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ORCIDInformation Sciences, Volume 364-365
Volume 364-365, October 2016
- Yuan Ge
, Xiaoxin Zhang, Qigong Chen, Ming Jiang:
Initialization of the HMM-based delay model in networked control systems. 1-15 - Yuwu Lu, Zhihui Lai, Yong Xu, Jane You, Xuelong Li, Chun Yuan:
Projective robust nonnegative factorization. 16-32 - Sihua Yi, Nan Jiang, Bin Feng, Xinggang Wang, Wenyu Liu:
Online similarity learning for visual tracking. 33-50 - Wesley Nunes Gonçalves, Núbia Rosa da Silva, Luciano da Fontoura Costa, Odemir Martinez Bruno:
Texture recognition based on diffusion in networks. 51-71 - Kalyan Goswami, Jong-Hyeok Lee, Byung-Gyu Kim:
Fast algorithm for the High Efficiency Video Coding (HEVC) encoder using texture analysis. 72-90 - Wen Sheng Du, Bao Qing Hu:
Attribute reduction in ordered decision tables via evidence theory. 91-110 - Fenghua He, Shaoshuai Mou, Ji Liu, A. Stephen Morse:
Convergence rate on periodic gossiping. 111-125
- Dianhui Wang:
Editorial: Randomized algorithms for training neural networks. 126-128 - Alexander N. Gorban, Ivan Yu. Tyukin, Danil V. Prokhorov, Konstantin I. Sofeikov:
Approximation with random bases: Pro et Contra. 129-145 - Le Zhang, Ponnuthurai N. Suganthan:
A survey of randomized algorithms for training neural networks. 146-155 - Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
A semi-supervised random vector functional-link network based on the transductive framework. 156-166 - L. Xie, Y. Yang, Z. Zhou, Jinchuan Zheng, M. Tao, Zhihong Man:
Dynamic neural modeling of fatigue crack growth process in ductile alloys. 167-183 - Mohd-Hanif Yusoff, Joseph Chrol-Cannon, Yaochu Jin:
Modeling neural plasticity in echo state networks for classification and regression. 184-196 - Erick De la Rosa, Wen Yu:
Randomized algorithms for nonlinear system identification with deep learning modification. 197-212 - Ayodeji A. Akinduko, Evgeny M. Mirkes, Alexander N. Gorban:
SOM: Stochastic initialization versus principal components. 213-221 - Yu-Lin He, Xizhao Wang, Joshua Zhexue Huang:
Fuzzy nonlinear regression analysis using a random weight network. 222-240
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