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CS:Qu Hong

published: 2015-12-09 21:10:55       hits: 

name : Qu Hong Sex: Male phone:  
email: hongqu@uestc.edu.cn office-address:  
PH.D  Supervisor: Yes Master Supervisor: Yes
major: Computer Science and Technology
research interst: Neural Networks, Deep Learning, Spiking Coding, NP Problems, Path Problems
Biography: Dr. Quhong, 1977, Member of IEEE , Member of ACM. He focuses on computational intelligence and its applications, such as Neural Networks and Machine Learning. He has published more than 10 papers on 《IEEE Transactions on Neural Networks》,《IEEE Transactions on Cybernetics》,《IEEE Transactions on Circuits and Systems, Part I》,《Chaos, Solitons and Fractals》,《Neurocomputing》and《Neural Processing Letters》, and so on.
Education experience: 2007-2008 ARIS Lab, Univ. of Guelph, Postdoctor
Research Topic: Robot Path Planning
2003-2006 UESTC, Ph. D. Degree
Major: Computer Science and Technology
2000-2003 UESTC, M. S. Degree
Major: Computer Science and Technology
1996-2000 UESTC, B.S. Degree
Major: Computer Science and Technology
Selected Publications:
[1] Hong Qu, Zhang Yi and S.X. Yang. Efficient Shortest Path Tree Computation in Network Routing Based on Pulse Coupled Neural Networks. 《IEEE Transactions on Cybernetics》, Vol. 43, No. 03, pp. 995 - 1010, 2013.
[2] Hong Qu, S.X. Yang, Allan R. Willms and Zhang Yi. Real-Time Robot Path Planning Based on a Modified Pulse-Coupled Neural Network Model. 《IEEE Transcations on Neural Networks: Regular Papers》, Vol. 20, No. 11, pp. 1724-1739, 2009.
[3] Hong Qu, Zhang Yi and HuaJin Tang. Improving Local Minima of Columnar Competitive Model for TSPs. 《IEEE Transactions on Circuits and Systems, Part I: Regular Papers》, Vol. 53, No.6, pp. 1353-1362, 2006.
[4] Hong Qu, Xing Ke. An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots. 《Neurocomputing》, Vol. 120, No, 23, pp. 509–517, 2013.
[5] Hong Qu, S.X. Yang, Zhang Yi. A Novel Neural Network Method for Shortest Path Tree Computation. 《Applied Soft Computing》, Vol. 12, No. 10, pp. 3246–3259, 2012.
[6] Wei Suo and Hong Qu. Automatic Image Segmentation Based on PCNN with Adaptive Threshold Time Constant. 《Neurocomputing》, Vol. 74, No. 9, pp. 1485-1491, 2011.
[7] Hong Qu, Zhang Yi and Xiaobin Wang. A Winner-Take-All Networks of N Linear Threshold Neurons without Self-Excitatory Connections.  《Neural Processing Letters》,Vol. 29, No.3, pp. 143-154 ,2009.
[8] Xiaobin Wang, Hong Qu, and Zhang Yi. A modified pulse coupled neural network for Shortest Path Problem. 《Neurocomputing》, Vol. 72, No. 13-15. pp. 3028-3033, 2009.
[9] Hong Qu, Zhang Yi and Xiaobin Wang. Switching Analysis of Neural Networks with Nonsaturating Linear Threshold Transfer Functions, 《Neurocomputing》, Vol. 72, No.1-3, pp. 413-419, 2008.
[10] Hong Qu, Zhang Yi and HuaJin Tang. A Columnar Competitive Model for Solving Multi-Traveling Salesman Problem. 《Chaos, Solitons and Fractals》,  Vol. 31, pp. 1009-1029, 2007.
[11] Hong Qu, and Zhang Yi. A new algorithm for finding the shortest paths using PCNNs. 《Chaos, Solitons and Fractals》,Vol. 33, No. 4, pp. 1220-1229,  2007.
[12] Hong Qu and Zhang Yi. Convergence and Periodicity of Solutions for a Class of Discrete-Time Recurrent Neural Network with Two Neurons. 《Lecture Notes in Computer Science》, Vol. 3971, pp.291-296, 2006.
[13] Hong Qu, Zhang Yi and XiaoLin Xiang. Theoretical Analysis and Parameter Setting of Hopfield Neural Networks. 《Lecture Notes in Computer Science》, Vol.3496,  pp.739-745, 2005.
[14] Hong Qu and Zhang Yi. Global Attractivity of Discrete-Time Recurrent Neural Networks With Un-saturating Piecewise Linear Activation Functions. The Second IEEE International Conference on Neural Networks and Brain, 2005.