Lecture Notes in Computer Science
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Lecture Notes in Computer Science 4984
Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison
Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany Masumi Ishikawa Kenji Doya Hiroyuki Miyamoto Takeshi Yamakawa (Eds.) Neural Information Processing 14th International Conference, ICONIP 2007 Kitakyushu, Japan, November 13-16, 2007 Revised Selected Papers, Part I 1 3
Volume Editors Masumi Ishikawa Hiroyuki Miyamoto Takeshi Yamakawa Kyushu Institute of Technology Department of Brain Science and Engineering 2-4 Hibikino, Wakamatsu, Kitakyushu 808-0196, Japan E-mail: {ishikawa, miyamo, yamakawa}@brain.kyutech.ac.jp Kenji Doya Okinawa Institute of Science and Technology Initial Research Project 12-22 Suzaki, Uruma, Okinawa 904-2234, Japan E-mail: doya@oist.jp Library of Congress Control Number: Applied for CR Subject Classification (1998): F.1, I.2, I.5, I.4, G.3, J.3, C.2.1, C.1.3, C.3 LNCS Sublibrary: SL 1 – Theoretical Computer Science and General Issues ISSN 0302-9743 ISBN-10 3-540-69154-5 Springer Berlin Heidelberg New York ISBN-13 978-3-540-69154-9 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com © Springer-Verlag Berlin Heidelberg 2008 Printed in Germany Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper SPIN: 12282845 06/3180
5 4 3 2 1 0 Preface These two-volume books comprise the post-conference proceedings of the 14th International Conference on Neural Information Processing (ICONIP 2007) held in Kitakyushu, Japan, during November 13–16, 2007. The Asia Pacific Neural Network Assembly (APNNA) was founded in 1993. The first ICONIP was held in 1994 in Seoul, Korea, sponsored by APNNA in collaboration with regional organizations. Since then, ICONIP has consistently provided prestigious oppor- tunities for presenting and exchanging ideas on neural networks and related fields. Research fields covered by ICONIP have now expanded to include such fields as bioinformatics, brain machine interfaces, robotics, and computational intelligence. We had 288 ordinary paper submissions and 3 special organized session pro- posals. Although the quality of submitted papers on the average was exception- ally high, only 60% of them were accepted after rigorous reviews, each paper being reviewed by three reviewers. Concerning special organized session propos- als, two out of three were accepted. In addition to ordinary submitted papers, we invited 15 special organized sessions organized by leading researchers in emerging fields to promote future expansion of neural information processing. ICONIP 2007 was held at the newly established Kitakyushu Science and Research Park in Kitakyushu, Japan. Its theme was “Towards an Integrated Approach to the Brain—Brain-Inspired Engineering and Brain Science,” which emphasizes the need for cross-disciplinary approaches for understanding brain functions and utilizing the knowledge for contributions to the society. It was jointly sponsored by APNNA, Japanese Neural Network Society (JNNS), and the 21st century