文章列表

[50] Huaqing Zhang, Jian Wang*, Zhanquan Sun, Jacek M. Zurada, and Nikhil R. Pal. Feature Selection for Neural Networks Using Group Lasso Regularization.IEEE Transactions on Knowledge and Data Engineering, In Press. (SCI二区) >> Fulltext Link

[49] Yi-Fei Pu, Ni Zhang, Zheng-Ning Wang, Jian Wang*, Zhang Yi, Yan Wang, Ji-Liu Zhou. Fractional-Order Retinex for Adaptive Contrast Enhancement of Under-Exposed Traffic Images.  IEEE Intelligent Transportation Systems Magazine, In Press. (SCI二区) >> Fulltext Link

[48]  Jian Wang, Bingjie Zhang, Zhaoyang Sang, Yusong Liu, Shujun Wu, Quan Miao. Convergence of a modified gradient-based learning algorithm with penalty for single-hidden-layer feed-forward networks. Neural Computing & Applications, In Press. (SCI二区) >> Fulltext Link

[47] Tao Gao, Xiaoling Gong, Kai Zhang, Feng Lin, Jian Wang*, Tingwen Huang, Jacek M. Zurada. A recalling-enhanced recurrent neural network: Conjugate gradient learning algorithm and its convergence analysis. Information Sciences, 519: 273-288, 2020. (SCI 一区:算机科学) >> Fulltext Link 

[46] Xuetao Xie, Huaqing Zhang, Junze Wang, Qin Chang, Jian Wang*, Nikhil R. Pal. Learning optimized structure of neural networks by hidden node pruning with L1 regularization. IEEE Transactions on Cybernetics, 50(3): 1333-1346, 2020. (SCI>> Fulltext Link

[45] Zhanquan Sun, Feng Li, Huifen Huang, Jian Wang. Image steganalysis based on convolutional neural network and feature selection. Concurrency and Computation: Practice and Experience, 32:e5469, 2020. (SCI 四区>> Fulltext Link

[44] Hao Zhang, Kai Zhang*, Liming Zhang, James Sheng, Jun Yao, Jian Wang, Yongfei Yang. Construction and optimization of adaptive well pattern based on reservoir anisotropy and uncertainty. Journal of Petroleum Science and Engineering, 181: 1-19, 2019. (SCI二区>> Fulltext Link

[43] Ling Yu, Zhen Zhang, Xuetao Xie, Hua Chen, Jian Wang*. Unsupervised feature selection using RBF autoencoder. International Symposium on Neural Networks, 11554: 48-57, 2019. (EI)>> Fulltext Link

[42] Tao Gao, Zhen Zhang, Qin Chang*, Xuetao Xie, Peng Ren, Jian Wang*. Conjugate gradient-based Takagi-Sugeno fuzzy neural network parameter identification and its convergence analysis. Neurocomputing, 364: 168-181, 2019. (SCI二区)  >> Fulltext Link

[41] Bingjie Zhang , Yusong Liu , Jinde Cao*, Shujun Wu , Jian Wang*. Fully complex conjugate gradient-based neural networks using Wirtinger calculus framework: Deterministic convergence and its application. Neural Networks, 115: 50-64, 2019. (SCI一区) >> Fulltext Link

[40] Jian Wang, Qingquan Chang, Qin Chang, Yusong Liu and Nikhil R. Pal*. Weight noise injection-based MLPs with group lasso penalty: asymptotic convergence and application to node pruning. IEEE Transactions on Cybernetics, 49(12): 4346-4364, 2019. (SCI一区)>> Fulltext Link

[39] Qin Chang, Junze Wang, Huaqing Zhang, Lina Shi, Jian Wang, Nikhil R. Pal. Structure Optimization of Neural Networks with L1 Regularization on Gates.IEEE Symposium Series on Computational Intelligence, Bangalore, India, pp. 196-203, 2018.  >> Fulltext Link

[38] Bingjie Zhang, Junze Wang, Shujun Wu, Jian Wang, Huaqing Zhang. Fully Complex-Valued Wirtinger Conjugate Neural Networks with Generalized Armijo Search.International Conference on Intelligent Computing, 10956: 123-133, 2018. (EI) >> Fulltext Link

[37] Mingyue Zhu, Tao Gao, Bingjie Zhang, Qingying Sun, Jian Wang. An Efficient Elman Neural Networks Based on Improved Conjugate Gradient Method with Generalized Armijo Search. International Conference on Intelligent Computing, 10954: 1-7, 2018. (EI) >> Fulltext Link

[36] Tao Gao, Jian Wang*, Bingjie Zhang, Huaqing Zhang, Peng Ren, Nikhil R. Pal.A Polak-Ribiere-Polyak Conjugate Gradient-Based Neuro-Fuzzy Network and Its Convergence.IEEE Access, 6: 41551-41565, 2018. (SCI二区) >> Fulltext Link

