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Challenges in applications of compu⁃ tational intelligence in industrial electronics[C] / / Proceed⁃ ings of 2010 IEEE International Symposium on Industrial Electronics. Bari: IEEE, 2010: 15-22. [56]WILAMOWSKI B M, COTTON N J, KAYNAK O, et al. Computing gradient vector and jacobian matrix in arbitrarily connected neural networks [ J]. IEEE transactions on in⁃ dustrial electronics, 2008, 55(10): 3784-3790. [57] OAKDEN A. Cascade networks and extreme learning ma⁃ chines [ D]. Canberra: Australian National University, 2014. [58]LI Fanjun, QIAO Junfei, HAN Honggui, et al. A self⁃or⁃ ganizing cascade neural network with random weights for nonlinear system modeling [ J]. Applied soft computing, 2016, 42: 184-193. [59]JAEGER H, HAAS H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communica⁃ tion[J]. Science, 2004, 304(5667): 78-80. [60]SKOWRONSKI M D, HARRIS J G. Automatic speech rec⁃ ognition using a predictive echo state network classifier[J]. Neural networks, 2007, 20(3): 414-423. [61]XIA Yili, JELFS B, VAN HULLE M M, et al. An aug⁃ mented echo state network for nonlinear adaptive filtering of complex noncircular signals[J]. IEEE transactions on neu⁃ ral networks, 2011, 22(1): 74-83. [62]LUKOSEVICIUS M, JAEGER H. Reservoir computing ap⁃ proaches to recurrent neural network training[J]. Computer science review, 2009, 3(3): 127-149. [63]彭宇, 王建民, 彭喜元. 储备池计算概述[ J]. 电子学 报, 2011, 39(10): 2387-2396. PENG Yu, WANG Jianmin, PENG Xiyuan. Survey on res⁃ ervoir computing [ J]. Acta electronica sinica, 2011, 39 (10): 2387-2396. [64] QIAO Junfei, LI Fanjun, HAN Honggui, et al. Growing echo⁃state network with multiple subreservoirs [ J]. IEEE transactions on neural networks and learning systems, 2016, 99: 1-14. [65] DENG Zhidong, ZHANG Yi. Collective behavior of a small⁃world recurrent neural system with scale⁃free distri⁃ bution[J]. IEEE transactions on neural networks, 2007, ·766· 智 能 系 统 学 报 第 11 卷
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