基本信息

康艳梅 

 

主要经历 

 

 1997.09-2000.04  西安交大应用数学专业硕士研究生 

 

 2000.09-2004.08  西安交大工程力学专业博士研究生 

  

 2004.10-2006.11  西安交大数学流动站博士后 

  

 2006.12-2007.07  西安交大理学院讲师 

 

  2007.08-2014.12 西安交大数学与统计学院副教授

 

  2010.08-2011.07

 Visiting Research Scholar , Lab of Computational Biology, Warwick University, UK

 

 2016.08.13-2016-10.27

 Visiting Professor, Faculty of Science, The University of Sydney, AUS

 

2017.12-2018.2

 

Research fellow, Research centre of  Chaos and Complexity, City University of HongKong, HK SAR
 

 

  2014年12月至今 西安交大数学与统计学院教授

  

 

  研究方向：应用随机动力系统及机器学习

 

 欢迎报考硕士、博士研究生

 

  联系邮件：ymkang@mail.xjtu.edu.cn

 

 

站点计数器

我的新闻

研究领域

 教学经历

 

主讲课程：概率论与数理统计、生命科学模型及分析、数学建模能力提升课程、数学物理方程、数学建模、概率论

负责建设课程：随机微分方程 

曾辅导课程：工科数学分析基础(I)、线性代数与空间解析几何

 

 

研究方向  

 

1.  应用随机动力系统 (Applied Stochastic Dynamical Systems)

2.  反常扩散与分数阶模型 (Anomalous diffusion and its Fractional-order model)

3.  随机共振的理论及应用 (Theory and Application for Stochastic Resonance)

4.  复杂网络的临界动力学 (Critical Dynamics of Complex Networks)

5.  机器学习的概率统计方法 (Probalistic and Statistical Methods in Machine Learning)

 

 

科研项目：

   

1. 非线性随机振动系统的新型矩闭合方法及应用， 国家自然科学基金面上项目​  

     执行年限： 2022年1月-2025年12月

​​​​​​     

2. 神经元突触输入的非泊松过程建模及皮层网络的临界动力学，国家自然科学基金面上项目

     执行年限： 2018年1月-2021年12月

 

3.  具有分式结构的生化反应系统的随机响应方法及其在基因调控网络中的应用，国家自然科学基金面上项目

     执行年限： 2014年1月-2017年12月

 

4. 反常扩散系统的响应理论及噪声诱导的非线性现象，国家自然科学基金面上项目，     

     执行年限：2011年1月-2013年12月

 

5. 非线性复杂统中随机共振现象的半解析方法，国家自然科学基金青年项目，     

     执行年限：2007年1月-2009年12月

 

6. 随机共振的半解析方法和控制策略，中国博士后科学基金，     

     执行年限：2006年1月-2006年12月


 

获奖情况
 
 
2011-2012学年度，西安交通大学电气工程学院优秀授课教师（获奖）
 
2010年, 西安交通大学校级优秀毕设指导教师(获奖)
 
2007 西安交通大学优秀博士后（获奖）
 
2007年 全国百篇优秀博士学位论文（提名）
 
2006年 陕西省优秀博士学位论文（获奖）
 
2005年 西安交通大学唐照千奖学特等奖（获奖）
 
 
 学术兼职
   

   《国际应用数学进展》编委；

     《Annals of Applied Science》编委；

   《Mathematical Review》评论员；  

     中国工业与应用数学学会会员；

     中国力学学会会员

  
 

主要学术论文

[1] 徐子恒，何玉珠，康艳梅. 基于随机放电神经元网络的彩色图像感知研究. 物理学报  71(2022) 070501

[2] Yanmei Kang, Yuxuan Fu and Yaqian Chen. Signal-to-noise gain of an adaptive neuron model with Gamma renewal synaptic input. Acta Mechanica Sinica 38(2022) 521347

[3]  Muhammad Bilal Ghori, Yanmei Kang and Yaqian Chen. Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model. Journal of Computational Neuroscience 50(2022) 217-240

[4] Yuzhu He, Yuxuan Fu, Zijian Qiao, Yanmei Kang. Chaotic resonance in a fractional-order oscillator system with application to mechanical fault diagnosis. Chaos, Solitons and Fractals 142 (2021) 110536

[5] Kang Yanmei, Liu Ruonan, Mao Xuerong. Aperiodic stochastic resonance in neural processing with colored Gaussian noise. Cognitive Neurodynamics, Cognitive Neurodynamics (2021) 15:517–532

