Theoretical Analysis

• 
  Shun-ichi Amari: Population Coding, Bayesian Inference and Information Geometry. 1-4
• 
  Lei Xu: One-Bit-Matching ICA Theorem, Convex-Concave Programming, and Combinatorial Optimization. 5-20
• 
  Walter J. Freeman: Dynamic Models for Intention (Goal-Directedness) Are Required by Truly Intelligent Robots. 21-33
• 
  Shoujue Wang, Yangyang Liu: Differences and Commonalities Between Connectionism and Symbolicism. 34-38
• 
  Feilong Cao, Zongben Xu, Youmei Li: Pointwise Approximation for Neural Networks. 39-44
• 
  Lipo Wang, Bing Liu, Chunru Wan: On the Universal Approximation Theorem of Fuzzy Neural Networks with Random Membership Function Parameters. 45-50
• 
  Tan Shan, Xiuli Ma, Xiangrong Zhang, Licheng Jiao: A Review: Relationship Between Response Properties of Visual Neurons and Advances in Nonlinear Approximation Theory. 51-56
• 
  Tan Shan, Xiangrong Zhang, Shuang Wang, Licheng Jiao: Image Representation in Visual Cortex and High Nonlinear Approximation. 57-62
• 
  Youmei Li, Zongben Xu, Feilong Cao: Generalization and Property Analysis of GENET. 63-68
• 
  Yumin Zhang, Lei Guo, Lingyao Wu, Chun-Bo Feng: On Stochastic Neutral Neural Networks. 69-74
• 
  Chunshu Zhang: Eigenanalysis of CMAC Neural Network. 75-80
• 
  Xizhao Wang, Chunguo Li: A New Definition of Sensitivity for RBFNN and Its Applications to Feature Reduction. 81-86
• 
  Xun Liang: Complexity of Error Hypersurfaces in Multilayer Perceptrons with General Multi-input and Multi-output Architecture. 87-94
• 
  Deepak Mishra, Abhishek Yadav, Sudipta Ray, Prem Kumar Kalra: Nonlinear Dynamical Analysis on Coupled Modified Fitzhugh-Nagumo Neuron Model. 95-101
• 
  Haijun Jiang, Jinde Cao, Zhidong Teng: Stability of Nonautonomous Recurrent Neural Networks with Time-Varying Delays. 102-107
• 
  Minghui Jiang, Yi Shen, Meiqin Liu: Global Exponential Stability of Non-autonomous Neural Networks with Variable Delay. 108-113
• 
  Yi Shen, Minghui Jiang, Xiaoxin Liao: A Generalized LMI-Based Approach to the Global Exponential Stability of Recurrent Neural Networks with Delay. 114-119
• 
  Jun Zhang, Xiaofeng Liao, Chuandong Li, Anwen Lu: A Further Result for Exponential Stability of Neural Networks with Time-Varying Delays. 120-125
• 
  Deyin Wu, Qingyu Xiong, Chuandong Li, Zhong Zhang, Haoyang Tang: Improved Results for Exponential Stability of Neural Networks with Time-Varying Delays. 126-131
• 
  Qiankun Song, Zhenjiang Zhao, Xuedong Chen: Global Exponential Stability of Recurrent Neural Networks with Infinite Time-Varying Delays and Reaction-Diffusion Terms. 132-141
• 
  Huaguang Zhang, Zhanshan Wang, Derong Liu: Exponential Stability Analysis of Neural Networks with Multiple Time Delays. 142-148
• 
  Wei Zhang, Jianqiao Yu: Exponential Stability of Cohen-Grossberg Neural Networks with Delays. 149-155
• 
  Yi Shen, Minghui Jiang, Xiaoxin Liao: Global Exponential Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays and Continuously Distributed Delays. 156-161
• 
