The two volume set LNCS 3173/3174 constitutes the refereed proceedings of the International Symposium on Neural Networks, ISNN 2004, held in Dalian, China in August 2004. The 329 papers presented were carefully reviewed and selected from more than 800 submissions. The papers span the entire scope...
Advances in Neural Networks – ISNN 2024 Editors and Affiliations Shanghai Jiao Tong University, Shanghai, China Xinyi Le South China University of Technology, Guangzhou, China Zhijun Zhang Bibliographic Information Book TitleAdvances in Neural Networks – ISNN 2024 ...
The present Special Issue "Advances in Neural Networks Research: IJCNN2009" provides a state-of-art overview of the field of neural networks. It includes 39 papers from selected areas of the 2009 International Joint Conference on Neural Networks (IJCNN2009). IJCNN2009 took place on June 14-19...
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In this study, we propose an approach based on BP neural network to kinematic control the hyper-redundant snake-like manipulator. This approach, inspired by the Serpenoid curve and the concertina motion principle of the nature snake, is completely capable of solving the control problem of a...
This paper reports the results of the NN3 competition, which is a replication of the M3 competition with an extension of the competition towards neural network (NN) and computational intelligence (CI) methods, in order to assess what progress has been made in the 10 years since the M3 compet...
【预订】Advances in Neural Networks - Isnn 2015: 12th International Symposium on Neural Networks, Isnn 2015, Jeju, South Korea, October 15-18, 2015, Proceedin 预订商品,按需印刷,需要1-3个月发货,非质量问题不接受退换货。 进口好书抢先订,点击前往! 出版社:Adis 手机专享价 ¥ 当当价 降价...
Advances in Neural Networks – ISNN 2011 Advances in Neural Networks – ISNN 2011 Editors and Affiliations Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, Beijing, China Derong Liu College of Information Sci...
第二代是20世纪80年代中期出现的基于连接主义的深度神经网络(DNN)[Rumelhart et al., 1986],自2006年以来在过去的十几年里一直引领着AI的发展[Hinton et al., 2006]。然而,主要通过发放率传输信息的DNN在生物学上是不精确的,并且在神经元内缺乏动态机制。SNN被认为是第三代ANN,因为它们具有丰富的时空神经动力...