李若霞
硕士生导师
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基本信息
教师英文名称:Ruoxia Li
所在单位:数学与统计学院
学历:博士研究生
办公地点:文津楼三段3201
性别:女
联系方式:ruoxiali1227@163.com
学位:理学博士学位
职称:助理研究员(自然科学)
在职信息:在职
毕业院校:东南大学
学科:运筹学与控制论
应用数学
应用数学
联系信息
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邮箱:
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论文成果
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李若霞,高兴宝,曹进德,张凯,Exponential Stabilization Control of Delayed Quaternion-Valued Memristive Neural Networks: Vector Ordering Approach:Circuits, Systems, and Signal Processing,2020.3.1,39(3):1353-1371
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李若霞,高兴宝,曹进德,Quasi-state estimation and quasi-synchronization control of quaternion-valued fractional-order fuzzy memristive neural networks: Vector ordering approach:APPLIED MATHEMATICS AND COMPUTATION,2019.12.1,362(0):124572
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李若霞,高兴宝,曹进德,张凯,Dissipativity and exponential state estimation for quaternion-valued memristive neural networks:NEUROCOMPUTING,2019.9.21,363(21):236-245
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李若霞,高兴宝,曹进德,Exponential State Estimation for Stochastically Disturbed Discrete-Time Memristive Neural Networks: Multiobjective Approach:IEEE Transactions on Neural Networks and Learning Systems,2019.8.28,0:DOI:10.1109/TNNLS.2019.2938774
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李若霞,高兴宝,曹进德,Exponential Synchronization of Stochastic Memristive Neural Networks with Time-Varying Delays:NEURAL PROCESSING LETTERS,2019.8.1,50(1):459-475
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李若霞,高兴宝,曹进德,张凯,Stability analysis of quaternion-valued Cohen-Grossberg neural networks:Mathematical Methods in the Applied Sciences,2019.7.15,42(10):3721-3738
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曹进德,李若霞,黄伟,魏运,郭建华,Traffic network equilibrium problems with demands uncertainty and capacity constraints of arcs by scalarization approaches:Science China Technological Sciences,2018.10.7,61(11):1642-1653
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李若霞,高兴宝,曹进德,Non-fragile state estimation for delayed fractional-order memristive neural networks:Applied Mathematics and Computation,2018.9.10,340(340):221-233
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李若霞,曹进德,Finite-time and fixed-time stabilization control of delayed memristive neural networks: Robust Analysis Technique:Neural Processing Letters,2018.6.1,47(3):1077-1096
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李若霞,曹进德,Finite-time stability analysis for Markovian jump memristive neural networks with partly unknown transition probabilities:IEEE Transactions on Neural Networks and Learning Systems,2017.12.1,28(12):2924-2935
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