[6]Yamin Ding, Yuxuan Fu, and Yanmei Kang. Stochastic analysis of COVID-19 by a SEIR model with Lévy noise. Chaos 31, 043132 (2021)

[7] Fengyin Gao, Yanmei Kang. Positive role of fractional Gaussian noise in FitzHugh–Nagumo neuron model. Chaos, Solitons & Fractals Volume 146, May 2021, 110914

[8] Yuxuan Fu, Yanmei Kang and Ruonan Liu. Novel bearing fault diagnosis algorithm based on the method of moments for stochastic resonant systems. IEEE Transactions on Instrumentation & Measurement  Vol 70 Art 6500610, 2021 DOI: 10.1109//TIM.2020.3017857

[9] Kang Yanmei, Liu Ruonan. Moment dynamics for gene regulation with rational rate laws. Physical Review E 102, 042407,2020

[10] Yaqian Chen, Junsong Wang, Yanmei Kang, and Muhammad Bilal Ghori. Emergence of Beta Oscillations in a Resonance Model for Parkinson’s Disease. Neural Plasticity Vol 2020, Art ID 8824760, 15 page

[11] Ruonan Liu, Yanmei Kang. Stochastic master equation for early protein aggregation in the transthytin amyloid disease. Scientific Reports Vol. 10, Article number: 12437(2020)  https://doaj.org/article/fdada9857a73460eb14fb984d9f8549b 本文被PNAS 2022 Vol. 119 No. 4 e2109750119引用

[12] Yuxuan Fu, Yanmei Kang, Guanrong Chen. Stochastic resonance based visual perception using spiking neural networks. Frontier in Computational Neuroscience Vol 14, Art 24, 2020. DOI: 10.3399//fncom.2020.00024   本文入选 Frontier in Computational Neuroscience 2021 Editors' Pciks 