  Xiaolin Li, Jinde Cao: Exponential Stability of Stochastic Cohen-Grossberg Neural Networks with Time-Varying Delays. 162-167
• 
  Tingwen Huang, Linhua Zhang: Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Delay. 168-173
• 
  Zhihong Tang, Yiping Luo, Feiqi Deng: Global Exponential Stability of Reaction-Diffusion Hopfield Neural Networks with Distributed Delays. 174-180
• 
  Bingji Xu, Qun Wang, Yi Shen, Xiaoxin Liao: Global Exponential Stability of Delayed Impulsive Hopfield Type Neural Networks. 181-186
• 
  Zhichun Yang, Jinan Pei, Daoyi Xu, Yumei Huang, Li Xiang: Global Exponential Stability of Hopfield Neural Networks with Impulsive Effects. 187-192
• 
  Qiang Zhang, Wenbing Liu, Xiaopeng Wei: Global Exponential Stability of Discrete Time Hopfield Neural Networks with Delays. 193-198
• 
  Hanlin He, Zhongsheng Wang, Xiaoxin Liao: Stability Analysis of Uncertain Neural Networks with Linear and Nonlinear Time Delays. 199-202
• 
  Li Xie, Tianming Liu, Jilin Liu, WeiKang Gu, Stephen T. C. Wong: Robust Stability for Delayed Neural Networks with Nonlinear Perturbation. 203-208
• 
  Huaguang Zhang, Ce Ji, Derong Liu: Robust Stability Analysis of a Class of Hopfield Neural Networks with Multiple Delays. 209-214
• 
  Wenlian Lu, Tianping Chen: Robust Stability of Interval Delayed Neural Networks. 215-221
• 
  Yinping Zhang, Jitao Sun: Impulsive Robust Control of Interval Hopfield Neural Networks. 222-228
• 
  Tao Xiang, Xiaofeng Liao, Jian Huang: Global Attractivity of Cohen-Grossberg Model with Delays. 229-234
• 
  Yi Shen, Xiaojun Zong, Minghui Jiang: High-Order Hopfield Neural Networks. 235-240
• 
  Jinan Pei, Daoyi Xu, Zhichun Yang, Wei Zhu: Stability Analysis of Second Order Hopfield Neural Networks with Time Delays. 241-246
• 
  Hongtao Lu, Zhizhou Zhang, Lin He: Convergence Analysis of Genetic Regulatory Networks Based on Nonlinear Measures. 247-252
• 
  Runnian Ma, Shengrui Zhang, Sheping Lei: Stability Conditions for Discrete Neural Networks in Partial Simultaneous Updating Mode. 253-258
• 
  Runnian Ma, Sheping Lei, Shengrui Zhang: Dynamic Behavior Analysis of Discrete Neural Networks with Delay. 259-264
• 
  Xiaofan Yang, David J. Evans, Yuan Yan Tang: Existence and Stability of Periodic Solution in a Class of Impulsive Neural Networks. 265-270
• 
  Changyin Sun, Liangzhen Xia, Chun-Bo Feng: Globally Attractive Periodic Solutions of Continuous-Time Neural Networks and Their Discrete-Time Counterparts. 271-275
• 
  Chaojin Fu, Hanlin He, Xiaoxin Liao: Globally Stable Periodic State of Delayed Cohen-Grossberg Neural Networks. 276-281
• 
  Zhigang Zeng, Boshan Chen, Zengfu Wang: Globally Attractive Periodic State of Discrete-Time Cellular Neural Networks with Time-Varying Delays. 282-287
• 
  Jianlong Qiu, Jinde Cao: An Analysis for Periodic Solutions of High-Order BAM Neural Networks with Delays. 288-293
• 
  Boshan Chen: Periodic Oscillation and Exponential Stability of a Class of Competitive Neural Networks. 294-301
• 
  Ying Wu, Jianxue Xu, Wuyin Jin: Synchronous Behaviors of Two Coupled Neurons. 302-307
