Han Bingxin

M.S., Professor

Department of Electrical and Electronics, Shijiazhuang Tiedao University.

Education

•M.S., Industrial Automation, Tianjin University.

•B.S., Electrical Automation, Hebei Mechanical and Electrical Institute.


Research Areas

Electrical Engineering, Intelligent Control, Neural Networks, Information Fusion.


Research Profile

Mr. Bingxin Han is a Professor for Electrical and Automation in Shijiazhuang Tiedao University. His research fields include Intelligent Control, Neural Networks and Information Fusion. Mr. Han teaches Automatical Control Theory, Moden Control Theory, Computer Control, and Artificial Neural Networks at Shijiazhuang Tiedao University. Before joining University, he was an associate professor at Heibei Architecture Science and Technology Institute. Mr. Han has published more than 30 papers in journals and international conference.


Professional Honors and Awards

• Excellent Teacher of Shijianzhuang Tiedao University Award, 2006.

• Excellent Party member of Chinese Communist Party in Shijianzhuang Tiedao University Award, 2005.


Selected Recent Publications

1          Bingxin Han. Lixian Liu. Chenghong Wang. Stochastic System Identification Techniques of State Space Models and its Application. Proceedings of the 6th World Congress on Control and Automation. 2006, pp.1452-1455.

2          Bingxin Han. Liuxian Liu. Chaofeng He. Liqiang Du. Application of ANN on the Intelligent Temperature Sensor. Proceedings of the 6th World Congress on Control and Automation, 2006. pp.4956-4959.

3          3. Bingxin Han, Lixian Liu, etc. Modeling Method Based on Signal Flow GraphCorrelation Matrix and its Application. The 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010, pp756~761.

4           Li LipingHan BingxinLiu Lixian. A New Dynamic Neural Network Theory Algorithm. Microelectronics & Computer, 26(1), pp. 45-47, 2009.

5          Lixian Liu, Bingxin Han and Xiaobing Ren, Zhanfeng Gao. Learning Algorithm for the State Feedback Artificial Neural Network. The Sixth International Conference on Natural Computation (ICNC 2010), pp375~361.

6          Lixian Liu, Bingxin Han, Liqiang Du, and Zhanfeng Gao. A Neural Network Structure and Learning Algorithms with the Neuron Output Feedback. Third International Workshop on Advanced Computational Intelligence, 2010. pp21~25.

7           Liu, Lixian; Han, Bingxin; Li, Jinbo; Li, Xinling. A globally optimized state-space model identification method. Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA2008, 2008, pp.4736-4740.