Wenlian Lu-Institute of Science and Technology for Brain-inspired Intelligence

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Research

Wenlian Lu
Research Direction：Applied mathematics, Signal processing, computer science
Email：wenlian@fudan.edu.cn
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Brief Introduction：Dr. Wenlian Lu is a professor in the Department of Mathematics, School of Mathematical Sciences, Fudan University. Dr. Lu has excellent work foundations in neural network dynamic behavior analysis, machine learning and statistics. In particular, the spatiotemporal model of the neural Gaussian random field is established, and the neural network model and experimental observation data are calculated by data assimilation fitting. He also join one of the earliest teams in the world to study the behavior of recurrent neural networks with discontinuous excitation functions has perfected the use of The theoretical basis of the discontinuous excitation function neural network for optimization calculation, a class of neural network system with discontinuous right end is designed, which can solve the combinatorial optimization problem of non-smooth cost function more accurately. Dr. Lu is elected as IEEE Senior Member; Selected as New Century Talents by Ministry of Education in 2013; Awarded as one of the 100 National Excellent Doctoral Dissertations.
Achievement：

1. Centralized and decentralized global outer-synchronization of asymmetric recurrent time-varying neural network by data-sampling.Lu W, Zheng R, Chen T. Neural Networks (2016).

2. A statistical approach for detecting common features.Gan X, Xu B ,Ji X,Lu W, Waxman D, Feng J.Journal of Neuroscience Methods (2015).

3. Achieving cluster consensus in continuous-time networks of multi-agents with inter-cluster non-identical inputs.Han Y,Lu W,Chen T.IEEE Transactions on Automatic Control (2015).

4. Consensus analysis of networks with time-varying topology and event-triggered diffusions.Han Y,Lu W, Chen T.Neural Networks (2015).

5. Consensus in continuous-time multiagent systems under discontinuous nonlinear protocols.Liu B,Lu W, Chen T.IEEE Transactions on Neural Networks and Learning Systems (2015).

6. Pinning networks of coupled dynamical systems with Markovian switching couplings and event-triggered diffusions.Lu W, Han Y, Chen T.Journal of the Franklin Institute (2015).

Next:Chunhe LI