[13] Yanmei Kang, Yaqian Chen, Yuxuan Fu, Zuolei Wang, Guanrong Chen. Formation of Spiral Wave in Hodgkin-Huxley Neuron Networks with Gamma-distributed Synaptic Input, Communications in Nonlinear Science and Numerical Simulation, 83 (2020) 105112.
[14] Shuo Ma, Yanmei Kang. An averaging prociple for stochastic switched systems with Levy noise. Mathematical Methods in the Applied Sciences. June 2020, DoI: 10.1002/mma.6538
[15]  Ruonan Liu, Yanmei Kang, Yuxuan Fu, Guanrong Chen. Stochastic resonance and bifurcation of order parameter in a coupled system of underdamped Duffing oscillators. International Journal of Bifurcation and Chaos, 29 (2019) 1950108. 
[16] Liu GK, Kang YM, Quan HD et al. The detection performance of the dual-sequence-hopping signal via stochastic resonance processing under colored noise. Radioengineering 28(3): 618-625(2019)
[17] Ma Shuo, Kang Yanmei,Periodic averaging method for impulsive stochastic differential equations with Levy noise. Applied Mathematics Letters, 93, 91097(2019) 
[18] Shuo Ma, Yanmei Kang. Finite time synchronization of stochastic Markovian jumping genetic oscillator networks with time-varying delay and Levy noise. Advances in Difference Equations, 2019 (2019) 352. 
[19] 刘广凯, 全厚德, 康艳梅, 孙慧贤, 崔佩璋, 韩月明一种随机共振增强正弦信号的二次多项式接收方法. 物理学报. 2019, 68 (21): 210501
[20] Shuo Ma, Yanmei Kang. Exponential synchronization of memristor-based delayed neutral-type neural networks with Levy noise via impulsive control. European Physical Journal Special Topics, 228 (2019) 2157-2170. 
[21] Xi Chen, Xiujun Cheng, Yanmei Kang, Jinqiao Duan.Target search of a protein on DNA in the presence of position-dependent bias. Journal OF Statistical Mechanics 2019, 033501 (2019).
[22] Feng-Yin Gao, Yan-Mei Kang, Xi Chen, Guanrong Chen, Fractional Gaussian noise enhanced information capacity of a nonlinear neuron model with binary input, Physical Review E 97, 052142, Published may 29, 2018.  
[23] Ruo-Nan Liu, Yan-Mei Kang, Observing Stochastic Resonance in Periodic Potential Systems Driven by Alpha Stable Lévy Noise. Physics Letter A 382(25): 1656-1664, Published June 26, 2018.
[24] Yuxuan Fu, Yanmei Kang, Yong Xie. Subcritical Hopf Bifurcation and Stochastic Resonance of Electrical Activities in Neuron under Electromagnetic Induction. Front. Comput. Neurosci., 06 February 2018  https://doi.org/10.3389/fncom.2018.00006
[25] C Chen, C Li and Y Kang. Modelling the effects of cutting off infected branches and replanting on fire-blight transmission using Filippov systems. Journal of theoretical biology 439, 127-140(2018)
[26]  C Chen, Y Kang, R Simit? Sliding motion and global dynamics of a Filippov fire-blight model with economic thresholds. Nonlinear Analysis: Real World Applications 39, 492-519 (2018)
[27]  Shuo Ma, Yan-Mei Kang, Exponential Synchronization of Delayed Neutral-Type Neural Networks with Levy noise under Non-Lipschitz Condition.  Communications in Nonlinear Science and Numerical Simulation 57, 372-387(2018)
[28]  Xi Chen, Yan-Mei Kang, Switches in a genetic regulatory system under multiplicative non-Gaussian noise.  Journal of theoretical biology 435: 134-144 (2017)
[29]  Kang Y. M, Chen X. Lin X.D. Tan N. Mean First Passage Time and Stochastic Resonance in a Transcriptional Regulatory System with Non-Gaussian Noise.  Fluctuation & Noise Letters (2017) , 16 (01), art. no. 175007[17 pages]
[30] Chen C, Kang Y. M. Dynamics of a stochastic multi-strain SIS epidemic model driven by Lévy noise. Communications in Nonlinear Science and Numerical Simulation 2017, 42:379-395. DOI: 10.1016/j.cnsns.2016.06.012
[31] Chen X., Kang Y. M. Application of Gaussian moment method to a gene autoregulation model of rational vector field. Mod. Phys. Lett. B 30, 1650264 (2016) [10 pages]  
[32] Chen Z. Y., Kang Y. M. The first passage time density of Ornstein–Uhlenbeck process with continuous and impulsive excitations. Chaos, Solitons & Fractals 2016 91: 214-220 http://dx.doi.org/10.1016/j.chaos.2016.05.018
[33] Kang Y. M. Simulating Transient dynamics of the time-dependent time fractional Fokker-Planck systems. Phys. Lett. A 2016, 380: 3160-3166 DOI: 10.1016/j.physleta.2016.07.049
[34] Chen C, Kang Y. M. The asymptotic behaviour of a stochastic vaccination model with backward bifurcation. Applied Mathematical Modelling 2016, 40(11-12): 6051-6058
[35] Kang Y. M., Xie Y. , Lu J. C. Jiang J.  On the nonexistence of non-constant exact periodic solutions in a class of Caputo fractional-order dynamical systems. Nonlinear Dynamics 82(3), 259–1267 (2015) 
[36] Kang Y M, Jiang Y L and Xie Y. Linear response characteristics of time-dependent time fractional Fokker-Planck equation systems. J. Phys. A: Math. Theor.47,455055(2014) 
[37] Xie Y, Kang Y M, Liu Y, Wu Y. Firing properties and synchronization rate in fractional-order Hindmarsh-Rose model neurons.  Science China Technological  Science 57(5), 917(2014)
