By Xusheng Lei, Jianbo Su (auth.), Fu-Liang Yin, Jun Wang, Chengan Guo (eds.)
This publication constitutes the complaints 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 United States, South the United States, 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 studies, this system Committee chosen 329 high quality papers for presentation at ISNN 2004 and booklet within the lawsuits. The papers are equipped 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 watch over; telecommunications; sign, photo and time sequence processing; detection, diagnostics, and computing device defense; biomedical purposes; and different functions) masking the full spectrum of the new neural community learn and improvement. as well as the various contributed papers, ?ve exotic 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 members to provide new effects, to debate the cutting-edge, and to replace info on rising components and destiny developments of neural community examine. It additionally created a pleasant chance for the members to satisfy colleagues and make acquaintances who percentage related learn interests.
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Extra resources for Advances in Neural Networks - ISNN 2004: International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part II
Thus the physical features of the object in image plane must be utilized in addition to its position coordinates in image plane, which implies the object model should be known a prior. Suppose the object is of a triangular shape, the object feature vector in image plane is deﬁned as: f = [x, y, θ, l1 , r21 , r31 ] , where (x, y) are the coordinates of a corner point of the object in image plane, θ is the angle of one edge rotating counterclockwise from the x axis. The lengths of the three edges are respectively l1 , l2 , l3 , and r21 = l2 /l1 ,r31 = l3 /l1 .
983 Lishuang Li, Chunrong Chen, Degen Huang, Yuansheng Yang FPGA Implementation of Feature Extraction and Neural Network Classifier for Handwritten Digit Recognition . . . . . . . . . . . . . . . 988 Dongsheng Shen, Lianwen Jin, Xiaobin Ma Replicator Neural Networks for Outlier Modeling in Segmental Speech Recognition . . . . . . . . . . . . . . . . . . . 996 L´aszl´o T´oth, G´abor Gosztolya A Novel Approach to Stellar Recognition by Combining EKF and RBF Net .
Yin, J. Wang, and C. ): ISNN 2004, LNCS 3174, pp. 25–34, 2004. © Springer-Verlag Berlin Heidelberg 2004 26 X. Xu, X. Wang, and D. Hu mobile robots so that explicit and exact modeling of robot dynamics is required. Intelligent control methods for mobile robots have attracted lots of research interests in recent years since intelligent controllers do not need explicit and exact model of robot dynamics and machine learning algorithms can be used to realize adaptivity to uncertainties. However, most existing intelligent controllers for mobile robots either require human knowledge for constructing control rules or collecting labeled samples for supervised learning .
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.)