COE program at Kyushu Institute of Technology. ICONIP 2007 was composed of 1 keynote speech, 5 plenary talks, 4 tutorials, 41 oral sessions, 3 poster sessions, 4 demonstrations, and social events such as the Banquet and International Music Festival. In all, 382 researchers registered, and 355 participants joined the conference from 29 countries. In each tutorial, we had about 60 participants on the average. Five best paper awards and five student best paper awards were granted to encourage outstanding researchers. To minimize the number of researchers who cannot present their excellent work at the conference due to financial problems, we provided travel and accommodation support of up to JPY 150,000 to six researchers and of up to JPY to eight students 100,000. ICONIP 2007 was jointly held with the 4th BrainIT 2007 organized by the 21st century COE program, “World of Brain Computing Interwoven out of An- imals and Robots,” with the support of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS). VI Preface
We would like to thank Mitsuo Kawato for his superb Keynote Speech, and Rajesh P.N. Rao, Fr´ ed´ eric Kaplan, Shin Ishii, Andrew Y. Ng, and Yoshiyuki Kabashima for their stimulating plenary talks. We would also like to thank Sven Buchholz, Eckhard Hitzer, Kanta Tachibana, Jung Wang, Nikhil R. Pal, and Tetsuo Furukawa for their enlightening tutorial lectures. We would like to express our deepest appreciation to all the participants for making the conference really attractive and fruitful through lively discussions, which we believe would tremendously contribute to the future development of neural information processing. We also wish to acknowledge the contributions by all the Committee members for their devoted work, especially Katsumi Tateno for his dedication as Secretary. Last but not least, we want to give special thanks to Irwin King and his students, Kam Tong Chan and Yi Ling Wong, for providing the submission and reviewing system, Etsuko Futagoishi for hard secretarial work, Satoshi Sonoh and Shunsuke Sakaguchi for maintaining our conference server, and many secretaries and graduate students at our department for their diligent work in running the conference. January 2008 Masumi Ishikawa Kenji Doya Hiroyuki Miyamoto Takeshi Yamakawa
Organization Conference Committee Chairs General Chair Takeshi Yamakawa (Kyushu Institute of Technology, Japan) Organizing Committee Chair Shiro Usui (RIKEN, Japan) Steering Committee Chair Takeshi Yamakawa (Kyushu Institute of Technology, Japan) Program Co-chairs Masumi Ishikawa (Kyushu Institute of Technology, Japan), Kenji Doya (OIST, Japan) Tutorials Chair Hirokazu Yokoi (Kyushu Institute of Technology, Japan) Exhibitions Chair Masahiro Nagamatsu (Kyushu Institute of Technology, Japan) Publications Chair Hiroyuki Miyamoto (Kyushu Institute of Technology, Japan) Publicity Chair Hideki Nakagawa (Kyushu Institute of Technology, Japan) Local Arrangements Chair Satoru Ishizuka (Kyushu Institute of Technology, Japan) Web Master Tsutomu Miki (Kyushu Institute of Technology, Japan)
