LINSHAN WANG
CONTACTMath department, E-mail: wangls@ouc.edu.cn
INORMATIONProfessor, PhD supvisor,
Ocean University of China, Songling road Qingdao,
Shandong 266100 China.
RESEARCHResearch Dynamical system and its application in Neural network.
INTERESTS
EDUCATIONEPh.D. in Science,Sichuan University, Chengdu, Sichuan, China, 2002.
TEACHING
EXPERIENCEUndergraduate course: Advanced Mathematics; Calculus; Ordinary differential
equations; of Mathematics.
Graduate course: Dynamical system; Functional differential equations; Recurrent
neuralnetwork; Stochastic differential equations.
Post-graduate course: Stochastic signal processing; Genetic algorithm and
recurrentneural networks.
PUBLICATIONSLinshan Wang. Recurrent neural network with delays. Science Publication, 2008.
PAPERS:
[1] Linshan Wang and Daoyi Xu. Global exponential stability of Hopfeild reaction-diffusion
neural networks with time-varying delays. Science in China(Series),46(2003)6:466-
474(SCI IDS: 742CX ).
[2] Linshan Wang. Comments on 'Robust stability for interval neural networks with time
delay' by X.F.Liao. IEEE Trans. On Neural Networks, 13(2002)1:250-252(SCI IDS:
514LE).
[3] Linshan Wang and Daoyi Xu. Asymptotic behavior of a class of reaction-diffusion equa-
tions with delays. Journal of Mathematical Analysis and Applications, 281(2003)2:439-
453(SCI IDS: 691EF).
[4]Linshan Wang and Daoyi Xu. Global asymptotic stability of associative memory neural
networks with S-type distributed delays. International Journal of Systems Science,
33(2002)11:869-877(SCI IDS: 639KG).
[5] Linshan Wang and Daoyi Xu. Stability for Hopfeld neural networks with delay, Journal
of Vibration and Control, 8(2002)1:13-18(SCI IDS: 530PN).
[6]Linshan Wang and Daoyi Xu. Stability analysis of Hopfeld neural networks with delay,
Applied Mathematics and Mechanics, 23(2002)1:65-70(SCI IDS: 534QJ).
[7]Shengfan Zhou and Linshan Wang. Kernel sections for damped non-autonomous wave
equations with critical exponent. Discrete and Continuous Dynamical Systems. 9(2002)2:399-
412(SCI IDS: 640BF)
.
[8]Linshan Wang and Yuying Gao. On global robust stability for interval Hopfeld neural
networks with delay. Ann. of Diff. Eqs., 19(2003)3:421-426.
[9] LinshanWang and Yuying Gao. Global exponential robust stability of reaction-diffusion
interval neural networks with time-varying delays. Physics Letters A, 305(2006)5,
343-348(SCI IDS: 009FW).
[10]Min Wang and Linshan Wang. Global asymptotic robust stability of static neural net-
work models with S-type distributed delays, Mathematical and Computer Modelling
, 44(2006)2: 218-222 (SCI IDS: 055SX).
[11]LiaoWentong and LinshanWang. Existence and global attractability of almost periodic
solution for competitive neural networks with time-varying delays and different time
Scales. Advances in Neural Networks,2006, (SCI IDS: BEM20).
[12]Linshan Wang. Stochastic exponential stability of the delayed reaction-diffusion re-
current neural networks with Markovian jumping parameters. Physics Letters A,
356(2008)4,346-352(SCI IDS 297MW).
[13]Linshan Wang. Robust stability of Cellular neural networks with delay. IET. Control
Theory Appl., 18(2007)1, 56-63 (SCI IDS 156RS ).
[14]Linshan Wang, Ruojun Zhang and Yangfan Wang. Global exponential stability of
reaction-diffusion cellular neural networks with S-type distributed time delays. Non-
linear Analysis, RWA, 10(2009): 1101-1113(SCI IDS 390CK).