[35] Tao Gao, Long Li, Zhen Zhang, Zhanquan Sun, Jian Wang. A New Parameter Identification Method for Type-1 TS Fuzzy Neural Network. The 15th International Symposium on Neural Networks, 10878: 200-207, 2018. (EI)   >> Fulltext Link

[34] Jian Wang, Chen Xu, Xifeng Yang, Jacek M. Zurada*. A novel pruning algorithm for smoothing feedforward neural networks based on group lasso method. IEEE Transactions on Neural Networks and learning Systems, 29(5): 2012-2024, 2018.  (SCI一区) >> Fulltext Link

[33] Jian Wang, Bingjie Zhang, Zhanquan Sun, Wenxue Hao, Qingying Sun*. A novel conjugate gradient method with generalized Armijo search for efficient training of feedforward neural networks. Neurocomputing, 275: 308-316, 2018.(SCI二区) >> Fulltext Link

[32] Hongmin Gao, Yichen Yang, Bingyin Zhang, Long Li, Huaqing Zhang, Shujun Wu. Feature Selection Using Smooth Gradient L1/2 Regularization. International Conference on Neural Information Processing, 10637: 160-170, 2017.  (EI) >> Fulltext Link

[31] Qin Liu, Zhaoyang Sang, Hua Chen, Jian Wang, Huaqing Zhang. An Efficient Algorithm for Complex-Valued Neural Networks Through Training Input Weights. International Conference on Neural Information Processing, 10637: 150-159, 2017.  (EI) >> Fulltext Link

[30] Bingjie Zhang, Tao Gao, Long Li, Zhanquan Sun, Jian Wang. An Improved Conjugate Gradient Neural Networks Based on a Generalized Armijo Search Method. International Conference on Neural Information Processing, 10637: 131-139, 2017. (EI) >> Fulltext Link

[29] Jian Wang, Yanqing Wen, Zhenyun Ye, Ling Jian, Hua Chen*. Convergence analysis of BP neural networks via sparse response regularization. Applied Soft Computing, 61: 354-363, 2017.  (SCI二区) >> Fulltext Link

[28] Jian Wang, Guoling Yang, Bingjie Zhang, Zhanquan Sun*, Yusong Liu, Jichao Wang. Convergence analysis of Caputo-type fractional order complex-valued neural networks.IEEE Access, 5: 14560-14571, 2017. (SCI二区) >> Fulltext Link

[27] Guoling Yang, Bingjie Zhang, Zhaoyang Sang, Jian Wang,Hua Chen. A Caputo-type Fractional-order gradient descent learning of BP neural networks. The 14th International Symposium on Neural Networks,  10261: 547-554, 2017. (EI)   >> Fulltext Link

[26] Jian Wang, Yanqing Wen, Yida Gou, Zhenyun Ye, Hua Chen*. Fractional-order gradient descent learning of BP neural networks with Caputo derivative. Neural Networks, 89: 19-30, 2017. (SCI一区) >> Fulltext Link

[25] Xian Shi, Jian Wang*, Xinmin Ge, Zhongying Han, Guanzheng Qu, Shu Jiang. A new method for rock brittleness evaluation in tight oil formation from conventional logs and petrophysical data. Journal of Petroleum Science and Engineering, 151: 169-182, 2017.(SCI三区) >> Fulltext Link

[24] Jian Wang, Qingling Cai, Qingquan Chang, Jacek M. Zurada. Convergence Analyses on Sparse Feedforward Neural Networks via Group Lasso Regularization.Information Sciences381: 250-269, 2017. (SCI二区) >> Fulltext Link

[23] 王健. 中外教合作教学模式对师生的能力影响研究. 黑江教育学院学, 35(8): 37-39, 2016. >> Fulltext Link

[22] Xian Shi, Gang Liu, Xiaoling Gong, Jialin Zhang, Jian Wang, Hongning Zhang. An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling. Mathematical Problems in Engineering, 3: 1-13, 2016. (SCI 四区>> Fulltext Link

[21] Xian Shi, Gang Liu, Yuanfang Cheng, Liu Yang, Hailong Jiang, Lei Chen, Shu Jiang, Jian Wang*. Brittleness index prediction in shale gas reservoirs based on efficient network models. Journal of Natural Gas Science and Engineering, 35: 673-685, 2016.  (SCI三区) >> Fulltext Link

[20] Jian Wang, Zhenyun Ye, Weifeng Gao, Jacek M. Zurada. Boundedness and Convergence Analysis of Weight Elimination for Cyclic Training of Neural Networks. Neural Networks, 82: 49-61, 2016.   (SCI二区)>> Fulltext Link

[19] Xiaoling Gong, Jian Wang, Yanjiang Wang, and Jacek M. Zurada. A Conjugate Gradient-based Efficient Algorithm for Training Single-hidden-layer Neural Networks.International Conference on Neural Information Processing, 9950: 470-478, 2016. (EI)  >> Fulltext Link

