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ORCIDISNN 2006: Chengdu, China
- Jun Wang, Zhang Yi, Jacek M. Zurada, Bao-Liang Lu, Hujun Yin:
Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part I. Lecture Notes in Computer Science 3971, Springer 2006, ISBN 3-540-34439-X
Neurobiological Analysis
- Si Wu, Jianfeng Feng, Shun-ichi Amari:
The Ideal Noisy Environment for Fast Neural Computation. 1-6 - Xu-Dong Wang, Jiang Hao, Mu-Ming Poo, Xiaohui Zhang:
How Does a Neuron Perform Subtraction? Arithmetic Rules of Synaptic Integration of Excitation and Inhibition. 7-14 - Jun Liu, Jian Wu, Zhengguo Lou, Guang Li:
Stochastic Resonance Enhancing Detectability of Weak Signal by Neuronal Networks Model for Receiver. 15-20 - Huafu Chen, Ling Zeng, Dezhong Yao, Qing Gao:
A Gaussian Dynamic Convolution Models of the FMRI BOLD Response. 21-26 - Mingxiao Ding, Naigong Yu, Xiaogang Ruan:
Cooperative Motor Learning Model for Cerebellar Control of Balance and Locomotion. 27-33 - Toshihiko Matsuka:
A Model of Category Learning with Attention Augmented Simplistic Prototype Representation. 34-40 - Toshihiko Matsuka, Arieta Chouchourelou:
On the Learning Algorithms of Descriptive Models of High-Order Human Cognition. 41-49 - Rubin Wang, Jing Yu, Zhikang Zhang:
A Neural Model on Cognitive Process. 50-59
Theoretical Analysis
- Zongben Xu, Jianjun Wang, Deyu Meng:
Approximation Bound of Mixture Networks in Lomegap Spaces. 60-65 - Feng-Jun Li, Zongben Xu:
Integral Transform and Its Application to Neural Network Approximation. 66-71 - Chunmei Ding, Feilong Cao, Zongben Xu:
The Essential Approximation Order for Neural Networks with Trigonometric Hidden Layer Units. 72-79 - Yong Fang, Tommy W. S. Chow:
Wavelets Based Neural Network for Function Approximation. 80-85 - Alejandro Cruz Sandoval, Wen Yu:
Passivity Analysis of Dynamic Neural Networks with Different Time-Scales. 86-92 - Zhiguo Yang, Daoyi Xu, Yumei Huang:
Exponential Dissipativity of Non-autonomous Neural Networks with Distributed Delays and Reaction-Diffusion Terms. 93-99 - Min-Jae Kang, Ho-Chan Kim, Farrukh Aslam Khan
, Wang-Cheol Song, Jacek M. Zurada:
Convergence Analysis of Continuous-Time Neural Networks. 100-108 - Weirui Zhao, Huanshui Zhang:
Global Convergence of Continuous-Time Recurrent Neural Networks with Delays. 109-114 - Xiaoxin Liao, Zhigang Zeng:
Global Exponential Stability in Lagrange Sense of Continuous-Time Recurrent Neural Networks. 115-121 - Yi Shen, Meiqin Liu, Xiaodong Xu:
Global Exponential Stability of Recurrent Neural Networks with Time-Varying Delay. 122-128 - Gang Wang, Huaguang Zhang, Chonghui Song:
New Criteria of Global Exponential Stability for a Class of Generalized Neural Networks with Time-Varying Delays. 129-134 - Changyin Sun, Linfeng Li:
Dynamics of General Neural Networks with Distributed Delays. 135-140 - Shuyong Li, Yumei Huang, Daoyi Xu:
On Equilibrium and Stability of a Class of Neural Networks with Mixed Delays. 141-146 - Hanlin He, Xiaoxin Liao:
Stability Analysis of Neutral Neural Networks with Time Delay. 147-152 - Jianlong Qiu, Jinde Cao:
Global Asymptotical Stability in Neutral-Type Delayed Neural Networks with Reaction-Diffusion Terms. 153-158 - Wudai Liao, Zhongsheng Wang, Xiaoxin Liao:
Almost Sure Exponential Stability on Interval Stochastic Neural Networks with Time-Varying Delays. 159-164 - Xuyang Lou, Baotong Cui:
Stochastic Robust Stability of Markovian Jump Nonlinear Uncertain Neural Networks with Wiener Process. 165-171 - Li Xie, Tianming Liu, Guodong Lu, Jilin Liu, Stephen T. C. Wong:
Stochastic Robust Stability Analysis for Markovian Jump Discrete-Time Delayed Neural Networks with Multiplicative Nonlinear Perturbations. 172-178 - Jun Xu, Daoying Pi, Yong-Yan Cao:
Global Robust Stability of General Recurrent Neural Networks with Time-Varying Delays. 179-184 - Yongqing Yang:
Robust Periodicity in Recurrent Neural Network with Time Delays and Impulses. 185-191 - Tianping Chen, Wenlian Lu:
Global Asymptotical Stability of Cohen-Grossberg Neural Networks with Time-Varying and Distributed Delays. 192-197 - Ce Ji, Huaguang Zhang, Chonghui Song:
LMI Approach to Robust Stability Analysis of Cohen-Grossberg Neural Networks with Multiple Delays. 198-203 - Tianping Chen, Lili Wang, Changlei Ren:
Existence and Global Stability Analysis of Almost Periodic Solutions for Cohen- Grossberg Neural Networks. 204-210 - Li-qun Zhou, Guang-Da Hu:
A New Sufficient Condition on the Complete Stability of a Class Cellular Neural Networks. 211-216 - Weifan Zheng, Jiye Zhang, Weihua Zhang:
Stability Analysis of Reaction-Diffusion Recurrent Cellular Neural Networks with Variable Time Delays. 217-223 - Wudai Liao, Yulin Xu, Xiaoxin Liao:
Exponential Stability of Delayed Stochastic Cellular Neural Networks. 224-229 - Chaojin Fu, Boshan Chen:
Global Exponential Stability of Cellular Neural Networks with Time-Varying Delays and Impulses. 230-235 - Jiye Zhang, Dianbo Ren, Weihua Zhang:
Global Exponential Stability of Fuzzy Cellular Neural Networks with Variable Delays. 236-242 - Tingwen Huang, Marco Roque-Sol:
Stability of Fuzzy Cellular Neural Networks with Impulses. 243-248 - Xiaoxin Liao, Fei Xu, Pei Yu:
Absolute Stability of Hopfield Neural Network. 249-254 - Bingji Xu, Qun Wang:
Robust Stability Analysis of Uncertain Hopfield Neural Networks with Markov Switching. 255-260 - Wei Zhu, Daoyi Xu:
Asymptotic Stability of Second-Order Discrete-Time Hopfield Neural Networks with Variable Delays. 261-266 - Shengrui Zhang, Runnian Ma:
Convergence Analysis of Discrete Delayed Hopfield Neural Networks. 267-272 - Minghui Jiang, Yi Shen, Xiaoxin Liao:
An LMI-Based Approach to the Global Stability of Bidirectional Associative Memory Neural Networks with Variable Delay. 273-278 - Hui Wang, Xiaofeng Liao, Chuandong Li, Degang Yang:
Existence of Periodic Solution of BAM Neural Network with Delay and Impulse. 279-284 - Min Xiao, Jinde Cao:
On Control of Hopf Bifurcation in BAM Neural Network with Delayed Self-feedback. 285-290 - Hong Qu, Zhang Yi:
Convergence and Periodicity of Solutions for a Class of Discrete-Time Recurrent Neural Network with Two Neurons. 291-296 - Wentong Liao, Linshan Wang:
Existence and Global Attractability of Almost Periodic Solution for Competitive Neural Networks with Time-Varying Delays and Different Time Scales. 297-302 - Jin Zhou, Tianping Chen, Lan Xiang, Meichun Liu:
Global Synchronization of Impulsive Coupled Delayed Neural Networks. 303-308 - Ping Li:
Synchronization of a Class of Coupled Discrete Recurrent Neural Networks with Time Delay. 309-315 - Yan Huang, Xiao-Song Yang:
Chaos and Bifurcation in a New Class of Simple Hopfield Neural Network. 316-321 - Hongwei Wang, Hong Gu:
Synchronization of Chaotic System with the Perturbation Via Orthogonal Function Neural Network. 322-327 - Haigeng Luo, Xiaodong Xu, Xiaoxin Liao:
