C.l. Philip Chen - Publications#

He is one of the foremost researchers and leaders in cybernetics and systems areas. His research results have been highly cited and inspired others, and set the directions for peers. Within his first-rated 200 more published research journal papers, 32 are top 1% highly cited papers in Web of Science. He is listed in top 14th author in having the most highly cited papers in computer science area in the world by Web of Science. He has H-index of 51 and has more than 15,300 citations in Google Scholar; and he has H-index of 40 and more than 6100 of citations in Web of Science, Clarivate Analytics.

1. C. L. Philip Chen, Yan-Jun Liu, and GX Wen, “Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Stochastic Systems,” IEEE Trans. On Cybernetics, Vol. 44, No. 5, pp. 583-593, May 2014; 230 Google citations.

2. C. L. Philip Chen, G. X. Wen, Y. J. Liu, and F.Y. Wang, “Adaptive Consensus Control for a Class of Nonlinear Multi-Agent Time-delay Systems using Neural Networks,” IEEE Trans. On Neural Networks and Learning Systems, Vol. 25, No. 6, pp. 1217-1226, June 2014; 220 Google citations.

3. C. L. Philip Chen, G.X. Wen, Y. J. Liu, and Z. Liu, “Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multi-Agent Systems,” IEEE Trans. on Cybernetics, Vol. 46, Issue 7, pp. 1591-1601, July 2016; 158 Google citations.

4 . C. L. Philip Chen, Chang-E Ren, Tao Du, “Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Mult-Agent Systems with Heterogeneous Nonlinear Dynamics,” IEEE Transactions on Fuzzy Systems, Volume: 24, Issue: 4, Pages: 906-915, Aug, 2016; 72 Google citations.

5. Daniel Viegas, Pedro Batista, Paulo Oliveira, Carlos Silvestre, and C. L. P. Chen, “Distributed State Estimation for Linear Multi-Agent Systems with Time-Varying Measurement Topology,” Automatica, Volume: 54 pp. 72-79, April, 2015; 19 Google citations.

6. C. L. Philip Chen and Zhulin Liu, "Broad learning system: An effective and efficient incremental learning system without the need for deep architecture", IEEE Transactions on Neural Networks and Learning Systems, Vol. 29, No.1, pp. 10-24, Jan, 2018; 32 Google citations.

7. L. Chen, C. L. Philip Chen, and M. Lu, “A Multiple-Kernel Fuzzy C-means Algorithm for Image Segmentation,” IEEE Trans. on Systems, Man, and Cybernetics, Part B, Vol. 41, No. 5, 2011, pp. 1263-1274; 186 Google citations.

8. C. L. Philip Chen, Hong Li, Yantao Wei, et. al, “A Local Contrast Method for Small Infrared Target Detection,” IEEE Trans. on Geoscience and Remote Sensing, Vol. 52, No. 1, pp. 574-581, Jan. 2014; 155 Google citations.

9. C. L. Philip Chen, C.Y. Zhang, L. Chen, and Min Gan, “Fuzzy Restricted Boltzmann Machine for the Enhancement of Deep Learning,” IEEE Trans. Fuzzy Systems, Vol. 23, No.6, pp.2163-2173, Dec. 2015. 64 Google citations.

10. C. L. Philip Chen and C. Y. Zhang, “Data-Intensive Applications, Challenges, Techniques and Technologies: A Survey on Big Data,” Information Sciences, Vol. 275, pp. 314–347, August 2014; 1399 Google citations.

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