• 
  Jin Zhou, Tianping Chen, Xiang Lan: Adaptive Synchronization of Delayed Neural Networks Based on Parameters Identification. 308-313
• 
  Yan Li, Xiaoli Li, Gaoxiang Ouyang, Xinping Guan: Strength and Direction of Phase Synchronization of Neural Networks. 314-319
• 
  Shaorong Li, Shaowen Li, Xipeng Sun, Jie Li: Hopf Bifurcation in a Single Inertial Neuron Model: A Frequency Domain Approach. 320-326
• 
  Shaowen Li, Shaorong Li: Hopf Bifurcation in a Single Inertial Neuron Model with a Discrete Delay. 327-333
• 
  Xu Xu, Yanchun Liang: Stability and Bifurcation of a Neuron Model with Delay-Dependent Parameters. 334-339
• 
  Shangbo Zhou, Hua Li, Zhongfu Wu: Stability and Chaos of a Neural Network with Uncertain Time Delays. 340-345
• 
  Fenghua Tu, Xiaofeng Liao, Chuandong Li: Chaotic Synchronization of Delayed Neural Networks. 346-350
• 
  Xiaohong Zhang, Shangbo Zhou: Chaos Synchronization for Bi-directional Coupled Two-Neuron Systems with Discrete Delays. 351-356
• 
  Qingdu Li, Xiao-Song Yang: Complex Dynamics in a Simple Hopfield-Type Neural Network. 357-362
• 
  Lidan Wang, Shukai Duan, Guangyuan Liu: Adaptive Chaotic Controlling Method of a Chaotic Neural Network Model. 363-368

Model Design

• 
  Wentao Huang, Licheng Jiao, Maoguo Gong, Chuang Guo: Modeling Cortex Network: A Spatio-temporal Population Approach. 369-374
• 
  Xusheng Sun, Shuning Wang: A Special Kind of Neural Networks: Continuous Piecewise Linear Functions. 375-379
• 
  Yingtung Hsiao, Chenglong Chuang, Joeair Jiang, Chiang Wang, Chengchih Chien: A Novel Dynamic Structural Neural Network with Neuron-Regeneration and Neuron-Degeneration Mechanisms. 380-384
• 
  Shuyuan Yang, Min Wang, Licheng Jiao: A New Adaptive Ridgelet Neural Network. 385-390
• 
  Bo Liu, Ling Wang, Yihui Jin, Dexian Huang: Designing Neural Networks Using Hybrid Particle Swarm Optimization. 391-397
• 
  Gengsheng Zheng, Sidney Nascimento Givigi, Weiyu Zheng: A New Strategy for Designing Bidirectional Associative Memories. 398-403
• 
  Sung-Kwun Oh, Byoung-Jun Park, Hyun-Ki Kim: Genetically Optimized Hybrid Fuzzy Neural Networks Based on TSK Fuzzy Rules and Polynomial Neurons. 404-409
• 
  Ho-Sung Park, Daehee Park, Sung-Kwun Oh: Genetically Optimized Self-organizing Fuzzy Polynomial Neural Networks Based on Information Granulation. 410-415
• 
  Sung-Kwun Oh, Keon-Jun Park, Hyung-Soo Hwang: Identification of ANFIS-Based Fuzzy Systems with the Aid of Genetic Optimization and Information Granulation. 416-421
• 
  Byoung-Jun Park, Sung-Kwun Oh: Design of Rule-Based Neurofuzzy Networks by Means of Genetic Fuzzy Set-Based Granulation. 422-427
• 
  Sung-Kwun Oh, Seok-Beom Roh, Yong-Kab Kim: Design of Genetic Fuzzy Set-Based Polynomial Neural Networks with the Aid of Information Granulation. 428-433
• 
  Meng Joo Er, Rishikesh Parthasarathi: A Novel Self-organizing Neural Fuzzy Network for Automatic Generation of Fuzzy Inference Systems. 434-439
• 
  Lunwen Wang, Ying Tan, Ling Zhang: Constructive Fuzzy Neural Networks and Its Application. 440-445