[15]Linshan Wang, Yan Zhang, Zhe Zhang, and Yangfan, Wang. LMI-based approach for
global expo9nential robust stability for reaction-dffusion uncertain neural networks
with time-varying delay. Chaos, Solitons and Fractals, 41(2009): 900-905(SCI IDS).
[16]Linshan Wang and Yangfan Wang. LMI-based approach of global exponential robust
stability for a class of uncertain distributed parameter control systems with time-
varying delays. Journal of Vibration and Control, 15(2009)8: 1173-1185(SCI IDS
475VN).
[17]Wenlin Li and Linshan Wang. Stability and bifurcation of a delayed three-level food
chain model with beddington-deangelis functional response. Nonlinear Analysis,
RWA, 10(2009): 2471-2477(SCI IDS 429HJ).
[18]Ruojun Zhang and Linshan Wang. Global exponential robust stability of interval cel-
lular neural networks with S-type distributed delays. Mathematical and Computer
Modelling, 50(2009)3: 380-385(SCI IDS 463YJ ).
[19]Linshan Wang and yangfan Wang. Global exponential stabilization for a class of dis-
tributed parameter systems with Markovian jumping parameters and time-varying
delay, Journal of Vibration and Control17(2011)6:873-880.
[20]Yangfan Wang, Chunge Lu, Guangrong Ji,,Linshan Wang. Global exponential stability
of high-order Hopfeld-type neural networks with S-ditributed time delays. Commun
Nonlinear Sci Numer Simulat, 16(2011)3319-3325.
[21]Yangfan Wang, Ping Lin, Linshan Wang. Exponential stability of reaction-diffusion
high-order Markovian jump Hopfeld neural networks with time-varying delays. Non-
linear Analysis, RWA,13(2012)1353-1361.
[22]Xiao Liang and Linshan Wang. Sliding mode control for Hopfeld neural networks with
time-delays and reaction-diffusion terms, Control Theory and Applications, 2012,
29(1):49-53(EI).
[23]Xiao Liang and Linshan Wang. Exponential stability for a class of stochastic reaction-
diffusion Hopfeld neural networks with delays. Journal of Applied Mathematics,
2012, Article ID 693163(SCI).
[24]Weiwei, Zhang and Linshan Wang.Robust stochastic stability analysis for uncertain
neutralS-type delays neural networks driven by Wiener process. Journal of Applied
Mathematics, 2012, Article ID 829594(SCI).
[25]Ruojun Zhang, Nan Ding, Linshan Wang. Mean Square Almost Periodic Solutions for Impulsive Stochastic Differential Equations with Delays. Journal of Applied Mathematics, Volume 2012：1-8, SCI.
[26]Linshan Wang, Jili Wang. Stability in Lagrange Sense for a Class of Stochastic Static Neural Networks with Mixed Time Delays. Ann. of Diff. Eqs, 2014， 30(2)：184-190.
[27]Chunge Lu, Linshan Wang. Robust Exponential Stability of Impulsive Stochastic Neural Networks with Leakage Time-Varying Delay. Abstract and Applied Analysis, Volume 2014: 1-8，SCI.
[28]Ruojun Zhang, Fuyun Lian, Linshan Wang. The Existence and Uniqueness of Positive Periodic Solutions for a Class of Nicholson-Type Systems with Impulses and Delays. Abstract and Applied Analysis, Volume 2013:1-10, SCI.
[29]Linshan Wang, Guiying Chen. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics, Volume 2014: 1-8 ，SCI .
[30]Chunge Lu, Linshan Wang. Exponential Stability of Stochastic MJSNNs with Partly Unknown Transition Probabilities. Volume 2013: 729-735，EI,SCI.
[31]Linshan Wang, Xiao Liang. Exponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays. Journal of Applied Mathematics, Volume 2012: 1-12，SCI.
[32]Ruojun Zhang，Tengda Wei. Advances in Positive periodic solution for Nicholson-type delay systems with impulsive effects. Journal of Difference Equations, 2015,(371):1-16，SCI.