[18] Xian Shi, Jian Wang*, Gang Liu, Liu Yang, Xinmin Ge, Shu Jiang. Application of extreme learning machine and neural networks in total organic carbon content  prediction in organic shale with wire line logs. Journal of Natural Gas Science and Engineering, 33: 687-702, 2016.(SCI三区) >> Fulltext Link

[17] 王健国芳刘珊黄炳家研究性教学在教学中的案例分析. 南大学学:哲学社会科学版,  17: 170-171, 2015. >> Fulltext Link

[16] Jian Wang, Guoling Yang, Shan Liu, Jacek M. Zurada. Convergence Analysis of Multilayer Feedforward Networks Trained with Penalty Terms. Journal of Applied Computer Science Methods, 7(2): 89-103, 2015. >> Fulltext Link

[15] Bingjia Huang, Jian Wang, Yanqing Wen, Hongmei Shao, Jing Wang. Convergence analysis of inverse iterative algorithms for neural networks with L1/2 penalty. Journal of China University of Petroleum, 39(2): 164-170, 2015. (EI)  >> Fulltext Link

[14] Hongmei Shao, Jian Wang, Lijun Liu, Dongpo Xu, Wendi Bao. Relaxed conditions for convergence of batch BPAP for feedforward neural networks. Neurocomputing, 153: 174-179, 2015.  (SCI二区) >> Fulltext Link

[13] Yetian Fan, Wei Wu, Wenyu Yang, Qinwei Fan, Jian Wang. A pruning algorithm with L 1/2 regularizer for extreme learning machine. Journal of Zhejiang University Science C:Computer & Electronics 15(2):119-125, 2014.(SCI四区)>> Fulltext Link

[12] Jian Wang, Jacek M. Zurada, Yanjiang Wang, Jing Wang, Guofang Xie. Boundedness of Weight Elimination for BP Neural Networks. International Conference on Artificial Intelligence and Soft Computing,8467:155-165, 2014.(EI)>> Fulltext Link

[11] Yan Liu, Wei Wu, Qinwei Fan, Dakun Yang, Jian Wang. A modified gradient learning algorithm with smoothing L1/2 regularization for Takagi–Sugeno fuzzy models. Neurocomputing, 138: 229-237, 2014. (SCI二区)  >> Fulltext Link

[10] Wei Wu, Qinwei Fan, Jacek M. Zurada, Jian Wang, Dakun Yang, Yan Liu. Batch gradient method with smoothing L1/2 regularization for training of feedforward neural networks. Neural Networks, 50: 72-78, 2014.  (SCI二区) >> Fulltext Link

[9] Jan Chorowski, Jian Wang, Jacek M. Zurada. Review and performance comparison of SVM- and ELM-based classifiers. Neurocomputing, 128: 507-516, 2014. (SCI二区)  >> Fulltext Link

[8] Jian Wang. The Linear Algebra Teaching Methods Comparison and Analysis between China and America. Journal of Jilin Teachers Institute of Engineering and Technology, 28(2): 74-75, 2012. >> Fulltext Link

[7] Jian Wang, Wei Wu, Jacek M. Zurada. Computational Properties of Cyclic and Almost-Cyclic learning with momentum for feedforward neural networks. International Symposium on Neural Networks (ISNN), Jul 18-21, 7367:  545-554, 20122012.  (EI)  >> Fulltext Link

[6] Jian Wang, Wei Wu, Jacek M. Zurada*. Computational properties and convergence analysis of BPNN for cyclic and almost cyclic learning with penalty. Neural Networks, 33: 127-135, 2012.  (SCI二区)  >> Fulltext Link

[5] Jian Wang, Wei Wu, Jacek M. Zurada. Boundedness and convergence of MPN for cyclic and almost cyclic learning with penalty. International Joint Conference on Neural Networks, Jul 31-Aug 5, 2011, pp. 125-132, San Jose, California, USA. (EI)   >> Fulltext Link

[4] Jian Wang, Wei Wu, Zhengxue Li, Long Li. Convergence of gradient method for double parallel feedforward neural network. International Journal of Numerical Analysis and Modeling, 8(3): 484-495, 2011. (SCI三区>> Fulltext Link

[3] Jian Wang, Wei Wu, Jacek M. Zurada. Deterministic convergence of conjugate gradient method for feedforward neural networks. Neurocomputing, 74(14-15): 2368-2376, 2011.  (SCI二区>> Fulltext Link

[2] Wei Wu, Jian Wang, Mingsong Cheng, Zhengxue Li. Convergence analysis of online gradient method for BP neural networks. Neural Networks, 24(1): 91-98, 2011.  (SCI二区) >> Fulltext Link

[1] Jian Wang, Jie Yang, Wei Wu. Convergence of cyclic and almost-cyclic learning with momentum for feedforward neural networks.IEEE Transactions on Neural Networks, 22(8): 1297-1306, 2011.  (SCI一区) >> Fulltext Link