• 
  Jianye Zhao, Hongling Meng, Daoheng Yu: A Novel CNN Template Design Method Based on GIM. 446-454
• 
  Yong Chen, Guoyin Wang, Fan Jin, Tianyun Yan: A Novel Generalized Congruence Neural Networks. 455-460
• 
  Cristofer Englund, Antanas Verikas: A SOM Based Model Combination Strategy. 461-466
• 
  Jing Li, Bao-Liang Lu, Michinori Ichikawa: Typical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function. 467-472
• 
  Shisheng Zhong, Gang Ding, Daizhong Su: Parallel Feedforward Process Neural Network with Time-Varying Input and Output Functions. 473-478
• 
  Zihong Liu, Zhihua Wang, Guolin Li, Zhiping Yu: A Novel Solid Neuron-Network Chip Based on Both Biological and Artificial Neural Network Theories. 479-484
• 
  Ming-Jung Seow, Vijayan K. Asari: Associative Memory Using Nonlinear Line Attractor Network for Multi-valued Pattern Association. 485-490
• 
  Shukai Duan, Lidan Wang: Associative Chaotic Neural Network via Exponential Decay Spatio-temporal Effect. 491-496
• 
  Tian-yi Ma, Ling Wang, Yingtao Jiang, Xiao-Zong Yang: On a Chaotic Neural Network with Decaying Chaotic Noise. 497-502
• 
  Manghui Wang: Extension Neural Network-Type 3. 503-508
• 
  Junquan Li, Yixin Yin: Pulsed Para-neural Networks (PPNN) Based on MEXORs and Counters. 509-514
• 
  Jian Tang, Zengqi Sun, Jihong Zhu: Using Ensemble Information in Swarming Artificial Neural Networks. 515-519
• 
  Zheng Qin, Yu Liu, Xingchen Heng, Xianhui Wang: Negatively Correlated Neural Network Ensemble with Multi-population Particle Swarm Optimization. 520-525
• 
  Haixia Chen, Senmiao Yuan, Kai Jiang: Wrapper Approach for Learning Neural Network Ensemble by Feature Selection. 526-531
• 
  Yue Liu, Yuan Li, Guo-Zheng Li, Bofeng Zhang, Gengfeng Wu: Constructive Ensemble of RBF Neural Networks and Its Application to Earthquake Prediction. 532-537

Learning Methods

• 
  Bin Zou, Luoqing Li, Jie Xu: The Bounds on the Rate of Uniform Convergence for Learning Machine. 538-545
• 
  Hongyu Li, Li Teng, Wenbin Chen, I-Fan Shen: Supervised Learning on Local Tangent Space. 546-551
• 
  Yali Zhao, Guangcheng Xi, Jianqiang Yi: Study Markov Neural Network by Stochastic Graph. 552-557
• 
  Nakjin Choi, Jun-Seok Lim, Koeng-Mo Sung: An Efficient Recursive Total Least Squares Algorithm for Training Multilayer Feedforward Neural Networks. 558-565
• 
  Lingyun Hu, Zengqi Sun: A Robust Learning Algorithm for Feedforward Neural Networks with Adaptive Spline Activation Function. 566-571
• 
  Fei Han, Deshuang Huang, Yiu-ming Cheung, Guang-Bin Huang: A New Modified Hybrid Learning Algorithm for Feedforward Neural Networks. 572-577
• 
  Jun-Seok Lim, Nakjin Choi, Koeng-Mo Sung: Robust Recursive TLS (Total Least Square) Method Using Regularized UDU Decomposed for FNN (Feedforward Neural Network) Training. 578-584
• 
  Jiancheng Lv, Zhang Yi: An Improved Backpropagation Algorithm Using Absolute Error Function. 585-590
• 
  Zhiyong Zhang, Jingang Liu, Zhongzhi Shi: An Improved Relative Criterion Using BP Algorithm. 591-596
• 