[33]Xiao Liang，Linshan Wang, Yangfan Wang, Rili Wang. Dynamical Behavior of Delayed
Reaction–Diffusion Hopfield Neural Networks Driven by Infinite Dimensional Wiener Processes. IEEE Transactions on Neural Networks and Learning Systems, Volume 2016:，27（9）1816-1826, SCI.
[34]Linshan Wang, Quisen Ma, Exponential Stability of Stochastic Cohen-Grossberg-Tpye Ban Neural Networks with S-Type Distributed Delays, Communications in Applied Analysis, 2015, 19(2):343-352 Math SCI.
[35]Seng Wang, Linshan Wang，Tengdai Wei，Optimal Harvesting for a Stochastic Predator-prey Model with S-type Distributed Time Delays. Methodology and Computing Probability,24, 2016, Dol:1007/s 11009-9519-2, pp:1-32.SCI.
[36] Seng Wang , Linshan Wang，Tengda Wei，T，Well-Posedness and Aymptotic Behaviors for a Predator-Prey System with Levy Noise. Methodology and Computing Probability,24, 2016, Dol:1007/s 11009-016-9509-4, pp:1-11.SCI
[37] Seng Wang , Linshan Wang，Tengda Wei Optimal harvesting for a stochastic logistic model with S-type distributed time delay. Journal of Difference Equations and Applications, Doi:10.1080-10236198.2016.1269761, pp:1-15.SCI.
[38]Wang L S. Global well-posedness and stability of the mild solutions for a class of stochastic partial unctionaldifferential equations (in Chinese). Sci Sin Math, 2017, 47(3):371-382.
[39]Tengda Wei, Yangfan Wang, Linshan Wang, Existence, uniqueness and stability to stochastic reaction-diffusion Cohen-Grossbery neural networks with delays and Wiener processes, Neurocomputing.2017, 239:19-27.SCI.
[40]Tengda Wei, Linshan Wang, Ping Lin, Jialing Chen,Yangfan Wang,Haiyong Zheng, Learning Non Negativity Constrained Variation for Image Denoising and Deblurring,
Numer. Math. Theor. Meth. Appl. 2017, 10(4):.852-871: SCI.
[41] Tengda Wei, Qi Yao, Ping Lin, Linshan Wang, Adaptive synchronization of stochastic complex dynamical networks and its application, Neural Computing and Applications,2017, 1-16, https://doi.org/10.1007/s00521-018-3501-6. SCI.
[42] Tengda Wei · Sheng Wang · Linshan Wang, 2Permanence and extinction of stochastic competitive Lotka–Volterra system with Lévy noise, J. Appl. Math. Comput. 2018, 57: 667–683。SCI
[43] Tengda Wei, Yangfan Wang, Linshan Wang,5Robust Exponential Synchronization for Stochastic Delayed Neural Networks with Reaction–Diffusion Terms and Markovian Jumping Parameters,6Neural Process Lett. 2018, 48:979–994. SCI.
[44]TengdaWei , Ping Lin, Quanxin Zhu, LinshanWang and YangfanWang, ).,Dynamical Behavior of Nonautonomous Stochastic Reaction–Diffusion Neural-Network Models, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 30(5):1575-1580.SCI.
[45]lTengda Wei, Ping Lin, Yangfan Wang, Linshan Wang, Stability of stochastic impulsive reaction–diffusion neural networks with S-type distributed delays and its application to image encryption, Neural Networks,2019, 116: 35-45.SCI.
[46]lSheng Wang, Linshan Wang, Tengda Wei, A Note on a Competitive Lotka-Volterra Model with L´evy Noise, Filomat, 2017 31(12): 3741–3748.SCI.
[47]lShengWang, LinshanWang,·TengdaWei, Well-Posedness and Asymptotic Behaviors
for a Predator-Prey System with L´evy Noise, Methodol Comput Appl Probab, 2017, 19:715–725.SCI.
[48]lSheng Wang, Linshan Wang, Tengda Wei, Sucient and Necessary Conditions of Stochastic Permanence and Extinction for Stochastic Logistic Model with Markovian Switching
and L´evy Noise, Filomat, 2017 31(18): 5869–5883.SCI.
