Advances in Neural Networks- ISNN 2013

1. Neural Network Models, Learning Algorithms, Stability and Convergence Analysis

   1. Stability Analysis of a Class of High Order Fuzzy Cohen-Grossberg Neural Networks with Mixed Delays and Reaction-Diffusion Terms

      • Weifan Zheng, Jiye Zhang, Mingwen Wang

      Pages 157-165

   2. A Study on the Randomness Reduction Effect of Extreme Learning Machine with Ridge Regression

      • Meng Joo Er, Zhifei Shao, Ning Wang

      Pages 166-173

   3. Stability of Nonnegative Periodic Solutions of High-Ordered Neural Networks

      • Lili Wang, Tianping Chen

      Pages 174-180

   4. Existence of Periodic Solution for Competitive Neural Networks with Time-Varying and Distributed Delays on Time Scales

      • Yang Liu, Yongqing Yang, Tian Liang, Xianyun Xu

      Pages 181-188

   5. Global Exponential Stability in the Mean Square of Stochastic Cohen-Grossberg Neural Networks with Time-Varying and Continuous Distributed Delays

      • Tian Liang, Yongqing Yang, Manfeng Hu, Yang Liu, Li Li

      Pages 189-196

   6. A Delay-Partitioning Approach to Stability Analysis of Discrete-Time Recurrent Neural Networks with Randomly Occurred Nonlinearities

      • Jianmin Duan, Manfeng Hu, Yongqing Yang

      Pages 197-204

   7. The Universal Approximation Capabilities of Mellin Approximate Identity Neural Networks

      • Saeed Panahian Fard, Zarita Zainuddin

      Pages 205-213

   8. H _∞ Filtering of Markovian Jumping Neural Networks with Time Delays

      • He Huang, Xiaoping Chen, Qiang Hua

      Pages 214-221

   9. Convergence Analysis for Feng’s MCA Neural Network Learning Algorithm

      • Zhengxue Li, Lijia You, Mingsong Cheng

      Pages 222-229

   10. Anti-periodic Solutions for Cohen-Grossberg Neural Networks with Varying-Time Delays and Impulses

       • Abdujelil Abdurahman, Haijun Jiang

       Pages 230-238

   11. Global Robust Exponential Stability in Lagrange Sense for Interval Delayed Neural Networks

       • Xiaohong Wang, Xingjun Chen, Huan Qi

       Pages 239-249

   12. The Binary Output Units of Neural Network

       • Qilin Sun, Yan Liu, Zhengxue Li, Sibo Yang, Wei Wu, Jiuwu Jin

       Pages 250-257

2. Kernel Methods, Large Margin Methods and SVM

   1. Support Vector Machine with Customized Kernel

      • Guangyi Chen, Tien Dai Bui, Adam Krzyzak, Weihua Liu

      Pages 258-264

   2. Semi-supervised Kernel Minimum Squared Error Based on Manifold Structure

      • Haitao Gan, Nong Sang, Xi Chen

      Pages 265-272

   3. Noise Effects on Spatial Pattern Data Classification Using Wavelet Kernel PCA

      • Shengkun Xie, Anna T. Lawniczak, Sridhar Krishnan

      Pages 273-282

   4. SVM-SVDD: A New Method to Solve Data Description Problem with Negative Examples

      • Zhigang Wang, Zeng-Shun Zhao, Changshui Zhang

      Pages 283-290

   5. Applying Wavelet Packet Decomposition and One-Class Support Vector Machine on Vehicle Acceleration Traces for Road Anomaly Detection

      • Fengyu Cong, Hannu Hautakangas, Jukka Nieminen, Oleksiy Mazhelis, Mikko Perttunen, Jukka Riekki et al.

      Pages 291-299

   6. Aeroengine Turbine Exhaust Gas Temperature Prediction Using Process Support Vector Machines

      • Xu-yun Fu, Shi-sheng Zhong

      Pages 300-310

   7. The Effect of Lateral Inhibitory Connections in Spatial Architecture Neural Network

      • Gang Yang, Jun-fei Qiao, Wei Li, Wei Chai

      Pages 311-318

   8. Empirical Mode Decomposition Based LSSVM for Ship Motion Prediction

      • Zhou Bo, Shi Aiguo

      Pages 319-325

The two-volume set LNCS 7951 and 7952 constitutes the refereed proceedings of the 10th International Symposium on Neural Networks, ISNN 2013, held in Dalian, China, in July 2013. The 157 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in following topics: computational neuroscience, cognitive science, neural network models, learning algorithms, stability and convergence analysis, kernel methods, large margin methods and SVM, optimization algorithms, varational methods, control, robotics, bioinformatics and biomedical engineering, brain-like systems and brain-computer interfaces, data mining and knowledge discovery and other applications of neural networks.

• algorithms
• extreme learning machines
• fuzzy modeling
• multi-objective optimization
• recommender systems
• algorithm analysis and problem complexity

• School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

  Chengan Guo

• Institute of Automation, Chinese Academy of Sciences, Beijing, China

  Zeng-Guang Hou

• School of Automation, Huazhong University of Science and Technology, Wuhan, China

  Zhigang Zeng

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