By Xusheng Lei, Jianbo Su (auth.), Fu-Liang Yin, Jun Wang, Chengan Guo (eds.)
This publication constitutes the lawsuits of the foreign Symposium on Neural N- works (ISNN 2004) held in Dalian, Liaoning, China duringAugust 19–21, 2004. ISNN 2004 acquired over 800 submissions from authors in ?ve continents (Asia, Europe, North the United States, South the US, 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 keeping with reports, this system Committee chosen 329 top of the range papers for presentation at ISNN 2004 and ebook within the lawsuits. The papers are prepared into many topical sections lower than 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 an eye on; telecommunications; sign, snapshot and time sequence processing; detection, diagnostics, and laptop protection; biomedical purposes; and different purposes) protecting the full spectrum of the hot neural community learn 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 global discussion board for the members to offer new effects, to debate the cutting-edge, and to switch info on rising parts and destiny developments of neural community examine. It additionally created a pleasant chance for the individuals to fulfill colleagues and make buddies who proportion related examine 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
Robot Manipulator Controller Based on Fuzzy Neural and CMAC Network. Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi An, China (2003) 525–529 3. : Backstepping Passivity Adaptive Position Control for Robotic Manipulators. Proceeding of the American Control Conference. Anchorage AK (2002) 4607–4611 4. : Neural-Fuzzy Control System for Robotic Manipulators. R. R. China Abstract. This paper proposes a novel self-learning PD (ProportionalDerivative) control method for mobile robot path-tracking problems.
Full-DOF Calibration-Free Robotic Hand-Eye Coordination 9 Nonlinear Mapping y Motion Planning in Image Space Robot Controller Image Plane l2 l1 l3 Camera Hand θ Working (x,y) (x,y) space Object x O Fig. 1. 3 Fig. 2. Feature deﬁnitions for a triangular object Visual Mapping Model When the object feature vector is deﬁned, its position and dynamics can be extracted by image processing. Suppose at the k-th visual sampling instant, feature position, velocity and acceleration vectors in image plane are f , f˙ and f¨, respectively, we have: (1) f˙(k) = f˙o (k) + f˙c (k), ˙ where fo is the feature motion in the image plane caused by the object motion, and f˙c is the feature motion caused by the camera motion.
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.