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西南大學電子信息工程學院研究生導師何興介紹如下：

何興，男，漢族，中共黨員，四川巴中人，西南大學電子信息工程學院副教授，碩士生導師。研究領域包括：神經(jīng)網(wǎng)絡，智能電網(wǎng)，分岔理論，神經(jīng)動力學優(yōu)化理論，非線性動力系統(tǒng)等。目前主持國家自然科學基金2項和重慶市科委項目1項。

近年來，以第一作者或通訊作者身份發(fā)表或錄用SCI論文20余篇，其中包括IEEE Trans. Control Syst. Technol., IEEE Trans. Neural Netw. Learn. Syst., IEEE Trans. Cybernetics, IEEE Trans. Syst.，Man Cybern.: Syst.，Neural Networks，Journal of the Franklin Institute, Nonlinear Analysis：RWA, Science China，中國科學 等國內(nèi)外著名期刊, 并且擔任多個國際期刊和學術會議的審稿人, 如IEEE TNNLS，IEEE TSMC-A，IEEE TCYB， IEEE TII, IEEE TSG, WCCI2014，ICONIP 2012，ISNN2013等。
 
聯(lián)系郵箱：

hexingdoc@swu.edu.cn, hexingdoc@hotmail.com.

學習和工作經(jīng)歷

2014.01-現(xiàn)在     西南大學   電子信息工程學院 副教授，碩士生導師
2016.8-2018.8    中科院自動化研究所     博士后
2015.12-2016.02  香港城市大學          訪問學者
2009.9-2013.12   重慶大學   計算機學院  工學博士
2012.11-2013.10   Texas A&M University at Qatar (Research Assistant)
2005.9-2009.7    貴州大學   理學院   理學學士

獲獎情況：

2017重慶市自然科學一等獎（排名第5），2018.1.15
西南大學 優(yōu)秀研究生班主任  2018.01
重慶市優(yōu)秀博士論文    2016.9    
重慶大學優(yōu)秀博士論文  2015.9

科研項目主持：

1. 國家自然科學基金面上項目：基于神經(jīng)動力學算法的多微網(wǎng)互聯(lián)模式下的需求響應策略， 2018.01-2021.12.
2. 國家自然科學青年基金：具有時滯項的離散慣性神經(jīng)網(wǎng)絡的余維2分岔，2015/01-2017/12.
3. 重慶市基礎與前沿研究計劃一般項目：時滯離散Hopfied神經(jīng)網(wǎng)絡的余維2分岔，2014/07-2017/06.

指導研究生創(chuàng)新項目

1. 符早 中央高�；�本科研業(yè)務費一般項目學生項目：分布式神經(jīng)網(wǎng)絡算法研究及其在智能電網(wǎng)中的應用  2016.05-2016.12.
2. 趙友  中央高校基本科研業(yè)務費一般項目學生項目：基于ADMM算法的智能電網(wǎng)中動態(tài)經(jīng)濟分配問題的研究  2017.05-2017.12

指導本科生獲獎 

1. 葛靈普等，全國大學生數(shù)學建模重慶賽區(qū)二等獎， 2015年
2. 孫淼等，  美國大學生數(shù)學建模三等獎，         2017年
3. 汪天才，  西南大學本科優(yōu)秀畢業(yè)論文二等獎，   2017年
 