[38] Chen C, Kang Y M. Dynamics of a Stochastic SIS Epidemic Model with Saturated Incidence. Abstract and Applied Analysis, 2014, 723825(2014).
[39] Zhang Z R, Kang Y M et al. Stochastic resonance in a simple threshold sensor systems with alpha stable noise. Commun. Theor. Phys. 61, 578(2014)
[40] Shao Y G, Kang Y M. Effect of spatially correlated noise on stochastic synchronization in globally coupled FitzHugh-Nagumo neuron systems. Theor. & Appl. Mech. Lett.4, 013006(2014) 
[41] Kang Y M et al.  Effect of spatial correlation on stochastic resonance in two linearly interacting noisy bistable oscillators. J. Stat Mech. P10029(2012)
[42] Kang Y M, Wang M et al. Stochastic resonance in coupled weakly-damped bistable oscillators subjected to additive and multiplicative noise. Acta Mech. Sin. 28(2),05 (2012) 
[43] Durrant S, Kang Y. M., Stocks N. and Feng J. F. Suprathreshold stochastic resonance in neural processing tuned by correlation. Phys. Rev. E 84, 011923(2011) 
[44] Kang Y M.  Coherence resonance in subdiffusive fractional Klein-Kramers periodic potential systems without a bifurcation precusor. EPL(Europhys. Lett.) 94, 60005(2011)
[45] Kang Y M, Jiang J, Xie Y.  Observing fluctuating spectral density of subdiffusive overdampoed Brownian particles in periodic potentials. J. Phys. A: 44, 035002(2011)
[46]  张广丽，吕希路，康艳梅. Alpha稳定噪声环境下过阻尼系统中的参数诱导随机共振现象. 物理学报 2012(4), 1-8
[47]  徐超，康艳梅. 非高斯噪声激励下含周期信号FitzHugh-Nagumo系统的响应特征. 物理学报 2011(10),742-749
[48] Li Y. J., Kang Y. M. A study on stochastic resonance in biased subdiffusive Smoluchowski systems within linear response range. Commun. Theor. Phys. 54, 292(2010)
[49] Kang Y M, Jiang Y L.  Linear response charactersistics in time-dependent subdiffusive fractional Fokker-Planck equations. J. Math. Phys. 51, 023301(2010) 本文在被2010年Physical Review Letters 论文引用
[50] Kang Y M, Jiang Y L.  Spectral density of fluctuations in fractional bistable Klein-Kramers systems. Phys. Rev. E 81,021109(2010)
[51] Xie Y, Chen L, Kang Y M and Aihara K. Controling the onset of Hopf bifurcation in the Hodgkin_Huxley model. Phys. Rev. E 77(6), 061921(2008)
[52] Xie Y, Chen L, Kang Y M. Changes in types of neural excitability via bifurcation control. Phys. Rev. E 77(2), 021917(2008) 
[53] Kang Y M, Jiang Y L. A semi-analytic method for computing the long-time order parameter dynamics in mean-field coupled overdamped oscillators with colored noises. Phys. Lett. A 372(46),6826(2008) 
[54] Kang Y M, Jiang Y L.  Long-time dynamic response and stochastic resonance of subdiffusive overdamped bistable fractional Fokker-Planck systems. Chin. Phys.  Lett.  25(10), 3578(2008)
[55] Kang Y M, Xie Y, Xu J X. Observing nonlinear stochastic resonance with piecewise constant forces by the method of moments. Chaos Solitons & Fractals 27(3), 715(2006) 
[56] Kang Y M, Xu J X and Xie Y. Signal-to-noise ratio gain of a noisy neuron that transmits subthreshold periodic spike strains. Phys. Rev. E 72(2), 021902(2005)
[57] Kang Y M, Xu J X, Jin W Y. Aperiodic stochastic resonance and stochastic synchronization of uni-directionally coupled optical ssytems. Int. J. Nonlinear Science and Numerical Simulation 6,19(2005)
[58] 康艳梅; 徐健学; 谢勇. 双稳杜芬振子的随机共振及其动力学机制. 力学学报,  36 (2) : 247-253 （2004）
[59] Kang Y M, Xu J X  and Xie Y. Observing stochastic resonance in an underdapmed bistable Duffing oscillator by the method of moments. Phys. Rev. E 68(3), 036123(2003)  
[60] 康艳梅, 徐健学,谢勇. 单模光学系统的非线性弛豫速率和随机共振. 物理学报 52(11), 2712(2003)
[61] 康艳梅，徐健学，谢勇. 弱噪声极限下二维布朗运动的随机共振现象. 物理学报 52(4), 802(2003)
 
 Representative Oral Presentation

 

[1] Stochastic Resonance in Oscillatory and Neural Networks. International Symposium on Newest Development of Stochastic dynamical systems, October 26-28, 2018, Huaiyin Normal University, Huai’an, Jiangsu Province, China

[2]Some quantitative analytic results on stochastic gene regulatory systems. The 4th International Random Dynamical Systems.  June-23-27, 2017, Huazhong University of Science and Technology, Wuhan, China 

[3] The first passage time distribution of the noisy integrate-and-fire neuron with continous and discrete periodic input. The 5th International Conference on Cognitive Neurodynamics(ICCN 2015), June 3-7 2015,  Sanya, China 

[4] Application of Gaussian moment method  to a simple gene regulation model of rational vector field. The 2015 International Conference on Noise and Fluctuations(ICNF2015), June 2-6 2015, Xi'an, China

[5] Enhancement of weak signal detection in parallel arrays of integrate-and-fire neurons by negative spatial correlation in H. Liljenstrom(ed.), Advances in Cognitive Neurodynamics (IV), Springer Science and Business Media Dordrechet 2015

[6] Stochastic Resonance in Neural Systems. Workshop on Life Science Modelling and Computation, Shanghai Jiaotong University, Shanghai, 2013 Dec. 27-29