Download e-book for iPad: Advances in Neural Networks - ISNN 2006: Third International by Do-Hyeon Kim, Eui-Young Cha, Kwang-Baek Kim (auth.), Jun

By Do-Hyeon Kim, Eui-Young Cha, Kwang-Baek Kim (auth.), Jun Wang, Zhang Yi, Jacek M. Zurada, Bao-Liang Lu, Hujun Yin (eds.)

ISBN-10: 3540344373

ISBN-13: 9783540344377

This e-book and its sister volumes represent the lawsuits of the 3rd overseas Symposium on Neural Networks (ISNN 2006) held in Chengdu in southwestern China in the course of might 28–31, 2006. After a winning ISNN 2004 in Dalian and ISNN 2005 in Chongqing, ISNN turned a well-established sequence of meetings on neural computation within the area with becoming acceptance and enhancing caliber. ISNN 2006 acquired 2472 submissions from authors in forty three international locations and areas (mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, Malaysia, India, Pakistan, Iran, Qatar, Turkey, Greece, Romania, Lithuania, Slovakia, Poland, Finland, Norway, Sweden, Demark, Germany, France, Spain, Portugal, Belgium, Netherlands, united kingdom, eire, Canada, united states, Mexico, Cuba, Venezuela, Brazil, Chile, Australia, New Zealand, South Africa, Nigeria, and Tunisia) throughout six continents (Asia, Europe, North the USA, South the United States, Africa, and Oceania). in response to rigorous studies, 616 top quality papers have been chosen for ebook within the complaints with the popularity cost being lower than 25%. The papers are equipped in 27 cohesive sections masking all significant subject matters of neural community study and improvement. as well as the various contributed papers, ten uncommon students gave plenary speeches (Robert J. Marks II, Erkki Oja, Marios M. Polycarpou, Donald C. Wunsch II, Zongben Xu, and Bo Zhang) and tutorials (Walter J. Freeman, Derong Liu, Paul J. Werbos, and Jacek M. Zurada).

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Extra resources for Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part II

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14 – 19, 2006. © Springer-Verlag Berlin Heidelberg 2006 A Modified Constructive Fuzzy Neural Networks ∈ 15 ∈ the character. u U is identification of the objects, c C is special attribute of the objects. When U, normally having n types, is classified, an ideal classifier should has the property of the following: φ , yi∩yj= , (i,j=1,2,…,n i≠j yi≠φ) (1) ∪ ∪ ∪y =U y1 y2 … (2) n Eq. (1) shows the samples are classified correctly, eq. (2) shows every sample can be classified. However, in real problems, different objects have different characters, and furthermore the different aspect of an object has different characters.

We summarize the above presentation as the follows: f1 (x, w) > f2 (x, w) ∩ f1 (x, w) ≥ τ1u ∩ f2 (x, w) < −τ1L ∩ ∀x ∈ ω1 = S − x, (2) f2 (x, w) > f1 (x, w) ∩ f2 (x, w) ≥ τ2u ∩ f1 (x, w) < −τ2L ∩ ∀x ∈ ω2 = S − x. where f1 (x, w) > f2 (x, w) means that x can be recognized by RBF NN, f1 (x,w) ≥ τ1u ensures the output of NN corresponding to x is larger than the threshold τ1u , (S − x) means that in the next time of the training iteration we can remove the training pattern x out of training set S. In order to remove the recognized input patterns, a new error function (3) is proposed to train RBF NN classifier [max{0, τ1u − f1 (x, w)}2 + max{0, τ1L + f2 (x, w)}2 ] + E(w) = ∀x∈ω1 [max{0, τ2L + f1 (x, w)}2 + max{0, τ2u − f2 (x, w)}2 ].

The average time of detection and the model size of our system are also given in Table1. From Table1, we can see our system has achieved detection at two frames per second on mobile phone. The quick performance of our system is due to the efficiency of FloatBoost classifier and the hierarchical structure that allows the non-eyes of image areas to be quickly discarded while spending more computation on promising eye-like regions. Some real-life examples of eyes location are shown in Fig. 3. A Hierarchical FloatBoost and MLP Classifier 25 Fig.

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Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part II by Do-Hyeon Kim, Eui-Young Cha, Kwang-Baek Kim (auth.), Jun Wang, Zhang Yi, Jacek M. Zurada, Bao-Liang Lu, Hujun Yin (eds.)


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