主要論文

1.  第一作者論文

[1]Xing He, Junzhi Yu, Tingwen Huang, Chaojie Li, Distributed Power Management for Dynamic Economic Dispatch in the Multi-micro-grids Environment, IEEE Transactions on Control Systems Technology, 2018,  DOI: 10.1109/TCST.2018.2816902.
[2] Xing He，Daniel W.C. Ho, Tingwen Huang, Junzhi Yu, Haitham Abu-Rub and Chaojie Li， Second-Order Continuous-Time Algorithms for Economic Power Dispatch in Smart Grids, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017. DOI: 10.1109/TSMC.2017.2672205.
[3] Xing He, Tingwen Huang, Junzhi Yu, Chuandong Li and Chaojie Li, An Inertial Projection Neural Network for Solving Variational Inequalities, IEEE Transactions on Cybernetics, 47(3)，809-814，2017.
[4] Xing He, Chuandong Li, Tingwen Huang, Chaojie Li, and Junjian Huang, A Recurrent Neural Network for Solving Bilevel Linear Programming Problem. IEEE Transactions on Neural Networks and Learning Systems, 25(4), 824-830, 2014.
[5] Xing He, Chuandong Li, Tingwen Huang, Chaojie Li，Bogdanov-Takens Singularity in Tri-Neuron Network With Time Delay，IEEE Transactions on Neural Networks and Learning Systems, 24(6), 1001-1007, 2013.
[6] Xing He, Tingwen Huang, et al. A Continuous-Time Algorithm for Distributed Optimization Based on Multiagent Networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, DOI:10.1109/TSMC.2017.2780194.
[7] Xing He, Junzhi Yu, Tingwen Huang, Chuandong Li, and Chaojie Li, Neural networks for solving Nash Equilibrium problem in application of multiuser power control, Neural Networks 57(9), 73-78, 2014.
[8] Xing He , Chuandong Li*, Tingwen Huang and Chaojie Li, Codimension two bifurcation in a delayed neural network with unidirectional coupling. Nonlinear analysis: Real World Application 14(2), 1191-1202, 2013.
[9] Xing He*, Chuandong Li, Tingwen Huang and Junzhi Yu, Bifurcation behaviors of an Euler discretized inertial delayed neuron model, Science China Technological Sciences, 59 (3)：418~427, 2016.
[10] Xing He*, Chuandong Li, Tingwen Huang, Junjian Huang, Zero-Hopf singularity in bidirectional ring network model with delay. Nonlinear Dynamics, 78: 2605-2616, 2014.

2. 通訊作者論文

[1] Chaojie Li, Xinghuo Yu, Tingwen Huang, Guo Chen and Xing He*, A Generalized Hopfield Network for Nonsmooth Constrained Convex Optimization: Lie Derivative Approach, IEEE Transactions on Neural Networks and Learning Systems, 27(2), 308-321, 2016.
[2] You Zhao, Xing He*, Tingwen Huang, et al. Smoothing inertial projection neural network for minimization Lp− q in sparse signal reconstruction, Neural Networks, 99, 31-41, 2018.
[3] Zao Fu, Xing He*, Tingwen Huang and Haitham Abu-Rub, A distributed continuous time algorithm for maximize social welfare in micro grid, Journal of the Franklin Institute, 353(15), 3966-3984，2016.
[4] 符早，何興*，李傳東，黃廷文，分布式一致性算法在微網(wǎng)社會福利問題中的應用. 中國科學: 信息科學,  2016, DOI:10.1360/N112016-00112.
[5] Ting Deng, Xing He*, Zhigang Zeng, Recurrent neural network for combined economic and emission dispatch，Applied Intelligence，https://doi.org/10.1007/s10489-017-1072-3，2017.
[6] Tiancai Wang, Xing He*, Tingwen Huang, Chuandong Li, Wei Zhang，Collective neurodynamic optimization for economic emission dispatch problem considering valve point effect in microgrid，Neural Networks, 93, 126-136, 2017
[7] Yao Yao, Xing He*, Tingwen Huang, Chaojie Li, and Dawen Xia, A projection neural network for optimal demand response in smart grid environment, Neural Computing Applications, 2016, DOI:10.1007/s00521-016-2532-0.
[8] Miao Sun, Xing He*, Tiancai Wang, Jie Tan, Dawen Xia, Circuit implementation of digitally programmable transconductance amplifier in analog simulation of reaction-diffusion neural model, Neurocomputing, 227, 74-81, 2017.