Get Advances in Neural Networks - ISNN 2004: International PDF

By Xusheng Lei, Jianbo Su (auth.), Fu-Liang Yin, Jun Wang, Chengan Guo (eds.)

ISBN-10: 3540228438

ISBN-13: 9783540228431

This publication 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 obtained over 800 submissions from authors in ?ve continents (Asia, Europe, North the USA, South the US, and Oceania), and 23 international locations 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). according to stories, this system Committee chosen 329 fine quality papers for presentation at ISNN 2004 and booklet within the complaints. The papers are equipped into many topical sections below eleven significant different types (theo- tical research; studying and optimization; aid vector machines; blind resource sepa- tion,independentcomponentanalysis,andprincipalcomponentanalysis;clusteringand classi?cation; robotics and keep watch over; telecommunications; sign, snapshot and time sequence processing; detection, diagnostics, and laptop defense; biomedical functions; and different purposes) overlaying the complete spectrum of the hot neural community learn and improvement. as well as the varied contributed papers, ?ve distinctive students have been invited to offer 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 provide new effects, to debate the state-of-the-art, and to interchange details on rising parts and destiny developments of neural community study. It additionally created a pleasant chance for the contributors to fulfill colleagues and make buddies who proportion comparable learn interests.

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A new singular perturbation model is used to realize the vibration suppression control and NF position/force control with an ANFIS model [6], and the proposed control algorithm is verified by an example. * This work was jointly supported by the National Excellent Doctoral Dissertation Foundation (Grant No: 200041), the National Science Foundation for Key Technical Research of China (Grant No: 90205008), the National Key Project for Basic Research of China (Grant No: G2002cb312205), the National 863 Project of China (Grant No: 2003AA742016) and Basic Research Foundation of Tsinghua University (Grant No: JC2003028).

1 System Model of Full-DOF Visual Tracking Problem Description For the full-DOF tracking problem, the robot hand should execute translation and rotation movements at the same time. 1. The camera is fixed in the robot hand. Relations between the robot (hand) and the camera are unknown. An object is moving in the working space freely (including translations and rotations). The tracking task is finished when the robot hand catches the object or is kept a constant relative pose with respect to the object.

A stability proof for the space robot with control law and projection-learning algorithm will be direct. Here the theorem and proof are omitted for paper length. 1 Task Design The parameters of the space robot with flexible dual arms are shown in Table 1, and EI3=EI5=300Nm, α = π / 4 . Table 1. Space robot parameters Weight(kg) Length(m) Link 1 40 2 Link 2 2 2 Link 3 2 2 Link 4 2 2 Link 5 2 2 Fig. 2. Tip position of link 3 1 - ye3 2 - xe3 Fig. 3. Tip position of link 5 1 - ye5 2 - xe5 Fig. 4. Internal force at end of link 3 1 - fIey3 2 - fIex3 Fig.

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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.)

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