  Younggui Yoon, Jaewook Lee: Solving Hard Local Minima Problems Using Basin Cells for Multilayer Perceptron Training. 597-602
• 
  Kwang-Baek Kim, Sungshin Kim, Young Hoon Joo, Am Sok Oh: Enhanced Fuzzy Single Layer Perceptron. 603-608
• 
  Jie Yang, Wei Wu, Zhiqiong Shao: A New Training Algorithm for a Fuzzy Perceptron and Its Convergence. 609-614
• 
  Junping Wang, Quanshi Chen: Stochastic Fuzzy Neural Network and Its Robust Parameter Learning Algorithm. 615-620
• 
  Dongli Wang, Yang Gao, Pei Yang: Applying Neural Network to Reinforcement Learning in Continuous Spaces. 621-626
• 
  SeungGwan Lee: Multiagent Reinforcement Learning Algorithm Using Temporal Difference Error. 627-633
• 
  Jian Fan, Gengfeng Wu: A Foremost-Policy Reinforcement Learning Based ART2 Neural Network and Its Learning Algorithm. 634-639
• 
  Jianing Li, Jianqiang Yi, Dongbin Zhao, Guangcheng Xi: A Reinforcement Learning Based Radial-Bassis Function Network Control System. 640-645
• 
  Yang Yang, Bao-Liang Lu: Structure Pruning Strategies for Min-Max Modular Network. 646-651
• 
  Pan Wang, Zhun Fan, Youfeng Li, Shan Feng: Sequential Bayesian Learning for Modular Neural Networks. 652-659
• 
  Dong-Sun Kim, Hyunsik Kim, Duck-Jin Chung: A Modified Genetic Algorithm for Fast Training Neural Networks. 660-665
• 
  Xiuli Ma, Licheng Jiao: Immunity Clonal Synergetic Learning of Unbalanced Attention Parameters in Synergetic Network. 666-671
• 
  Yi He, Yuhui Qiu, Guangyuan Liu, Kaiyou Lei: Optimizing Weights of Neural Network Using an Adaptive Tabu Search Approach. 672-676
• 
  Ke Lu, Jidong Zhao, Mengqin Xia, Jiazhi Zeng: Semi-supervised Learning for Image Retrieval Using Support Vector Machines. 677-681
• 
  Lipo Wang, Xiuju Fu: A Simple Rule Extraction Method Using a Compact RBF Neural Network. 682-687
• 
  Li Xiao, Guangyuan Liu: Automatic Fuzzy Rule Extraction Based on Fuzzy Neural Network. 688-693

Optimization Methods

• 
  Changyin Sun, Chun-Bo Feng: Neural Networks for Nonconvex Nonlinear Programming Problems: A Switching Control Approach. 694-699
• 
  Weitao Sun, Jiwu Shu, Weimin Zheng: Deterministic Global Optimization with a Neighbourhood Determination Algorithm Based on Neural Networks. 700-705
• 
  Yongqing Yang, Jinde Cao, Daqi Zhu: A Neural Network Methodology of Quadratic Optimization with Quadratic Equality Constraints. 706-711
• 
  Zhiqing Meng, Chuangyin Dang: A Hopfiled Neural Network for Nonlinear Constrained Optimization Problems Based on Penalty Function. 712-717
• 
  Xuewen Mu, Sanyang Liu, Yaling Zhang: A Neural Network Algorithm for Second-Order Conic Programming. 718-724
• 
  Hong-Zhong Huang, Zhigang Tian: Application of Neural Network to Interactive Physical Programming. 725-730
• 
  Paulo Henrique Siqueira, Sérgio Scheer, Maria Teresinha Arns Steiner: Application of the "Winner Takes All" Principle in Wang's Recurrent Neural Network for the Assignment Problem. 731-738
• 
  Hong Qu, Zhang Yi, XiaoLin Xiang: Theoretical Analysis and Parameter Setting of Hopfield Neural Networks. 739-744
• 