Secretary Katsumi Tateno (Kyushu Institute of Technology, Japan) Steering Committee Takeshi Yamakawa, Masumi Ishikawa, Hi- rokazu Yokoi, Masahiro Nagamatsu, Hiroyuki Miyamoto, Hideki Nakagawa, Satoru Ishizuka, Tsutomu Miki, Katsumi Tateno Program Committee Masumi Ishikawa, Kenji Doya Track Co-chairs Track 1: Masato Okada (Tokyo Univ.), Yoko Yamaguchi (RIKEN), Si Wu (Sussex Univ.) Track 2: Koji Kurata (Univ. of Ryukyus), Kazushi Ikeda (Kyoto Univ.), Liqing Zhang (Shanghai Jiaotong Univ.) VIII Organization Track 3: Yuzo Hirai (Tsukuba Univ.), Yasuharu Koike (Tokyo Institute of Tech.), J.H. Kim (Handong Global Univ., Korea) Track 4: Akira Iwata (Nagoya Institute of Tech.), Noboru Ohnishi (Nagoya Univ.), Se- Young Oh (Postech, Korea) Track 5: Hideki Asoh (AIST), Shin Ishii (Kyoto Univ.), Sung-Bae Cho (Yonsei Univ., Korea) Advisory Board Shun-ichi Amari (Japan), Sung-Yang Bang (Korea), You-Shou Wu (China), Lei Xu (Hong Kong), Nikola Kasabov (New Zealand), Kunihiko Fukushima (Japan), Tom D. Gedeon (Australia), Soo-Young Lee (Korea), Yixin Zhong (China), Lipo Wang (Singapore), Nikhil R. Pal (India), Chin-Teng Lin (Taiwan), Lai- wan Chan (Hong Kong), Jun Wang (Hong Kong), Shuji Yoshizawa (Japan), Minoru Tsukada (Japan), Takashi Nagano (Japan), Shozo Yasui (Japan) Referees
S. Akaho P. Andras T. Aonishi T. Aoyagi T. Asai H. Asoh
J. Babic R. Surampudi Bapi A. Kardec Barros J. Cao
H. Cateau J-Y. Chang S-B. Cho S. Choi
I.F. Chung A.S. Cichocki M. Diesmann K. Doya
P. Erdi H. Fujii
N. Fukumura W-k. Fung T. Furuhashi A. Garcez T.D. Gedeon S. Gruen
K. Hagiwara M. Hagiwara K. Hamaguchi R.P. Hasegawa H. Hikawa Y. Hirai
K. Horio K. Ikeda
F. Ishida S. Ishii
M. Ishikawa A. Iwata
K. Iwata H. Kadone Y. Kamitani N. Kasabov M. Kawamoto C. Kim
E. Kim K-J. Kim
S. Kimura A. Koenig Y. Koike T. Kondo
S. Koyama J.L. Krichmar H. Kudo T. Kurita S. Kurogi M. Lee
J. Liu B-L. Lu
N. Masuda N. Matsumoto B. McKay K. Meier
H. Miyamoto Y. Miyawaki H. Mochiyama C. Molter T. Morie K. Morita M. Morita Y. Morita N. Murata H. Nakahara Y. Nakamura S. Nakauchi K. Nakayama
Organization IX K. Niki J. Nishii I. Nishikawa S. Oba T. Ogata
S-Y. Oh N. Ohnishi M. Okada H. Okamoto T. Omori T. Omori
R. Osu N. R. Pal P. S. Pang G-T. Park J. Peters S. Phillips Y. Sakaguchi K. Sakai
Y. Sakai Y. Sakumura K. Samejima M. Sato
N. Sato R. Setiono T. Shibata H. Shouno M. Small M. Sugiyama I. Hong Suh J. Suzuki T. Takenouchi Y. Tanaka I. Tetsunari N. Ueda
S. Usui Y. Wada
H. Wagatsuma L. Wang
K. Watanabe J. Wu
Q. Xiao Y. Yamaguchi K. Yamauchi Z. Yi
J. Yoshimoto B.M. Yu
B-T. Zhang L. Zhang
L. Zhang Sponsoring Institutions Asia Pacific Neural Network Assembly (APNNA) Japanese Neural Network Society (JNNS) 21st Century COE Program, Kyushu Institute of Technology Cosponsors RIKEN Brain Science Institute Advanced Telecommunications Research Institute International (ATR) Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT) IEEE CIS Japan Chapter Fuzzy Logic Systems Institute (FLSI)
Table of Contents – Part I Computational Neuroscience A Retinal Circuit Model Accounting for Functions of Amacrine Cells . . .
