Neural Information Processing

1. Front Matter

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2. Distance- and Direction-Dependent Synaptic Weight Distributions for Directional Spike Propagation in a Recurrent Network: Self-actuated Shutdown of Synaptic Plasticity

   • Toshikazu Samura, Yutaka Sakai, Hatsuo Hayashi, Takeshi Aihara

   Pages 1-8

3. Modulated Neuronal Activity and Connectivity of Smoking Resist Using Real-Time fMRI Neurofeedback

   • Dong-Youl Kim, Jong-Hwan Lee

   Pages 9-16

4. Parameterized Digital Hardware Design of Pulse-Coupled Phase Oscillator Model toward Spike-Based Computing

   • Yasuhiro Suedomi, Hakaru Tamukoh, Michio Tanaka, Kenji Matsuzaka, Takashi Morie

   Pages 17-24

5. Brain-Inspired e-Learning System Using EEG

   • Kiyohisa Natsume

   Pages 25-32

6. A Method to Deal with Prospective Risks at Home in Robotic Observations by Using a Brain-Inspired Model

   • David Chik, Gyanendra Nath Tripathi, Hiroaki Wagatsuma

   Pages 33-40

7. A Study on Region of Interest of a Selective Attention Based on Gestalt Principles

   • Hyunrae Jo, Amitash Ojha, Minho Lee

   Pages 41-48

8. Triggered Initiation of Retrograde Wave Propagation in a Cable of FitzHugh-Nagumo Cells

   • Katsumi Tateno

   Pages 49-54

9. Spiking Neural Network for On-line Cognitive Activity Classification Based on EEG Data

   • Stefan Schliebs, Elisa Capecci, Nikola Kasabov

   Pages 55-62

10. Spatio-temporal EEG Data Classification in the NeuCube 3D SNN Environment: Methodology and Examples

    • Nikola Kasabov, Jin Hu, Yixiong Chen, Nathan Scott, Yulia Turkova

    Pages 63-69

11. NeuCubeRehab: A Pilot Study for EEG Classification in Rehabilitation Practice Based on Spiking Neural Networks

    • Yixiong Chen, Jin Hu, Nikola Kasabov, Zengguang Hou, Long Cheng

    Pages 70-77

12. NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation

    • Nathan Scott, Nikola Kasabov, Giacomo Indiveri

    Pages 78-84

13. Vector Quantization Using Mixture of Epsilon-Insensitive Components

    • Kazuho Watanabe

    Pages 85-92

14. Applicability of ICA-Based Dimension Reduction in Fuzzy c-Means-Based Classifier

    • Takuya Kobayashi, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi

    Pages 93-100

15. Random Segmentation Based Principal Component Analysis to Remove Residual MR Gradient Artifact in the Simultaneous EEG/fMRI: A Preliminary Study

    • Hyun-Chul Kim, Jong-Hwan Lee

    Pages 101-107

16. Extracting Latent Dynamics from Multi-dimensional Data by Probabilistic Slow Feature Analysis

    • Toshiaki Omori

    Pages 108-116

17. Challenges in Representation Learning: A Report on Three Machine Learning Contests

    • Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron Courville, Mehdi Mirza, Ben Hamner et al.

    Pages 117-124

18. A Comparative Study on Image Retrieval Systems

    • Chee Sheen Chan, Jer Lang Hong

    Pages 125-132

19. Identifying Association between Longer Itemsets and Software Defects

    • Zeeshan A. Rana, Sehrish Abdul Malik, Shafay Shamail, Mian M. Awais

    Pages 133-140

20. Detection of Driving Fatigue Based on Grip Force on Steering Wheel with Wavelet Transformation and Support Vector Machine

    • Fan Li, Xiao-Wei Wang, Bao-Liang Lu

    Pages 141-148

The three volume set LNCS 8226, LNCS 8227, and LNCS 8228 constitutes the proceedings of the 20th International Conference on Neural Information Processing, ICONIP 2013, held in Daegu, Korea, in November 2013. The 180 full and 75 poster papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The specific topics covered are as follows: cognitive science and artificial intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing; control, robotics and hardware technologies and novel approaches and applications.

• activity recognition
• artificial intelligence
• image processing
• machine learning
• pattern recognition

• Kyungpook National University, Taegu, Korea

  Minho Lee

• The University of Tokyo, Bunkyo-ku, Japan

  Akira Hirose

• Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, Beijing, China

  Zeng-Guang Hou

• Sungkyunkwan University, Suwon, Korea

  Rhee Man Kil

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