[1]MENG Xi,QIAO Junfei,LI Wenjing.Construction of RBF neural networks via fast density clustering[J].CAAI Transactions on Intelligent Systems,2018,13(3):331-338.[doi:10.11992/tis.201702014]

Construction of RBF neural networks via fast density clustering

[1] CHEN Sheng, WOLFGANG A, HARRIS C J, et al. Symmetric RBF classifier for nonlinear detection in multiple-antenna-aided systems[J]. IEEE transactions on neural networks, 2008, 19(5):737-745.
[2] 乔俊飞, 韩红桂. RBF神经网络的结构动态优化设计[J]. 自动化学报, 2010, 36(6):865-872. QIAO Junfei, HAN Honggui. Optimal structure design for RBFNN structure[J]. Acta Automatica Sinica, 2010, 36(6):865-872.
[3] BARANDIARAN X, MORENO A. On the nature of neural information:a critique of the received view 50 years later[J]. Neurocomputing, 2008, 71(4/5/6):681-692.
[4] 侯远杭, 黄胜, 梁霄. PSO训练的弹性RBFNN在船型优化中的应用研究[J]. 哈尔滨工程大学学报, 2017, 38(2):175-180. HOU Yuanhang, HUANG Sheng, LIANG Xiao. Ship hull optimization based on PSO training FRBF neural network[J]. Journal of Harbin engineering university, 2017, 38(2):175-180.
[5] 蒙西, 乔俊飞, 韩红桂. 基于ART的RBF网络结构设计[J]. 控制与决策, 2014, 29(10):1876-1880. MENG Xi, QIAO Junfei, HAN Honggui. RBF neural network based on ART neural network[J]. Control and decision, 2014, 29(10):1876-1880.
[6] CECATI C, KOLBUSZ J, Ró?YCKI P, et al. A novel RBF training algorithm for short-term electric load forecasting and comparative studies[J]. IEEE transactions on industrial electronics, 2015, 62(10):6519-6529.
[7] 乔俊飞, 韩红桂. 神经网络结构动态优化设计的分析与展望[J]. 控制理论与应用, 2010, 27(3):350-357. QIAO Junfei, HAN Honggui. Dynamic optimization structure design for neural networks:review and perspective[J]. Control theory & applications, 2010, 27(3):350-357.
[8] TAGLIAFERRI R, STAIANO A, SCALA D. A supervised fuzzy clustering for radial basis function neural networks training[C]//Proceedings of the 9th IFSA World Congress and 20th NAFIPS International Conference. Vancouver, BC, Canada, 2001:1804-1809.
[9] RUBIO J J, PACHECO J. An stable online clustering fuzzy neural network for nonlinear system identification[J]. Neural computing and applications, 2009, 18(6):633-641.
[10] WANG Di, ZENG Xiaojun, KEANE J A. A clustering algorithm for radial basis function neural network initialization[J]. Neurocomputing, 2012, 77(1):144-155.
[11] PLATT J. A Resource-allocating network for function interpolation[J]. Neural computation, 1991, 3(2):213-225.
[12] LU Yingwei, SUNDARARAJAN N, SARATCHANDRAN P. A sequential learning scheme for function approximation using minimal radial basis function neural networks[J]. Neural computation, 1997, 9(2):461-478.
[13] HUANG Guangbin, SARATCHANDRAN P, SUNDARARAJAN N. An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks[J]. IEEE transactions on systems, man, and cybernetics, part B (Cybernetics), 2004, 34(6):2284-2292.
[14] HAN Honggui, CHEN Qili, QIAO Junfei. Research on an online self-organizing radial basis function neural network[J]. Neural computing and applications, 2010, 19(5):667-676.
[15] YU Hao, REINER P D, XIE Tiantian, et al. An incremental design of radial basis function networks[J]. IEEE transactions on neural networks and learning systems, 2014, 25(10):1793-1803.
[16] RODRIGUEZ A, LAIO A. Clustering by fast search and find of density peaks[J]. Science, 2014, 344(6191):1492-1496.
[17] HAGAN M T, MENHAJ M B. Training feedforward networks with the Marquardt algorithm[J]. IEEE transactions on neural networks, 1994, 5(6):989-993.
[18] WILAMOWSKI B M, YU Hao. Improved computation for Levenberg-Marquardt training[J]. IEEE transactions on neural networks, 2010, 21(6):930-937.
[19] WU Shiqian, ER M J, GAO Yang. A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks[J]. IEEE transactions on fuzzy systems, 2002, 9(4):578-594.
[20] MENG Xi, QIAO Junfei, HAN Honggui. An ART-like algorithm for constructing RBF neural networks[C]//Proceedings of 2015 International Joint Conference on Neural Networks. Killarney, Ireland, 2015.
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Last Update: 2018-06-25

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