1 Murat Saglam, Yuki Hayashida, and Nobuki Murayama Global Bifurcation Analysis of a Pyramidal Cell Model of the Primary Visual Cortex: Towards a Construction of Physiologically Plausible Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Tatsuya Ishiki, Satoshi Tanaka, Makoto Osanai, Shinji Doi, Sadatoshi Kumagai, and Tetsuya Yagi Representation of Medial Axis from Synchronous Firing of Border-Ownership Selective Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Yasuhiro Hatori and Ko Sakai Neural Mechanism for Extracting Object Features Critical for Visual Categorization Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Mitsuya Soga and Yoshiki Kashimori An Integrated Neuro-mechanical Model of C. elegans Forward Locomotion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Jordan H. Boyle, John Bryden, and Netta Cohen Applying the String Method to Extract Bursting Information from Microelectrode Recordings in Subthalamic Nucleus and Substantia Nigra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Pei-Kuang Chao, Hsiao-Lung Chan, Tony Wu, Ming-An Lin, and Shih-Tseng Lee Population Coding of Song Element Sequence in the Songbird Brain Nucleus HVC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Jun Nishikawa, Masato Okada, and Kazuo Okanoya Spontaneous Voltage Transients in Mammalian Retinal Ganglion Cells Dissociated by Vibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Tamami Motomura, Yuki Hayashida, and Nobuki Murayama Region-Based Encoding Method Using Multi-dimensional Gaussians for Networks of Spiking Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Lakshmi Narayana Panuku and C. Chandra Sekhar Firing Pattern Estimation of Biological Neuron Models by Adaptive Observer
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Kouichi Mitsunaga, Yusuke Totoki, and Takami Matsuo XII Table of Contents – Part I Thouless-Anderson-Palmer Equation for Associative Memory Neural Network Models with Fluctuating Couplings . . . . . . . . . . . . . . . . . . . . . . . . 93 Akihisa Ichiki and Masatoshi Shiino Spike-Timing Dependent Plasticity in Recurrently Connected Networks with Fixed External Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Matthieu Gilson, David B. Grayden, J. Leo van Hemmen, Doreen A. Thomas, and Anthony N. Burkitt A Comparative Study of Synchrony Measures for the Early Detection of Alzheimer’s Disease Based on EEG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Justin Dauwels, Fran¸ cois Vialatte, and Andrzej Cichocki Reproducibility Analysis of Event-Related fMRI Experiments Using Laguerre Polynomials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Hong-Ren Su, Michelle Liou, Philip E. Cheng, John A.D. Aston, and Shang-Hong Lai The Effects of Theta Burst Transcranial Magnetic Stimulation over the Human Primary Motor and Sensory Cortices on Cortico-Muscular Coherence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Murat Saglam, Kaoru Matsunaga, Yuki Hayashida, Nobuki Murayama, and Ryoji Nakanishi Interactions between Spike-Timing-Dependent Plasticity and Phase Response Curve Lead to Wireless Clustering . . . . . . . . . . . . . . . . . . . . . . . . 142 Hideyuki Cˆ ateau, Katsunori Kitano, and Tomoki Fukai A Computational Model of Formation of Grid Field and Theta Phase Precession in the Entorhinal Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Yoko Yamaguchi, Colin Molter, Wu Zhihua, Harshavardhan A. Agashe, and Hiroaki Wagatsuma Working Memory Dynamics in a Flip-Flop Oscillations Network Model with Milnor Attractor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 David Colliaux, Yoko Yamaguchi, Colin Molter, and Hiroaki Wagatsuma Corticopetal Acetylcholine: Possible Scenarios on the Role for Dynamic Organization of Quasi-Attractors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Hiroshi Fujii, Kazuyuki Aihara, and Ichiro Tsuda Tracking a Moving Target Using Chaotic Dynamics in a Recurrent Neural Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Yongtao Li and Shigetoshi Nara A Generalised Entropy Based Associative Model . . . . . . . . . . . . . . . . . . . . . 189
Masahiro Nakagawa Table of Contents – Part I XIII