  Xiuhong Wang, Qingli Qiao, Zhengqu Wang: Solving Optimization Problems Based on Chaotic Neural Network with Hysteretic Activation Function. 745-749
• 
  Shenshen Gu: An Improved Transiently Chaotic Neural Network for Solving the K-Coloring Problem. 750-755
• 
  Huali Sun, Jianying Xie, Yaofeng Xue: A Sweep-Based TCNN Algorithm for Capacity Vehicle Routing Problem. 756-761
• 
  Xinli Xu, Qiu Guan, Wanliang Wang, Shengyong Chen: Transient Chaotic Discrete Neural Network for Flexible Job-Shop Scheduling. 762-769
• 
  Fuqing Zhao, Yi Hong, Dongmei Yu, Xuhui Chen, Yahong Yang: Integration of Artificial Neural Networks and Genetic Algorithm for Job-Shop Scheduling Problem. 770-775
• 
  Xin Feng, Ho-fung Leung, Lixin Tang: An Effective Algorithm Based on GENET Neural Network Model for Job Shop Scheduling with Release Dates and Due Dates. 776-781
• 
  Yuan Xie, Jianying Xie, Jie Li: Fuzzy Due Dates Job Shop Scheduling Problem Based on Neural Network. 782-787
• 
  Lixin Tang, Yanyan Zhang: Heuristic Combined Artificial Neural Networks to Schedule Hybrid Flow Shop with Sequence Dependent Setup Times. 788-793
• 
  Yongyi Shou: A Neural Network Based Heuristic for Resource-Constrained Project Scheduling. 794-799
• 
  Ping Wang, Hong-Zhong Huang, Ming J. Zuo, Weidong Wu, Chunsheng Liu: Functional-Link Net Based Multiobjective Fuzzy Optimization. 800-804
• 
  Xianghui Liu, Jianping Yin, Zhiping Cai, Xicheng Lu, Shiming Chen: Optimizing the Distributed Network Monitoring Model with Bounded Bandwidth and Delay Constraints by Neural Networks. 805-810
• 
  Jinwu Gao, Yankui Liu: Stochastic Nash Equilibrium with a Numerical Solution Method. 811-816

Kernel Methods

• 
  Zhenzhou Chen, Lei Li: Generalized Foley-Sammon Transform with Kernels. 817-823
• 
  Hong-Jie Xing, Yujiu Yang, Yong Wang, Bao-Gang Hu: Sparse Kernel Fisher Discriminant Analysis. 824-830
• 
  Peter Williams, Sheng Li, Jianfeng Feng, Si Wu: Scaling the Kernel Function to Improve Performance of the Support Vector Machine. 831-836
• 
  Liangzhi Gan, Zonghai Sun, Youxian Sun: Online Support Vector Machines with Vectors Sieving Method. 837-842
• 
  Xiangjun Wen, Yunze Cai, Xiaoming Xu: Least Squares Support Vector Machine Based on Continuous Wavelet Kernel. 843-850
• 
  Liefeng Bo, Ling Wang, Licheng Jiao: Multiple Parameter Selection for LS-SVM Using Smooth Leave-One-Out Error. 851-856
• 
  Daewon Lee, Jaewook Lee: Trajectory-Based Support Vector Multicategory Classifier. 857-862
• 
  Jingqing Jiang, Chunguo Wu, Yanchun Liang: Multi-category Classification by Least Squares Support Vector Regression. 863-868
• 
  Zhifeng Hao, Bo Liu, Xiaowei Yang, Yanchun Liang, Feng Zhao: Twi-Map Support Vector Machine for Multi-classification Problems. 869-874
• 
  Jun Feng, Yang Yang, Jinsheng Fan: Fuzzy Multi-class SVM Classifier Based on Optimal Directed Acyclic Graph Using in Similar Handwritten Chinese Characters Recognition. 875-880
• 
  Yimin Wen, Bao-Liang Lu: A Hierarchical and Parallel Method for Training Support Vector Machines. 881-886
• 
