By Xusheng Lei, Jianbo Su (auth.), Fu-Liang Yin, Jun Wang, Chengan Guo (eds.)
This booklet constitutes the court cases of the overseas Symposium on Neural N- works (ISNN 2004) held in Dalian, Liaoning, China duringAugust 19–21, 2004. ISNN 2004 bought over 800 submissions from authors in ?ve continents (Asia, Europe, North the US, South the USA, and Oceania), and 23 nations and areas (mainland China, Hong Kong, Taiwan, South Korea, Japan, Singapore, India, Iran, Israel, Turkey, Hungary, Poland, Germany, France, Belgium, Spain, united kingdom, united states, Canada, Mexico, - nezuela, Chile, andAustralia). in line with experiences, this system Committee chosen 329 high quality papers for presentation at ISNN 2004 and ebook within the lawsuits. The papers are prepared into many topical sections below eleven significant different types (theo- tical research; studying and optimization; help vector machines; blind resource sepa- tion,independentcomponentanalysis,andprincipalcomponentanalysis;clusteringand classi?cation; robotics and keep an eye on; telecommunications; sign, photo and time sequence processing; detection, diagnostics, and desktop protection; biomedical functions; and different functions) masking the entire spectrum of the new neural community examine and improvement. as well as the various contributed papers, ?ve special students have been invited to provide plenary speeches at ISNN 2004. ISNN 2004 was once an inaugural occasion. It introduced jointly a couple of hundred researchers, educators,scientists,andpractitionerstothebeautifulcoastalcityDalianinnortheastern China. It supplied a world discussion board for the contributors to give new effects, to debate the state-of-the-art, and to switch info on rising parts and destiny tendencies of neural community learn. It additionally created a pleasant chance for the individuals to fulfill colleagues and make neighbors who percentage related learn interests.
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Additional resources for Advances in Neural Networks - ISNN 2004: International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part II
971 Gang Chen, Bi-Cheng Li, Zhi-Gang Guo Neural Networks in Detection and Identification of Littoral Oil Pollution by Remote Sensing . . . . . . . . . . . . . . . . . . . . . 977 Bin Lin, Jubai An, Carl Brown, Hande Zhang Identifying Pronunciation-Translated Names from Chinese Texts Based on Support Vector Machines . . . . . . . . . . . . . . . . . . 983 Lishuang Li, Chunrong Chen, Degen Huang, Yuansheng Yang FPGA Implementation of Feature Extraction and Neural Network Classifier for Handwritten Digit Recognition .
Cn Abstract. In this paper, a method for trajectory generation in running is proposed with Radial Basis Function Neural Network, which can generate a series of joint trajectories to adjust humanoid robot step length and step time based on the sensor information. Compared with GA, RBFNN use less time to generate new trajectory to deal with sudden obstacles after thorough training. The performance of the proposed method is validated by simulation of a 28 DOF humanoid robot model with ADAMS.
Then a simulation example of 2-DOF robotic systems is given at last, from the simulation results, we can see the well performance of the designed observer and the estimation errors of the joint velocities are negligible. 1 Introduction Robotic manipulator systems are highly nonlinear, couples and time varying, which are subject to uncertainties unavoidably. The uncertainties consist of both structured uncertainties and unstructured uncertainties, which cannot be modeled precisely. For this reason, FNN technique has become a research hotspot in recent years [1,2].
Advances in Neural Networks - ISNN 2004: International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part II by Xusheng Lei, Jianbo Su (auth.), Fu-Liang Yin, Jun Wang, Chengan Guo (eds.)