The Detection of an Approaching Sound Source Using Pulsed Neural Network
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
Kaname Iwasa, Takeshi Fujisumi, Mauricio Kugler, Susumu Kuroyanagi, Akira Iwata, Mikio Danno, and Masahiro Miyaji Sensitivity and Uniformity in Detecting Motion Artifacts . . . . . . . . . . . . . 209
Wen-Chuang Chou, Michelle Liou, and Hong-Ren Su A Ring Model for the Development of Simple Cells in the Visual Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Takashi Hamada and Kazuhiro Okada Learning and Memory Practical Recurrent Learning (PRL) in the Discrete Time Domain . . . . . 228
Mohamad Faizal Bin Samsudin, Takeshi Hirose, and Katsunari Shibata Learning of Bayesian Discriminant Functions by a Layered Neural Network
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
Yoshifusa Ito, Cidambi Srinivasan, and Hiroyuki Izumi RNN with a Recurrent Output Layer for Learning of Naturalness . . . . . . 248
J´ an Dolinsk´ y and Hideyuki Takagi Using Generalization Error Bounds to Train the Set Covering Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258 Zakria Hussain and John Shawe-Taylor Model of Cue Extraction from Distractors by Active Recall . . . . . . . . . . . . 269 Adam Ponzi PLS Mixture Model for Online Dimension Reduction . . . . . . . . . . . . . . . . . 279 Jiro Hayami and Koichiro Yamauchi Analysis on Bidirectional Associative Memories with Multiplicative Weight Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
Chi Sing Leung, Pui Fai Sum, and Tien-Tsin Wong Fuzzy ARTMAP with Explicit and Implicit Weights . . . . . . . . . . . . . . . . . . 299
Takeshi Kamio, Kenji Mori, Kunihiko Mitsubori, Chang-Jun Ahn, Hisato Fujisaka, and Kazuhisa Haeiwa Neural Network Model of Forward Shift of CA1 Place Fields Towards Reward Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309
Adam Ponzi XIV Table of Contents – Part I Neural Network Models A New Constructive Algorithm for Designing and Training Artificial Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 Md. Abdus Sattar, Md. Monirul Islam, and Kazuyuki Murase Effective Learning with Heterogeneous Neural Networks . . . . . . . . . . . . . . 328 Llu´ıs A. Belanche-Mu˜ noz Pattern-Based Reasoning System Using Self-incremental Neural Network for Propositional Logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 Akihito Sudo, Manabu Tsuboyama, Chenli Zhang, Akihiro Sato, and Osamu Hasegawa Effect of Spatial Attention in Early Vision for the Modulation of the Perception of Border-Ownership . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 Nobuhiko Wagatsuma, Ryohei Shimizu, and Ko Sakai Effectiveness of Scale Free Network to the Performance Improvement of a Morphological Associative Memory without a Kernel Image . . . . . . . 358
Takashi Saeki and Tsutomu Miki Intensity Gradient Self-organizing Map for Cerebral Cortex Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 Cheng-Hung Chuang, Jiun-Wei Liou, Philip E. Cheng, Michelle Liou, and Cheng-Yuan Liou Feature Subset Selection Using Constructive Neural Nets with Minimal Computation by Measuring Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 374 Md. Monirul Kabir, Md. Shahjahan, and Kazuyuki Murase Dynamic Link Matching between Feature Columns for Different Scale and Orientation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
Yasuomi D. Sato, Christian Wolff, Philipp Wolfrum, and Christoph von der Malsburg Perturbational Neural Networks for Incremental Learning in Virtual Learning System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
Eiichi Inohira, Hiromasa Oonishi, and Hirokazu Yokoi Bifurcations of Renormalization Dynamics in Self-organizing Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 Peter Tiˇ no Variable Selection for Multivariate Time Series Prediction with Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 Min Han and Ru Wei Table of Contents – Part I XV Ordering Process of Self-Organizing Maps Improved by Asymmetric Neighborhood Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 Takaaki Aoki, Kaiichiro Ota, Koji Kurata, and Toshio Aoyagi A Characterization of Simple Recurrent Neural Networks with Two Hidden Units as a Language Recognizer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436
