## Neural Information Processing: 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 ProceedingsNikil R. Pal, Nikola Kasabov, Rajani K. Mudi, Srimanta Pal, Swapan K. Parui Springer, 2004年10月29日 - 1369 頁 It is our great pleasure to welcome you to the 11th International Conference on Neural Information Processing (ICONIP 2004) to be held in Calcutta. ICONIP 2004 is organized jointly by the Indian Statistical Institute (ISI) and Jadavpur University (JU). We are con?dent that ICONIP 2004, like the previous conf- ences in this series,will providea forum for fruitful interactionandthe exchange of ideas between the participants coming from all parts of the globe. ICONIP 2004 covers all major facets of computational intelligence, but, of course, with a primary emphasis on neural networks. We are sure that this meeting will be enjoyable academically and otherwise. We are thankful to the track chairs and the reviewers for extending their support in various forms to make a sound technical program. Except for a few cases, where we could get only two review reports, each submitted paper was reviewed by at least three referees, and in some cases the revised versions were againcheckedbythereferees. Wehad470submissionsanditwasnotaneasytask for us to select papers for a four-day conference. Because of the limited duration of the conference, based on the review reports we selected only about 40% of the contributed papers. Consequently, it is possible that some good papers are left out. We again express our sincere thanks to all referees for accomplishing a great job. In addition to 186 contributed papers, the proceedings includes two plenary presentations, four invited talks and 18 papers in four special sessions. The proceedings is organized into 26 coherent topical groups. |