  Kaian Wang, Hai Zhao, Bao-Liang Lu: Task Decomposition Using Geometric Relation for Min-Max Modular SVMs. 887-892
• 
  Shuyuan Yang, Min Wang, Licheng Jiao, Qing Li: A Novel Ridgelet Kernel Regression Method. 893-899
• 
  Jianhua Xu: Designing Nonlinear Classifiers Through Minimizing VC Dimension Bound. 900-905
• 
  Zejian Yuan, Nanning Zheng, Yuehu Liu: A Cascaded Mixture SVM Classifier for Object Detection. 906-912
• 
  Hongwei Liu, Hongtao Su, Zheng Bao: Radar High Range Resolution Profiles Feature Extraction Based on Kernel PCA and Kernel ICA. 913-918
• 
  Meiying Ye: Controlling Chaotic Systems via Support Vector Machines Without Analytical Model. 919-924
• 
  Fei Xing, Ping Guo: Support Vector Regression for Software Reliability Growth Modeling and Prediction. 925-930
• 
  Peng Fu, Deyun Zhang, Zhaofeng Ma, Hao Dong: SVM-Based Semantic Text Categorization for Large Scale Web Information Organization. 931-936
• 
  Zhousuo Zhang, Qiao Hu, Zhengjia He: Fuzzy Support Vector Machine and Its Application to Mechanical Condition Monitoring. 937-942

Component Analysis

• 
  Juan Manuel Górriz Sáez, Carlos García Puntonet, Angel Manuel Gómez, Oscar Pernía: Guided GA-ICA Algorithms. 943-948
• 
  Jian Cheng, Kongqiao Wang, Yen-Wei Chen: A Cascaded Ensemble Learning for Independent Component Analysis. 949-954
• 
  Dengpan Gao, Jinwen Ma, QianSheng Cheng: A Step by Step Optimization Approach to Independent Component Analysis. 955-960
• 
  Gang Wang, Xin Xu, Dewen Hu: Self-adaptive FastICA Based on Generalized Gaussian Model. 961-966
• 
  Zhilin Zhang, Zhang Yi: An Efficient Independent Component Analysis Algorithm for Sub-Gaussian Sources. 967-972
• 
  Jianzhao Qin, Yuanqing Li, Andrzej Cichocki: ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System. 973-978
• 
  Yi-qiong Xu, Bi-cheng Li, Bo Wang: Fast Independent Component Analysis for Face Feature Extraction. 979-984
• 
  Chengming Liu, Xuming Huang, LiMing Zhang: Affine Invariant Descriptors for Color Images Based on Independent Component Analysis. 985-990
• 
  Linhua Zhang, Shaojiang Deng, Xuebing Wang: A New Image Protection and Authentication Technique Based on ICA. 991-996
• 
  Tao Jiang, Xingzhou Jiang: Locally Spatiotemporal Saliency Representation: The Role of Independent Component Analysis. 997-1003
• 
  Dazheng Feng: A Multistage Decomposition Approach for Adaptive Principal Component Analysis. 1004-1009
• 
  Xiao-Long Zhu, Xian-Da Zhang, Ying Jia: A New Kalman Filtering Algorithm for Nonlinear Principal Component Analysis. 1010-1015
• 
  Vo Dinh Minh Nhat, Sungyoung Lee: An Improvement on PCA Algorithm for Face Recognition. 1016-1021
• 
  Tianqi Zhang, Xiaokang Lin, Zhengzhong Zhou, Aiping Mu: A Modified PCA Neural Network to Blind Estimation of the PN Sequence in Lower SNR DS-SS Signals. 1022-1027
• 
  Dezhong Peng, Zhang Yi, XiaoLin Xiang: A Modified MCA EXIN Algorithm and Its Convergence Analysis. 1028-1033
• 
  Mao Ye: Robust Beamforming by a Globally Convergent MCA Neural Network. 1034-1041

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