Azusa Iwata, Yoshihisa Shinozawa, and Akito Sakurai Supervised/Unsupervised/Reinforcement Learning Unbiased Likelihood Backpropagation Learning . . . . . . . . . . . . . . . . . . . . . . 446 Masashi Sekino and Katsumi Nitta The Local True Weight Decay Recursive Least Square Algorithm . . . . . . 456 Chi Sing Leung, Kwok-Wo Wong, and Yong Xu Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466
Keisuke Yamazaki and Sumio Watanabe Using Image Stimuli to Drive fMRI Analysis . . . . . . . . . . . . . . . . . . . . . . . . 477
David R. Hardoon, Janaina Mour˜ ao-Miranda, Michael Brammer, and John Shawe-Taylor Parallel Reinforcement Learning for Weighted Multi-criteria Model with Adaptive Margin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487 Kazuyuki Hiraoka, Manabu Yoshida, and Taketoshi Mishima Convergence Behavior of Competitive Repetition-Suppression Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497
Davide Bacciu and Antonina Starita Self-Organizing Clustering with Map of Nonlinear Varieties Representing Variation in One Class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 Hideaki Kawano, Hiroshi Maeda, and Norikazu Ikoma An Automatic Speaker Recognition System . . . . . . . . . . . . . . . . . . . . . . . . . 517 P. Chakraborty, F. Ahmed, Md. Monirul Kabir, Md. Shahjahan, and Kazuyuki Murase Modified Modulated Hebb-Oja Learning Rule: A Method for Biologically Plausible Principal Component Analysis . . . . . . . . . . . . . . . . . 527 Marko Jankovic, Pablo Martinez, Zhe Chen, and Andrzej Cichocki Statistical Learning Algorithms Orthogonal Shrinkage Methods for Nonparametric Regression under Gaussian Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537 Katsuyuki Hagiwara XVI Table of Contents – Part I A Subspace Method Based on Data Generation Model with Class Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547
Minkook Cho, Dongwoo Yoon, and Hyeyoung Park Hierarchical Feature Extraction for Compact Representation and Classification of Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 Markus Schubert and Jens Kohlmorgen Principal Component Analysis for Sparse High-Dimensional Data . . . . . . 566 Tapani Raiko, Alexander Ilin, and Juha Karhunen Hierarchical Bayesian Inference of Brain Activity . . . . . . . . . . . . . . . . . . . . . 576 Masa-aki Sato and Taku Yoshioka Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 586
Byron M. Yu, John P. Cunningham, Krishna V. Shenoy, and Maneesh Sahani Estimating Internal Variables of a Decision Maker’s Brain: A Model-Based Approach for Neuroscience . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596
Kazuyuki Samejima and Kenji Doya Visual Tracking Achieved by Adaptive Sampling from Hierarchical and Parallel Predictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 604 Tomohiro Shibata, Takashi Bando, and Shin Ishii Bayesian System Identification of Molecular Cascades . . . . . . . . . . . . . . . . 614 Junichiro Yoshimoto and Kenji Doya Use of Circle-Segments as a Data Visualization Technique for Feature Selection in Pattern Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625
Shir Li Wang, Chen Change Loy, Chee Peng Lim, Weng Kin Lai, and Kay Sin Tan Extraction of Approximate Independent Components from Large Natural Scenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635
Yoshitatsu Matsuda and Kazunori Yamaguchi Local Coordinates Alignment and Its Linearization . . . . . . . . . . . . . . . . . . . 643
Tianhao Zhang, Xuelong Li, Dacheng Tao, and Jie Yang Walking Appearance Manifolds without Falling Off . . . . . . . . . . . . . . . . . . . 653
Nils Einecke, Julian Eggert, Sven Hellbach, and Edgar K¨ orner
Inverse-Halftoning for Error Diffusion Based on Statistical Mechanics of the Spin System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663
Yohei Saika Table of Contents – Part I XVII
Optimization Algorithms Chaotic Motif Sampler for Motif Discovery Using Statistical Values of Spike Time-Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673 Takafumi Matsuura and Tohru Ikeguchi A Thermodynamical Search Algorithm for Feature Subset Selection . . . .
