
收藏  |  浏览/下载：123/0  |  提交时间：2021/05/17
Projected recurrent neural network (PRNN)  Lower limb movement  Intention recognition