Advances in Neural Networks - ISNN 2009

1. Robotics

   1. Tracking Control of Robot Manipulators via Orthogonal Polynomials Neural Network

      • Hongwei Wang, Shuanghe Yu

      Pages 178-187

   2. Q-Learning Based on Dynamical Structure Neural Network for Robot Navigation in Unknown Environment

      • Junfei Qiao, Ruiyuan Fan, Honggui Han, Xiaogang Ruan

      Pages 188-196

   3. Research on Mobile Robot’s Motion Control and Path Planning

      • Shigang Cui, Xuelian Xu, Li Zhao, Liguo Tian, Genghuang Yang

      Pages 197-206

   4. A New Cerebellar Model Articulation Controller for Rehabilitation Robots

      • Shan Liu, Yongji Wang, Yongle Xie, Shuyan Jiang, Jinsong Meng

      Pages 207-216

   5. Layer-TERRAIN: An Improved Algorithm of TERRAIN Based on Sequencing the Reference Nodes in UWSNs

      • Yue Liang, Zhong Liu

      Pages 217-225

   6. A Hybrid Neural Network Method for UAV Attack Route Integrated Planning

      • Nan Wang, Xueqiang Gu, Jing Chen, Lincheng Shen, Min Ren

      Pages 226-235

   7. Hybrid Game Theory and D-S Evidence Approach to Multiple UCAVs Cooperative Air Combat Decision

      • Xingxing Wei, Haibin Duan, Yanran Wang

      Pages 236-246

   8. FCMAC Based Guidance Law for Lifting Reentry Vehicles

      • Hao Wu, Chuanfeng Li, Yongji Wang

      Pages 247-256

   9. Hybrid Filter Based Simultaneous Localization and Mapping for a Mobile Robot

      • Kyung-Sik Choi, Bong-Keun Song, Suk-Gyu Lee

      Pages 257-266

   10. Using Toe-Off Impulse to Control Chaos in the Simplest Walking Model via Artificial Neural Network

       • Saeed Jamali, Karim Faez, Sajjad Taghvaee, Mostafa Ozlati Moghadam

       Pages 267-277

   11. Reinforcement Learning Control of a Real Mobile Robot Using Approximate Policy Iteration

       • Pengcheng Zhang, Xin Xu, Chunming Liu, Qiping Yuan

       Pages 278-288

2. Image Processing

   1. A Simple Neural Network for Enhancement of Image Acuity by Fixational Instability

      • Daqing Yi, Ping Jiang, Jin Zhu

      Pages 289-298

   2. A General-Purpose FPGA-Based Reconfigurable Platform for Video and Image Processing

      • Jie Li, Haibo He, Hong Man, Sachi Desai

      Pages 299-309

   3. Image Analysis by Modified Krawtchouk Moments

      • Luo Zhu, Jiaping Liao, Xiaoqin Tong, Li Luo, Bo Fu, Guojun Zhang

      Pages 310-317

   4. Efficient Provable Secure ID-Based Directed Signature Scheme without Random Oracle

      • Jianhong Zhang, Yixian Yang, Xinxin Niu

      Pages 318-327

   5. Mask Particle Filter for Similar Objects Tracking

      • Huaping Liu, Fuchun Sun, Meng Gao

      Pages 328-336

   6. An Efficient Wavelet Based Feature Extraction Method for Face Recognition

      • Iman Makaremi, Majid Ahmadi

      Pages 337-345

   7. Face Recognition Based on Histogram of Modular Gabor Feature and Support Vector Machines

      • Xiaodong Li, Shumin Fei, Tao Zhang

      Pages 346-355

   8. Feature-Level Fusion of Iris and Face for Personal Identification

      • Zhifang Wang, Qi Han, Xiamu Niu, Christoph Busch

      Pages 356-364

   9. Watermark Image Restoration Method Based on Block Hopfield Network

      • Xiaohong Ma, Xin Li, Hualou Liang

      Pages 365-370

This book and its companion volumes, LNCS vols. 5551, 5552 and 5553, constitute the proceedings of the 6th International Symposium on Neural Networks (ISNN 2009), held during May 26–29, 2009 in Wuhan, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural n- works and related fields, with a successful sequence of ISNN symposia held in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), and Beijing (2008). Following the tradition of the ISNN series, ISNN 2009 provided a high-level inter- tional forum for scientists, engineers, and educators to present state-of-the-art research in neural networks and related fields, and also to discuss with international colleagues on the major opportunities and challenges for future neural network research. Over the past decades, the neural network community has witnessed tremendous - forts and developments in all aspects of neural network research, including theoretical foundations, architectures and network organizations, modeling and simulation, - pirical study, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, have provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large-scale, and n- worked brain-like intelligent systems. This long-term goal can only be achieved with the continuous efforts of the community to seriously investigate different issues of the neural networks and related fields.

• algorithm
• algorithms
• artificial intelligence
• classification
• communication
• fuzzy
• fuzzy system
• genetic algorithms
• image processing
• learning
• machine learning
• modeling
• optimization
• robot
• robotics
• algorithm analysis and problem complexity

• Departamento de Control Automático, CINVESTAV-IPN, México D.F., México

  Wen Yu

• Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA

  Haibo He

• Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, Rapid City, USA

  Nian Zhang

Policies and ethics