683 F´ elix F. Gonz´ alez and Llu´ıs A. Belanche Solvable Performances of Optimization Neural Networks with Chaotic Noise and Stochastic Noise with Negative Autocorrelation . . . . . . . . . . . . . 693 Mikio Hasegawa and Ken Umeno Solving the k-Winners-Take-All Problem and the Oligopoly Cournot-Nash Equilibrium Problem Using the General Projection Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 703
Xiaolin Hu and Jun Wang Optimization of Parametric Companding Function for an Efficient Coding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713 Shin-ichi Maeda and Shin Ishii A Modified Soft-Shape-Context ICP Registration System of 3-D Point Data
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Jiann-Der Lee, Chung-Hsien Huang, Li-Chang Liu, Shih-Sen Hsieh, Shuen-Ping Wang, and Shin-Tseng Lee Solution Method Using Correlated Noise for TSP . . . . . . . . . . . . . . . . . . . . 733 Atsuko Goto and Masaki Kawamura Novel Algorithms Bayesian Collaborative Predictors for General User Modeling Tasks . . . . 742
Jun-ichiro Hirayama, Masashi Nakatomi, Takashi Takenouchi, and Shin Ishii Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 752
Shohei Shimizu and Aapo Hyv¨ arinen
Efficient Incremental Learning Using Self-Organizing Neural Grove . . . . . 762 Hirotaka Inoue and Hiroyuki Narihisa Design of an Unsupervised Weight Parameter Estimation Method in Ensemble Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771
Masato Uchida, Yousuke Maehara, and Hiroyuki Shioya Sparse Super Symmetric Tensor Factorization . . . . . . . . . . . . . . . . . . . . . . . 781
Andrzej Cichocki, Marko Jankovic, Rafal Zdunek, and Shun-ichi Amari XVIII Table of Contents – Part I Probabilistic Tensor Analysis with Akaike and Bayesian Information Criteria
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Dacheng Tao, Jimeng Sun, Xindong Wu, Xuelong Li, Jialie Shen, Stephen J. Maybank, and Christos Faloutsos Decomposing EEG Data into Space-Time-Frequency Components Using Parallel Factor Analysis and Its Relation with Cerebral Blood Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 802 Fumikazu Miwakeichi, Pedro A. Valdes-Sosa, Eduardo Aubert-Vazquez, Jorge Bosch Bayard, Jobu Watanabe, Hiroaki Mizuhara, and Yoko Yamaguchi Flexible Component Analysis for Sparse, Smooth, Nonnegative Coding or Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 811
Andrzej Cichocki, Anh Huy Phan, Rafal Zdunek, and Li-Qing Zhang Appearance Models for Medical Volumes with Few Samples by Generalized 3D-PCA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 821 Rui Xu and Yen-Wei Chen Head Pose Estimation Based on Tensor Factorization . . . . . . . . . . . . . . . . . 831 Wenlu Yang, Liqing Zhang, and Wenjun Zhu Kernel Maximum a Posteriori Classification with Error Bound Analysis
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Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, and Michael R. Lyu Comparison of Local Higher-Order Moment Kernel and Conventional Kernels in SVM for Texture Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 851
Keisuke Kameyama Pattern Discovery for High-Dimensional Binary Datasets . . . . . . . . . . . . . . 861
V´ aclav Sn´ aˇ sel, Pavel Moravec, Duˇ san H´ usek, Alexander Frolov, Hana ˇ Rezankov´ a, and Pavel Polyakov Expand-and-Reduce Algorithm of Particle Swarm Optimization . . . . . . . . 873
Eiji Miyagawa and Toshimichi Saito Nonlinear Pattern Identification by Multi-layered GMDH-Type Neural Network Self-selecting Optimum Neural Network Architecture . . . . . . . . . 882 Tadashi Kondo Motor Control and Vision Coordinated Control of Reaching and Grasping During Prehension Movement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 892 Masazumi Katayama and Hirokazu Katayama Table of Contents – Part I XIX
Computer Simulation of Vestibuloocular Reflex Motor Learning Using a Realistic Cerebellar Cortical Neuronal Network Model . . . . . . . . . . . . . . 902