Numerical Analysis of a Chaotic Delay Recurrent Neural Network with Four Neurons. 328-333 - Guang-Hong Wang, Ping Jiang:
Autapse Modulated Bursting. 334-343
Neurodynamic Optimization
- Guocheng Li, Shiji Song, Cheng Wu, Zifang Du:
A Neural Network Model for Non-smooth Optimization over a Compact Convex Subset. 344-349 - Shiji Song, Guocheng Li, Xiaohong Guan:
Differential Inclusions-Based Neural Networks for Nonsmooth Convex Optimization on a Closed Convex Subset. 350-358 - Fuye Feng, Yong Xia, Quanju Zhang:
A Recurrent Neural Network for Linear Fractional Programming with Bound Constraints. 359-368 - Qingshan Liu, Jun Wang, Jinde Cao:
A Delayed Lagrangian Network for Solving Quadratic Programming Problems with Equality Constraints. 369-378 - Yao-Qun Xu, Ming Sun, Guangren Duan:
Wavelet Chaotic Neural Networks and Their Application to Optimization Problems. 379-384 - Ling Qin, Yixin Chen, Ling Chen, Yuan Yao:
A New Optimization Algorithm Based on Ant Colony System with Density Control Strategy. 385-390 - Paulo Henrique Siqueira, Sérgio Scheer, Maria Teresinha Arns Steiner:
A New Neural Network Approach to the Traveling Salesman Problem. 391-398 - Lijun Liu, Wei Wu:
Dynamical System for Computing Largest Generalized Eigenvalue. 399-404 - Yiguang Liu, Zhisheng You:
A Concise Functional Neural Network for Computing the Extremum Eigenpairs of Real Symmetric Matrices. 405-413
Learning Algorithms
- Frank Emmert-Streib:
A Novel Stochastic Learning Rule for Neural Networks. 414-423 - Deepak Mishra, Abhishek Yadav, Prem Kumar Kalra:
Learning with Single Quadratic Integrate-and-Fire Neuron. 424-429 - Hongyu Li, I-Fan Shen:
Manifold Learning of Vector Fields. 430-435 - Hongyu Li, I-Fan Shen:
Similarity Measure for Vector Field Learning. 436-441 - Jinwen Ma, Bin Cao:
The Mahalanobis Distance Based Rival Penalized Competitive Learning Algorithm. 442-447 - Seongwon Cho, Jaemin Kim, Sun-Tae Chung:
Dynamic Competitive Learning. 448-455 - Jinwuk Seok, Seongwon Cho, Jaemin Kim:
Hyperbolic Quotient Feature Map for Competitive Learning Neural Networks. 456-463 - Zhiwu Lu, Jinwen Ma:
A Gradient Entropy Regularized Likelihood Learning Algorithm on Gaussian Mixture with Automatic Model Selection. 464-469 - Ah-Hwee Tan:
Self-organizing Neural Architecture for Reinforcement Learning. 470-475 - SeungGwan Lee:
On the Efficient Implementation Biologic Reinforcement Learning Using Eligibility Traces. 476-481 - Lianwei Zhao, Siwei Luo, Mei Tian, Chao Shao, Hongliang Ma:
Combining Label Information and Neighborhood Graph for Semi-supervised Learning. 482-488 - Liang Liu, Naigong Yu, Mingxiao Ding, Xiaogang Ruan:
A Cerebellar Feedback Error Learning Scheme Based on Kalman Estimator for Tracing in Dynamic System. 489-495 - Lei Guo, Hong Wang:
An Optimal Iterative Learning Scheme for Dynamic Neural Network Modelling. 496-501 - Toshinori Deguchi, Naohiro Ishii:
Delayed Learning on Internal Memory Network and Organizing Internal States. 502-508 - Huawei Chen, Fan Jin:
A Novel Learning Algorithm for Feedforward Neural Networks. 509-514 - He-Sheng Tang, Song-Tao Xue, Rong Chen:
On Hinfinity Filtering in Feedforward Neural Networks Training and Pruning. 515-523 - Jinhua Xu, Daniel W. C. Ho:
A Node Pruning Algorithm Based on Optimal Brain Surgeon for Feedforward Neural Networks. 524-529 - Eu Jin Teoh, Cheng Xiang, Kay Chen Tan:
A Fast Learning Algorithm Based on Layered Hessian Approximations and the Pseudoinverse. 530-536 - Hai Zhao, Bao-Liang Lu:
A Modular Reduction Method for k-NN Algorithm with Self-recombination Learning. 537-544 - Haixia Chen, Senmiao Yuan, Kai Jiang:
Selective Neural Network Ensemble Based on Clustering. 545-550 - Songsong Li, Toshimi Okada, Xiaoming Chen, Zheng Tang:
An Individual Adaptive Gain Parameter Backpropagation Algorithm for Complex-Valued Neural Networks. 551-557 - Marco A. Moreno-Armendáriz, Giovanni Egidio Pazienza, Wen Yu:
Training Cellular Neural Networks with Stable Learning Algorithm. 558-563 - Yangmin Li, Xin Chen:
A New Stochastic PSO Technique for Neural Network Training. 564-569 - Ben Niu, Yunlong Zhu, Xiaoxian He:
A Multi-population Cooperative Particle Swarm Optimizer for Neural Network Training. 570-576 - Haichang Gao, Boqin Feng, Yun Hou, Li Zhu:
Training RBF Neural Network with Hybrid Particle Swarm Optimization. 577-583 - Ming-Jung Seow, Vijayan K. Asari:
Robust Learning by Self-organization of Nonlinear Lines of Attractions. 584-589 - Kai Zhang, Gen-Zhi Guan, Fang-Fang Chen, Lin Zhang, Zhi-Ye Du:
Improved Learning Algorithm Based on Generalized SOM for Dynamic Non-linear System. 590-598 - Kao-Shing Hwang, Yu-Jen Chen, Tzung-Feng Lin:
Q-Learning with FCMAC in Multi-agent Cooperation. 599-606 - Xuesong Wang, Yuhu Cheng, Wei Sun:
Q Learning Based on Self-organizing Fuzzy Radial Basis Function Network. 607-615 - Haisheng Lin, Xiao Zhi Gao, Xianlin Huang, Zhuoyue Song:
A Fuzzy Neural Networks with Structure Learning. 616-622 - Mariela Cerrada, José Aguilar, André Titli:
Reinforcement Learning-Based Tuning Algorithm Applied to Fuzzy Identification. 623-630 - Fei Han, Tat-Ming Lok, Michael R. Lyu:
A New Learning Algorithm for Function Approximation Incorporating A Priori Information into Extreme Learning Machine. 631-636 - Jun-Seok Lim, Koeng-Mo Sung, Joonil Song:
Robust Recursive Complex Extreme Learning Machine Algorithm for Finite Numerical Precision. 637-643 - You Xu, Yang Shu:
Evolutionary Extreme Learning Machine - Based on Particle Swarm Optimization. 644-652 - You Xu:
A Gradient-Based ELM Algorithm in Regressing Multi-variable Functions. 653-658 - Jaehun Lee, Wooyong Chung, Euntai Kim:
A New Genetic Approach to Structure Learning of Bayesian Networks. 659-668
Model Design
- Shoujue Wang, Singsing Liu, Wenming Cao:
Research on Multi-Degree-of-Freedom Neurons with Weighted Graphs. 669-675 - Hong Yue, Aurelie J. A. Leprand, Hong Wang:
Output PDF Shaping of Singular Weights System: Monotonical Performance Design. 676-682 - Yi Shen, Meiqin Liu, Xiaodong Xu:
Stochastic Time-Varying Competitive Neural Network Systems. 683-688 - Dong-Chul Park, Duc-Hoai Nguyen, Song-Jae Lee, Yunsik Lee:
Heterogeneous Centroid Neural Networks. 689-694 - Shuzhong Yang, Siwei Luo, Jianyu Li:
Building Multi-layer Small World Neural Network. 695-700 - Stones Lei Zhang, Zhang Yi, Jiancheng Lv:
Growing Hierarchical Principal Components Analysis Self-Organizing Map. 701-706 - Andrey Gavrilov, Young-Koo Lee, Sungyoung Lee:
Hybrid Neural Network Model Based on Multi-layer Perceptron and Adaptive Resonance Theory. 707-713 - Yan-Peng Liu, Ming-Guang Wu, Ji-Xin Qian:
Evolving Neural Networks Using the Hybrid of Ant Colony Optimization and BP Algorithms. 714-722 - Dong-Sun Kim, Hyunsik Kim, Duck-Jin Chung:
A Genetic Algorithm with Modified Tournament Selection and Efficient Deterministic Mutation for Evolving Neural Network. 723-731 - Yunhui Liu, Siwei Luo, Ziang Lv, Hua Huang:
A Neural Network Structure Evolution Algorithm Based on e, m Projections and Model Selection Criterion. 732-738 - Zhuhong Zhang, Xin Tu, Chang-Gen Peng:
A Parallel Coevolutionary Immune Neural Network and Its Application to Signal Simulation. 739-746 - Ji-Xiang Du, Chuan-Min Zhai, Zengfu Wang, Guo-Jun Zhang:
A Novel Elliptical Basis Function Neural Networks Optimized by Particle Swarm Optimization. 747-751 - Ming Ma, Libiao Zhang, Jie Ma, Chunguang Zhou:
Fuzzy Neural Network Optimization by a Particle Swarm Optimization Algorithm. 752-761 - Sumitra Mukhopadhyay, Ajit K. Mandal:
Fuzzy Rule Extraction Using Robust Particle Swarm Optimization. 762-767 - Seok-Beom Roh, Sung-Kwun Oh, Tae-Chon Ahn:
A New Design Methodology of Fuzzy Set-Based Polynomial Neural Networks with Symbolic Gene Type Genetic Algorithms. 768-773 - Sung-Kwun Oh, In-Tae Lee, Jeoung-Nae Choi:
Design of Fuzzy Polynomial Neural Networks with the Aid of Genetic Fuzzy Granulation and Its Application to Multi-variable Process System. 774-779 - Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn:
A Novel Self-Organizing Fuzzy Polynomial Neural Networks with Evolutionary FPNs: Design and Analysis. 780-785 - Sung-Kwun Oh, Byoung-Jun Park, Witold Pedrycz:
Design of Fuzzy Neural Networks Based on Genetic Fuzzy Granulation and Regression Polynomial Fuzzy Inference. 786-791 - Lei Zhang, Guoyou Wang, Wentao Wang:
A New Fuzzy ART Neural Network Based on Dual Competition and Resonance Technique. 792-797 - Chang-Wook Han, Jung-Il Park:
Simulated Annealing Based Learning Approach for the Design of Cascade Architectures of Fuzzy Neural Networks. 798-803 - Huaguang Zhang, Yanhong Luo, Derong Liu:
A New Fuzzy Identification Method Based on Adaptive Critic Designs. 804-809 - Wei-Hong Xu, Guo-Ping Chen, Zhong-Ke Xie:
Impacts of Perturbations of Training Patterns on Two Fuzzy Associative Memories Based on T-Norms. 810-817 - Cornelio Yáñez-Márquez, Luis Pastor Sánchez Fernández, Itzamá López-Yáñez:
Alpha-Beta Associative Memories for Gray Level Patterns. 818-823 - Zhigang Zeng, Jun Wang:
Associative Memories Based on Discrete-Time Cellular Neural Networks with One-Dimensional Space-Invariant Templates. 824-829 - Roy Kwang Yang Chang, Chu Kiong Loo, Machavaram Venkata Chalapathy Rao:
Autonomous and Deterministic Probabilistic Neural Network Using Global k-Means. 830-836 - Marija Bacauskiene, Vladas Cibulskis, Antanas Verikas:
Selecting Variables for Neural Network Committees. 837-842 - Qingyu Xiong, Jian Huang, Xiaodong Xian, Qian Xiao:
An Adaptive Network Topology for Classification. 843-848 - Emad A. M. Andrews Shenouda:
A Quantitative Comparison of Different MLP Activation Functions in Classification. 849-857 - Eu Jin Teoh, Cheng Xiang, Kay Chen Tan:
Estimating the Number of Hidden Neurons in a Feedforward Network Using the Singular Value Decomposition. 858-865 - Jiang Zhong, Chunxiao Ye, Yong Feng, Ying Zhou, Zhongfu Wu:
Neuron Selection for RBF Neural Network Classifier Based on Multiple Granularities Immune Network. 866-872 - Yuehui Chen, Lizhi Peng, Ajith Abraham:
Hierarchical Radial Basis Function Neural Networks for Classification Problems. 873-879 - Fang Liu, Jian-Zhong Zhou, Fangpeng Qiu, Junjie Yang:
Biased Wavelet Neural Network and Its Application to Streamflow Forecast. 880-888 - Yanlai Li, Kuanquan Wang, Tao Li:
A Goal Programming Based Approach for Hidden Targets in Layer-by-Layer Algorithm of Multilayer Perceptron Classifiers. 889-894 - Zhou Yang, Wenjie Zhu, Liang Ji:
SLIT: Designing Complexity Penalty for Classification and Regression Trees Using the SRM Principle. 895-902 - Haijun Li, Zheng-Xuan Wang, Limin Wang, Senmiao Yuan:
Flexible Neural Tree for Pattern Recognition. 903-908 - Lei Wang, Yinling Nie, Weike Nie, Licheng Jiao:
A Novel Model of Artificial Immune Network and Simulations on Its Dynamics. 909-914
Kernel Methods
- Bo Chen, Hongwei Liu, Zheng Bao:
A Kernel Optimization Method Based on the Localized Kernel Fisher Criterion. 915-921 - Bo Jin, Yan-Qing Zhang:
Genetic Granular Kernel Methods for Cyclooxygenase-2 Inhibitor Activity Comparison. 922-927 - Luoqing Li, Chenggao Wan:
Support Vector Machines with Beta-Mixing Input Sequences. 928-935 - Fangfang Wu, Yinliang Zhao:
Least Squares Support Vector Machine on Gaussian Wavelet Kernel Function Set. 936-941 - Huihong Jin, Zhiqing Meng, Xuanxi Ning:
A Smoothing Multiple Support Vector Machine Model. 942-948 - Hongbing Liu, Shengwu Xiong, Xiaoxiao Niu:
Fuzzy Support Vector Machines Based on Spherical Regions. 949-954 - Marek Bundzel, Tomás Kasanický, Baltazár Frankovic:
Building Support Vector Machine Alternative Using Algorithms of Computational Geometry. 955-961 - Shengfeng Tian, Shaomin Mu, Chuanhuan Yin:
Cooperative Clustering for Training SVMs. 962-967 - Xiaohong Wang, Sitao Wu, Xiaoru Wang, Qunzhan Li:
SVMV - A Novel Algorithm for the Visualization of SVM Classification Results. 968-973 - Genting Yan, Guangfu Ma, Liangkuan Zhu:
Support Vector Machines Ensemble Based on Fuzzy Integral for Classification. 974-980 - Shu Yu, Xiaowei Yang, Zhifeng Hao, Yanchun Liang:
An Adaptive Support Vector Machine Learning Algorithm for Large Classification Problem. 981-990 - Woo-Sung Kang, Ki Hong Im, Jin Young Choi:
SVDD-Based Method for Fast Training of Multi-class Support Vector Classifier. 991-996 - Bo Liu, Xiaowei Yang, Zhifeng Hao:
Binary Tree Support Vector Machine Based on Kernel Fisher Discriminant for Multi-classification. 997-1003 - Jianhua Xu:
A Fast and Sparse Implementation of Multiclass Kernel Perceptron Algorithm. 1004-1009 - Jingqing Jiang, Chuyi Song, Chunguo Wu, Yanchun Liang, Xiaowei Yang, Zhifeng Hao:
Mutual Conversion of Regression and Classification Based on Least Squares Support Vector Machines. 1010-1015 - Liangzhi Gan, Hai-kuan Liu, Youxian Sun:
Sparse Least Squares Support Vector Machine for Function Estimation. 1016-1021 - Feng-Qing Han, Da-Cheng Wang, Chuan-Dong Li, Xiao-Feng Liao:
A Multiresolution Wavelet Kernel for Support Vector Regression. 1022-1029 - Zhen Yang, Jun Guo, Weiran Xu, Xiangfei Nie, Jian Wang, Jianjun Lei:
Multi-scale Support Vector Machine for Regression Estimation. 1030-1037 - Dong-Chul Park, Chung-Nguyen Tran, Sancho Park:
Gradient Based Fuzzy C-Means Algorithm with a Mercer Kernel. 1038-1043 - Yunwei Pu, Ming Zhu, Weidong Jin, Laizhao Hu:
An Efficient Similarity-Based Validity Index for Kernel Clustering Algorithm. 1044-1049 - En-Hui Zheng, Min Yang, Ping Li, Zhi-Huan Song:
Fuzzy Support Vector Clustering. 1050-1056 - Chengbo Wang, Chengan Guo:
An SVM Classification Algorithm with Error Correction Ability Applied to Face Recognition. 1057-1062 - Zejian Yuan, Lei Yang, Yanyun Qu, Yuehu Liu, Xinchun Jia:
A Boosting SVM Chain Learning for Visual Information Retrieval. 1063-1069 - Bo Wu, Liangpei Zhang, Pingxiang Li, Jinmu Zhang:
Nonlinear Estimation of Hyperspectral Mixture Pixel Proportion Based on Kernel Orthogonal Subspace Projection. 1070-1075 - Li Sun, Ling Jing, Xiaodong Xia:
A New Proximal Support Vector Machine for Semi-supervised Classification. 1076-1082 - Liefeng Bo, Ling Wang, Licheng Jiao:
Sparse Gaussian Processes Using Backward Elimination. 1083-1088 - Xunkai Wei, Ying-Hong Li, Yue Feng:
Comparative Study of Extreme Learning Machine and Support Vector Machine. 1089-1095
ICA and BSS
- Woong Myung Kim, Chan-Ho Park, Hyon-Soo Lee:
Multi-level Independent Component Analysis. 1096-1102 - Tao Yu, Huai-Zong Shao, Qi-Cong Peng:
An ICA Learning Algorithm Utilizing Geodesic Approach. 1103-1108 - Gang Wang, Nini Rao, Zhi-Lin Zhang, Quanyi Mo, Pu Wang:
An Extended Online Fast-ICA Algorithm. 1109-1114 - Shangming Yang:
Gradient Algorithm for Nonnegative Independent Component Analysis. 1115-1120 - Fasong Wang, Hongwei Li, Rui Li, Shaoquan Yu:
Unified Parametric and Non-parametric ICA Algorithm for Arbitrary Sources. 1121-1126 - Xiao-fei Shi, Jidong Suo, Chang Liu, Li Li:
A Novel Kurtosis-Dependent Parameterized Independent Component Analysis Algorithm. 1127-1132 - Gang Wang, Xin Xu, Dewen Hu:
Local Stability Analysis of Maximum Nongaussianity Estimation in Independent Component Analysis. 1133-1139 - Mao Ye, Xue Li, Chengfu Yang, Zengan Gao:
Convergence Analysis of a Discrete-Time Single-Unit Gradient ICA Algorithm. 1140-1146 - Ji-Min Ye, Shun-Tian Lou, Hai-Hong Jin, Xian-Da Zhang:
An Novel Algorithm for Blind Source Separation with Unknown Sources Number. 1147-1152 - Gaoming Huang, Luxi Yang, Zhenya He:
Blind Source Separation Based on Generalized Variance. 1153-1158 - Junying Zhang, Hongyi Zhang, Le Wei, Yue Joseph Wang:
Blind Source Separation with Pattern Expression NMF. 1159-1164 - Chun-Hou Zheng, Zhi-Kai Huang, Michael R. Lyu, Tat-Ming Lok:
Nonlinear Blind Source Separation Using Hybrid Neural Networks. 1165-1170 - Xiaolu Li, Zhaoshui He:
Identification of Mixing Matrix in Blind Source Separation. 1171-1176 - Wenqiang Guo, Tianshuang Qiu, Yuzhang Zhao, Daifeng Zha:
Identification of Independent Components Based on Borel Measure for Under-Determined Mixtures. 1177-1182 - Ronghua Li, Ming Xiao:
Estimation of Delays and Attenuations for Underdetermined BSS in Frequency Domain. 1183-1188 - Gaoming Huang, Yang Gao, Luxi Yang, Zhenya He:
Application of Blind Source Separation to Five-Element Cross Array Passive Location. 1189-1194 - Hua Zhang, Da-Zheng Feng:
Convolutive Blind Separation of Non-white Broadband Signals Based on a Double-Iteration Method. 1195-1201 - Bin Xia, Liqing Zhang:
Multichannel Blind Deconvolution Using a Novel Filter Decomposition Method. 1202-1207 - Feng Jiang, Liqing Zhang, Bin Xia:
Two-Stage Blind Deconvolution for V-BLAST OFDM System. 1208-1213
Data Preprocessing
- Xuelei Hu, Lei Xu:
A Comparative Study on Selection of Cluster Number and Local Subspace Dimension in the Mixture PCA Models. 1214-1221 - Ping Ling, Chunguang Zhou:
Adaptive Support Vector Clustering for Multi-relational Data Mining. 1222-1230 - XuLei Yang, Qing Song, Meng Joo Er:
Robust Data Clustering in Mercer Kernel-Induced Feature Space. 1231-1237 - Hyun-Chul Kim, Jaewook Lee:
Pseudo-density Estimation for Clustering with Gaussian Processes. 1238-1243 - Lin Wang, Minghu Jiang, Yinghua Lu, Frank Noé, Jeremy C. Smith:
Clustering Analysis of Competitive Learning Network for Molecular Data. 1244-1249 - Lin Wang, Minghu Jiang, Yinghua Lu, Frank Noé, Jeremy C. Smith:
Self-Organizing Map Clustering Analysis for Molecular Data. 1250-1255 - Mao-ting Gao, Zheng-ou Wang:
A Conscientious Rival Penalized Competitive Learning Text Clustering Algorithm. 1256-1260 - Kin Keung Lai, Lean Yu, Ligang Zhou, Shouyang Wang:
Self-Organizing-Map-Based Metamodeling for Massive Text Data Exploration. 1261-1266 - Jiabing Wang, Hong Peng, Jing-Song Hu, Jun Zhang:
Ensemble Learning for Keyphrases Extraction from Scientific Document. 1267-1272 - Yugang Fan, Ping Li, Zhi-Huan Song:
Grid-Based Fuzzy Support Vector Data Description. 1273-1279 - Yang Weon Lee:
Development of the Hopfield Neural Scheme for Data Association in Multi-target Tracking. 1280-1285 - Dong Sun, Yong Deng:
Determine Discounting Coefficient in Data Fusion Based on Fuzzy ART Neural Network. 1286-1292 - Junlin Zhou, Yan Fu:
Scientific Data Lossless Compression Using Fast Neural Network. 1293-1298 - Xiu-Rong Zhao, Qing He, Zhongzhi Shi:
HyperSurface Classifiers Ensemble for High Dimensional Data Sets. 1299-1304 - Jen-Cheng Chen, Jia-Sheng Heh, Maiga Chang:
Designing a Decompositional Rule Extraction Algorithm for Neural Networks. 1305-1311 - Qutang Cai, Changshui Zhang:
Estimating Fractal Intrinsic Dimension from the Neighborhood. 1312-1318 - Junying Chen, Zheng Qin:
Dimensionality Reduction for Evolving RBF Networks with Particle Swarms. 1319-1325 - Heyong Wang, Jie Zheng, Zheng-an Yao, Lei Li:
Improved Locally Linear Embedding Through New Distance Computing. 1326-1333 - Dongyue Chen, Liming Zhang:
An Incremental Linear Discriminant Analysis Using Fixed Point Method. 1334-1339 - Jun-Seok Lim, Joonil Song, Yonggook Pyeon:
A Prewhitening RLS Projection Alternated Subspace Tracking (PAST) Algorithm. 1340-1345 - Junping Zhang, Chao Shen, Jufu Feng:
Classification with the Hybrid of Manifold Learning and Gabor Wavelet. 1346-1351 - Xizhao Wang, Hui Zhang:
A Novel Input Stochastic Sensitivity Definition of Radial Basis Function Neural Networks and Its Application to Feature Selection. 1352-1358 - Mohammed Attik:
Using Ensemble Feature Selection Approach in Selecting Subset with Relevant Features. 1359-1366 - Yan Wu, Yang Yang:
A New Method for Feature Selection. 1367-1372 - Zongxia Xie, Qinghua Hu, Daren Yu:
Improved Feature Selection Algorithm Based on SVM and Correlation. 1373-1380 - Ziqiang Wang, Dexian Zhang:
Feature Selection in Text Classification Via SVM and LSI. 1381-1386 - Qijun Zhao, Hongtao Lu, David Zhang:
Parsimonious Feature Extraction Based on Genetic Algorithms and Support Vector Machines. 1387-1393 - Hui Zhang, Tu Bao Ho, Mao Song Lin, Xuefeng Liang:
Feature Extraction for Time Series Classification Using Discriminating Wavelet Coefficients. 1394-1399 - Gang Liu, Xihai Li, Daizhi Liu, Wei-Gang Zhai:
Feature Extraction of Underground Nuclear Explosions Based on NMF and KNMF. 1400-1405 - Feng Zhu, Yafeng Hu, Xianda Zhang, Deguang Xie:
Hidden Markov Model Networks for Multiaspect Discriminative Features Extraction from Radar Targets. 1406-1411 - Dong-hong Liu, Zhi-jie Chen, Wen-long Hu, Yong-shun Zhang:
Application of Self-organizing Feature Neural Network for Target Feature Extraction. 1412-1420 - Shi-Fei Ding, Zhong-Zhi Shi:
Divergence-Based Supervised Information Feature Compression Algorithm. 1421-1426
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