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### 內容

1 | |

19 | |

37 | |

50 | |

78 | |

84 | |

90 | |

104 | |

Pattern Recognition | 738 |

Web Documents Categorization Using Neural Networks | 758 |

Clustering of IntervalValued Data | 775 |

A Long Memory Process Based Parametric Modeling and Recognition | 787 |

Time Series Classification | 800 |

Recognition of Bangla Handwritten Characters | 814 |

Automated Classification of Industry and Occupation Codes | 827 |

Fault Diagnosis for Industrial Images | 842 |

110 | |

ModeUtilizing Developmental Learning | 116 |

Dynamics of ComplexValued Neural Networks | 122 |

Two Models for Theta Precession Generation Using the Complex Version | 130 |

Selforganizing Maps | 136 |

An Empirical Study on the Robustness of SOM in Preserving Topology | 142 |

Extending the SOM Algorithm to NonEuclidean Distances | 150 |

An Efficient TwoLevel SOMART Document Clustering | 158 |

Using SOMBased Data Binning | 172 |

Closest Substring Problem Results from an Evolutionary Algorithm | 205 |

Multiobjective Genetic Search for Spanning Tree Problem | 218 |

Evolutionary Learning Programs Behavior in Neural Networks | 236 |

A New PID Tuning Technique Using Differential Evolution | 254 |

Neural Network ClosedLoop Control | 269 |

Cognitive Science | 282 |

Cognitive Process of Emotion Under Uncertainty | 300 |

Cerebral Activation Areas with Respect to Word and Sentence Production | 316 |

Neuroinformatics | 326 |

A HardwareDirected Face Recognition System | 327 |

The Teager Energy Based Features for Identification of Identical Twins | 333 |

User Enrollment Using Multiple Snapshots of Fingerprint | 344 |

Signature Verification Using Static and Dynamic Features | 350 |

Face Recognition Using SVM Combined with CNN for Face Detection | 356 |

Face Recognition Using Weighted Modular | 362 |

Adaptive Intelligent Systems | 368 |

Invehicle Noise and Enhanced Speech Intelligibility | 375 |

An Evolving Neural Network Model for Person Verification | 381 |

Pulsed Paraneural Networks PPNN Based on MEXOR Logic | 399 |

Universal SpikeTrain Processor for a HighSpeed Simulation | 416 |

Predictive Approaches for Sparse Model Learning | 434 |

A Process of Differentiation in the Assembly Neural Network | 452 |

Managing Interference Between Prior and Later Learning | 458 |

Adaptive Learning in Incremental Learning RBF Networks | 471 |

Incremental Learning and Dimension Selection Through Sleep | 489 |

An OnLine Learning Algorithm with Dimension Selection | 502 |

Improving kNN Based Text Classification | 516 |

TeacherDirected Learning with Gaussian | 530 |

Variational Information Maximization for Neural Coding | 543 |

Comparison of TDLeafλ and TDλ Learning | 549 |

Gaussian Process Regression with Fluid Hyperpriors | 567 |

A ForwardPropagation Rule for Acquiring Neural Inverse Models | 585 |

A Neighbor Generation Mechanism Optimizing Neural Networks | 613 |

TWRBF Transductive RBF Neural Network | 633 |

An Incremental Neural Network | 641 |

Image Processing | 659 |

RealTime Gaze Detection via Neural Network | 673 |

SizeIndependent Image Segmentation by Hierarchical Clustering | 686 |

Genetic Algorithm for Optimal Imperceptibility in Image Communication | 700 |

Using Biased Support Vector Machine to Improve Retrieval Result | 714 |

A Fast MPEG4 Video Encryption Scheme | 720 |

A New MDS Algorithm for Textual Data Analysis | 860 |

Chaotic Behavior in Neural Networks | 868 |

SnapShots | 874 |

Deciphering the Genetic Blueprint of Cerebellar Development | 880 |

A Guided Tour of Neuroinformatics Research in India | 891 |

Fuzzy Systems | 898 |

A Fuzzy Multilevel Programming Method | 904 |

Fuzzy RuleBased Systems Derived from Similarity to Prototypes | 912 |

A Partitioning Method for Fuzzy Probabilistic Predictors | 929 |

Fuzzy Compactness Based Adaptive Window Approach | 935 |

Neurofuzzy Systems | 941 |

A Neurofuzzy Approach for Predicting the Effects of Noise Pollution | 947 |

Evolving Fuzzy Neural Networks Applied to Odor Recognition | 953 |

Differential Evolution Based OnLine Feature Analysis | 959 |

Neurofuzzy System for Clustering of Video Database | 965 |

Dynamic Neurofuzzy Inference and Statistical Models for Risk Analysis | 971 |

An Enhanced Fuzzy Multilayer Perceptron | 977 |

Hybrid Systems | 983 |

Genetic Algorithm Based Fuzzy ID3 Algorithm | 989 |

NeuralEvolutionary Learning in a Bounded Rationality Scenario | 996 |

Rule Extraction Framework Using Rough Sets and Neural Networks | 1002 |

A Fusion Neural Network for Estimation of Blasting Vibration | 1008 |

Feature Selection for Fast Image Classification | 1026 |

Independent Component Analysis | 1044 |

Automated Diagnosis of Brain Tumours Using a Novel Density Estimation | 1058 |

Permutation Correction of Filter Bank | 1076 |

Ant Colony | 1082 |

Investigations into the Use of Supervised Multiagents | 1101 |

Neural Network Hardware | 1117 |

Robotics | 1135 |

A Genetic Approach to Optimizing the Values of Parameters | 1148 |

Signal Processing | 1166 |

TwoStage Duration Model for Indian Languages | 1179 |

A Comparative Study of Feature Extraction Algorithms | 1192 |

Speaker Segmentation Based on Subsegmental Features | 1210 |

A Study for Excluding Incorrect Detections of Holter ECG Data | 1223 |

Phoneme Transcription by a Support Vector Machine | 1241 |

Support Vector Machines Approach to Pattern Detection | 1254 |

Combined Kernel Function for Support Vector Machine | 1273 |

Neural Networks for fMRI Spatiotemporal Analysis | 1292 |

Modeling Corrupted Time Series Data | 1298 |

Hydrological Forecasting and Updating Procedures for Neural Network | 1304 |

Bioinformatics | 1310 |

Protein Metal Binding Residue Prediction Based on Neural Networks ChinTeng Lin KenLi Lin ChihHsien Yang IFang Chung | 1316 |

Assessment of Reliability of Microarray Data | 1322 |

DNA Sequence Pattern Identification | 1328 |

Genetic Mining of DNA Sequence Structures for Effective Classification | 1334 |

Gene Regulatory Network Discovery | 1344 |

Author Index 1363 | 1362 |

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### 常見字詞

activity adaptive agent algorithm analysis applied approach average Berlin Heidelberg 2004 binary calculated cell classifier clustering competitive components Computer cortical data set database defined denotes dynamics eigenfaces equation error estimation evaluate evolutionary algorithm experimental results experiments extracted face detection face image face recognition feature vector fingerprint frequency function Fuzzy Gaussian genetic algorithm Heidelberg hidden units ICONIP IEEE input pattern kernel layer learning linear LNCS Machine Learning matrix minutiae module N.R. Pal neural network neurons nodes noise object obtained optimal output paper parameters performance phase pixel PPNN problem Proc proposed method pulse receptive field recurrent neural network region represents samples selected self-organizing Self-Organizing Map shown shows signal simulation space Springer-Verlag Berlin Heidelberg structure supervised learning support vector machines synaptic target task technique threshold tion training set update variables visual visual cortex wavelet weights