Wenfeng Jing

发表

Towards establishing a meaningful and practical dynamics results for the unified RNN model

Chen Qiao, Hai-Bao Chen, Wenfeng Jing, 2015, Neurocomputing.

The general critical analysis for continuous-time UPPAM recurrent neural networks

Yu-Ping Wang, Jian Fang, Chen Qiao, 2016, Neurocomputing.

A More Efficient Preprocessing Method for Support Vector Classification

Deyu Meng, Zongben Xu, Wenfeng Jing, 2005, 2005 International Conference on Neural Networks and Brain.

Eliminating Vertical Stripe Defects on Silicon Steel Surface by Regularization

Deyu Meng, Zhiming Peng, Wenfeng Jing, 2011 .

The UPPAM continuous-time RNN model and its critical dynamics study

Zongben Xu, Chen Qiao, Wenfeng Jing, 2013, Neurocomputing.

A New Approach for Classification: Visual Simulation Point of View

Deyu Meng, Zongben Xu, Wenfeng Jing, 2005, ISNN.

A New Pre-processing Method for Regression

Deyu Meng, Zongben Xu, Wenfeng Jing, 2006, ISNN.

When Does Online BP Training Converge?

Zongben Xu, Wenfeng Jing, Rui Zhang, 2009, IEEE Transactions on Neural Networks.

A New Approach for Regression: Visual Regression Approach

Deyu Meng, Chen Xu, Wenfeng Jing, 2005, CIS.

Critical dynamical analysis for α-UAM RNNs without diagonal nonlinear requirements

Yan Shi, Chen Qiao, Wenfeng Jing, 2017, J. Intell. Fuzzy Syst..

Sparse kernel logistic regression based on L1/2 regularization

Chen Xu, Zhiming Peng, Wenfeng Jing, 2012, Science China Information Sciences.

Multiview deep learning based on tensor decomposition and its application in fault detection of overhead contact systems

Wenfeng Jing, Yansheng Gong, Xuewu Zhang, 2021 .

A Nested Residual Encoder-Decoder Network for Overhead Contact System Fastener Anomaly Detection

Wenfeng Jing, Qifan Guo, Cheng Zhang, 2021, IEEE Access.

Feature Back-Tracking with Sparse Deep Belief Networks

Wenfeng Jing, Cheng Zhang, Xuewu Zhang, 2021 .

Eliminating Vertical Stripe Defects on Silicon Steel Surface by L1/2 Regularization

Zhiming Peng, Wenfeng Jing, Chen Qiao, 2014 .