[49]Sheng Wang, Linshan Wang,Tengda Wei, Permanence and extinction of stochastic competitive Lotka–Volterra system with Lévy noise, J. Appl. Math. Comput., 2018, 57:667–683.SCI
[50]Sheng Wang, Linshan Wang, Tengda Wei, Optimal Harvesting for a Stochastic Predator-prey Model with S-type Distributed Time Delays, Methodol Comput Appl Probab, 2018, 20:37–68.SCI.
[51]Sheng Wang, Linshan Wang,Tengda Wei, Permanence and asymptotic behaviors of stochastic predator–prey system with Markovian switching and Lévy noise, Physica A, 2018, 495: 294-311. SCI.
[52]Sheng Wang, Guixin Hu, Linshan Wang,Tengda Wei, Stability in distribution of a stochastic predator–prey system with S-type distributed time delays,Physica A, 2018, 505: 919-930. SCI.
[53]Sheng Wang, Guixin Hu, Linshan Wang,Stability in Distribution of a Stochastic Competitive Lotka-Volterra System with S-type Distributed Time Delays, Methodol Comput Appl Probab, 2018, 20:1241–1257. SCI.
[54] Qi Yao , Linshan Wang, Existence–uniqueness and stability of reaction–diffusion stochastic Hopfield neural networks with S-type distributed time delays, Neurocomputing,2018, 275: 470–477 SCI.
[55] Qi Yao , Linshan Wang,Periodic solutions to stochasticreaction-diffusion neural networks withS-type distributed delays, IEEE Access, 2019, DOI10.1109/ACCESS.2019.2911962, SCI.
[56] Qi Yao , Linshan Wang,Periodic solutions to impulsive stochastic reaction-diffusion neural networks with delays,Communications in Nonlinear Science and Numerical Simulation, Volume 78, November2019,https://doi.org/10.1016/j.cnsns.2019.104865.SCI.
[57] M. Syed Ali , L. Palanisamy , J. Yogambigai ,Linshan Wang*(王林山), Passivity-based synchronization of Markovian jump complexdynamical networks with time-varying delays, parameteruncertainties, reaction–diffusion terms, and sampled-datacontrol, Journal of Computational and AppliedMathematics, 2019, https://doi.org/10.1016/j.cam.2018.10.047.SCI
GRANTS:
1. National Natural Science Foundation of China (No. 10771199), Global robust sta-
bility of undeterministic neural network with delays and reaction di®usion, 2008.1-
2011.12, sponsor.
2.National Natural Science Foundation of China (No.10171072), Attractor of lat-
tice dynamical system and nonlinear wave equation . 2002.1-2004.12. Joint with:
Sichuan University.
3. National Natural Science Foundation of China, Solution and small divisor of iter-
ative functional differential equations (No.10871117). 2009.1-2011.12. Joint with:
Shandong University.
4.National Natural Science Foundation of China (No11171347), Stochastic stability
and Stochastic attractor of delayed reaction-diffusion neural network with white
noise. 2012.1-2015.12, sponsor.
5.Key Natural Science Foundation of Shandong province (No:ZR2011AZ001),Nonlinear
analysis of stochastic reaction-diffusion neural network with delays. 2012.1-2014.12,sponsor.
6.National Natural Science Foundation of China (No11771014), Studyonwell-posednessandasympoticbehaviorforaclassofStochastic reaction-diffusion neural network with delays. 2018.1-2021.12, sponsor.
AWARDS: Top-notch professional and technical personnel of Qingdao, 2005
Prominent teacher of Ocean University of China, 2005.
Excellent teacher award sponsored by Communicate Bank of China , 2007.
QingYuanxunaward, 2015.
MEMBEROFTHEMember of AMS.
DOMESTICANDVice Chairman of differential equation association of Shandong province.
INTEMATIOMALiCommentator of AMS
SCIENTIFIC.MemberofIEEE
PROGRAM
COMMITTEE