Kayichiro Inagaki, Yutaka Hirata, Pablo M. Blazquez, and Stephen M. Highstein Reflex Contributions to the Directional Tuning of Arm Stiffness . . . . . . . . 913 Gary Liaw, David W. Franklin, Etienne Burdet, Abdelhamid Kadi-allah, and Mitsuo Kawato Analysis of Variability of Human Reaching Movements Based on the Similarity Preservation of Arm Trajectories . . . . . . . . . . . . . . . . . . . . . . . . . 923 Takashi Oyama, Yoji Uno, and Shigeyuki Hosoe Directional Properties of Human Hand Force Perception in the Maintenance of Arm Posture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 933
Yoshiyuki Tanaka and Toshio Tsuji Computational Understanding and Modeling of Filling-In Process at the Blind Spot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 943 Shunji Satoh and Shiro Usui Biologically Motivated Face Selective Attention Model . . . . . . . . . . . . . . . . 953 Woong-Jae Won, Young-Min Jang, Sang-Woo Ban, and Minho Lee Multi-dimensional Histogram-Based Image Segmentation . . . . . . . . . . . . . . 963 Daniel Weiler and Julian Eggert A Framework for Multi-view Gender Classification . . . . . . . . . . . . . . . . . . . 973 Jing Li and Bao-Liang Lu Japanese Hand Sign Recognition System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 983 Hirotada Fujimura, Yuuichi Sakai, and Hiroomi Hikawa An Image Warping Method for Temporal Subtraction Images Employing Smoothing of Shift Vectors on MDCT Images . . . . . . . . . . . . . 993
Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, Takayuki Ishida, Ikuo Kawashita, Kazuo Awai, and Kunio Doi Conflicting Visual and Proprioceptive Reflex Responses During Reaching Movements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1002 David W. Franklin, Udell So, Rieko Osu, and Mitsuo Kawato An Involuntary Muscular Response Induced by Perceived Visual Errors in Hand Position . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1012 David W. Franklin, Udell So, Rieko Osu, and Mitsuo Kawato Independence of Perception and Action for Grasping Positions . . . . . . . . . 1021 Takahiro Fujita, Yoshinobu Maeda, and Masazumi Katayama XX Table of Contents – Part I Handwritten Character Distinction Method Inspired by Human Vision Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1031 Jumpei Koyama, Masahiro Kato, and Akira Hirose Recent Advances in the Neocognitron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1041 Kunihiko Fukushima Engineering-Approach Accelerates Computational Understanding of V1–V2 Neural Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1051 Shunji Satoh and Shiro Usui Recent Studies Around the Neocognitron . . . . . . . . . . . . . . . . . . . . . . . . . . . 1061 Hayaru Shouno Toward Human Arm Attention and Recognition . . . . . . . . . . . . . . . . . . . . . 1071 Takeharu Yoshizuka, Masaki Shimizu, and Hiroyuki Miyamoto Projection-Field-Type VLSI Convolutional Neural Networks Using Merged/Mixed Analog-Digital Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1081 Osamu Nomura and Takashi Morie Optimality of Reaching Movements Based on Energetic Cost under the Influence of Signal-Dependent Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1091 Yoshiaki Taniai and Jun Nishii Influence of Neural Delay in Sensorimotor Systems on the Control Performance and Mechanism in Bicycle Riding . . . . . . . . . . . . . . . . . . . . . . . 1100 Yusuke Azuma and Akira Hirose Global Localization for the Mobile Robot Based on Natural Number Recognition in Corridor Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1110 Su-Yong An, Jeong-Gwan Kang, Se-Young Oh, and Doo San Baek A System Model for Real-Time Sensorimotor Processing in Brain . . . . . . 1120 Yutaka Sakaguchi Perception of Two-Stroke Apparent Motion and Real Motion . . . . . . . . . . 1130 Qi Zhang and Ken Mogi Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1141 M. Ishikawa et al. (Eds.): ICONIP 2007, Part I, LNCS 4984, pp. 1–6, 2008. © Springer-Verlag Berlin Heidelberg 2008 Download 12.42 Mb. Do'stlaringiz bilan baham: 
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