• 
  Proceedings of the International Joint Conference on Neural Networks, IJCNN 2006, part of the IEEE World Congress on Computational Intelligence, WCCI 2006, Vancouver, BC, Canada, 16-21 July 2006. IEEE 2006

Neural Hardware I

• 
  Johannes Schemmel, Andreas Grübl, Karlheinz Meier, Eilif Mueller: Implementing Synaptic Plasticity in a VLSI Spiking Neural Network Model. 1-6
• 
  Eric K. C. Tsang, Bertram Emil Shi: Active Binocular Gaze Control Inspired by Superior Colliculus. 7-14
• 
  Ocean Y. H. Cheung, Philip Heng Wai Leong, Eric K. C. Tsang, Bertram Emil Shi: A Scalable FPGA Implementation of Cellular Neural Networks for Gabor-type Filtering. 15-20
• 
  Johannes Fieres, Johannes Schemmel, Karlheinz Meier: Training convolutional networks of threshold neurons suited for low-power hardware implementation. 21-28
• 
  Liang Zhang, Joaquin Sitte: Local Cluster Neural Network On-chip Training. 29-34
• 
  Ming Z. Zhang, Ming-Jung Seow, Vijayan K. Asari: A Hardware Architecture for Color Image Enhancement Using a Machine Learning Approach with Adaptive Parameterization. 35-40

Reinforcement Learning Theory I

• 
  Jelmer van Ast, Robert Babuska: Dynamic Exploration in Q(lambda)-learning. 41-46
• 
  Xiaolong Ma, Konstantin Likharev: Global Reinforcement Learning in Neural Networks with Stochastic Synapses. 47-53
• 
  Johane Takeuchi, Osamu Shouno, Hiroshi Tsujino: Connectionist Reinforcement Learning with Cursory Intrinsic Motivations and Linear Dependencies to Multiple Representations. 54-61
• 
  Thaddeus T. Shannon: Qualitative Adaptive Critics. 62-67
• 
  Ju Jiang, Mohamed S. Kamel: Aggregation of Reinforcement Learning Algorithms. 68-72
• 
  Jan Peters, Stefan Schaal: Reinforcement Learning for Parameterized Motor Primitives. 73-80

Neuroinformatics

• 
  Vicenç Gómez, Andreas Kaltenbrunner, Vicente López: Event modeling of message interchange in stochastic neural ensembles. 81-88
• 
  Fernando Buarque de Lima Neto, Philippe De Wilde: Venn-like models of neo-cortex patches. 89-96
• 
  Antony Browne: Using Neural Networks with Automatic Relevance Determination to Identify Regions of the Thalamus Implicated in Schizophrenia. 97-101
• 
  Marc de Kamps: An analytic solution of the reentrant Poisson master equation and its application in the simulation of large groups of spiking neurons. 102-109
• 
  Thierry Viéville, Pierre Kornprobst: Modeling Cortical Maps with Feed-Backs. 110-117
• 
  Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana D. de Lima, Thomas B. Voigt: Simulation of young neocortical networks by spatially coupled oscillators. 118-122

Learning in Kernel Methods

• 
  Kaan Ataman, W. Nick Street, Yi Zhang: Learning to Rank by Maximizing AUC with Linear Programming. 123-129
• 
  Olutayo O. Oladunni, Theodore B. Trafalis: A Pairwise Reduced Kernel-based Multi-classification Tikhonov Regularization Machine. 130-137
• 
  Carlos Alzate, Johan A. K. Suykens: A Weighted Kernel PCA Formulation with Out-of-Sample Extensions for Spectral Clustering Methods. 138-144
• 
  Roland Vollgraf, Klaus Obermayer: Sparse Optimization for Second Order Kernel Methods. 145-152
• 
  Ichiro Takeuchi, Kaname Nomura, Takafumi Kanamori: The Entire Solution Path of Kernel-based Nonparametric Conditional Quantile Estimator. 153-158
• 
  Ping Sun, Xin Yao: Greedy forward selection algorithms to Sparse Gaussian Process Regression. 159-165

Neural Modeling of Emotion

• 
  Jia-Jun Wong, Siu-Yeung Cho: Recognizing Human Emotion from Partial Facial Features. 166-173
• 
  Nickolaos F. Fragopanagos, Nienke J. H. Korsten, John G. Taylor: A neural model of the enhancement of perception caused by emotional cues. 174-180
• 
  Bing Lu, Walter M. Yamada, Theodore W. Berger: Nonlinear Queuing Model for Dynamic Synapse with Multiple Transmitter Pools. 181-187
• 
  Steven L. Bressler, Craig G. Richter, Yonghong Chen, Mingzhou Ding: Top-Down Cortical Influences in Visual Expectation. 188-194
• 
  Daniel S. Levine: Emotion and Decision Making: Short-term Reactions versus Long-term Evaluations. 195-202

Complex-Valued Neural Networks I

• 
  Mitsunaga Kinjo, Shigeo Sato, Koji Nakajima: A Study on Learning with a Quantum Neural Network. 203-206
• 
  Gerasimos G. Rigatos: Energy spectrum of quantum associative memories. 207-212
• 
  Yasuaki Kuroe, Yuriko Taniguchi: Models of Self-Correlation Type Complex-Valued Associative Memories and Their Performance Comparison. 213-217
• 
  Teijiro Isokawa, Haruhiko Nishimura, Naotake Kamiura, Nobuyuki Matsui: Fundamental Properties of Quaternionic Hopfield Neural Network. 218-223
• 
  Katsuhiro Mori, Teijiro Isokawa, Noriaki Kouda, Nobuyuki Matsui, Haruhiko Nishimura: Qubit Inspired Neural Network towards Its Practical Applications. 224-229
• 
  George M. Georgiou: Exact Interpolation and Learning in Quadratic Neural Networks. 230-234

Reinforcement Learning Theory II

• 
  Nancy Fulda, Dan Ventura: Learning a Rendezvous Task with Dynamic Joint Action Perception. 235-240
• 
  Mohammad G. Azar, Majid Nili Ahmadabadi, Amir Massoud Farahmand, Babak Nadjar Araabi: Learning to Coordinate Behaviors in Soft Behavior-Based Systems Using Reinforcement Learning. 241-248
• 
  Krishna P. Miyapuram, Raju S. Bapi, Chandrasekhar V. S. Pammi, Ahmed, Kenji Doya: Hierarchical Chunking during Learning of Visuomotor Sequences. 249-253
• 
  Maryam Shokri, Hamid R. Tizhoosh, Mohamed Kamel: Opposition-Based Q(lambda) Algorithm. 254-261
• 
  Myriam Abramson, William Chao, Ranjeev Mittu: Training Coordination Proxy Agents. 262-269
• 
  Nicolas Brodu: Learning using Dynamical Regime Identification and Synchronization. 270-276

Neuroscience & Computational Neuroscience I

• 
  Abraham K. Ishihara, Johan van Doornik, Terence D. Sanger: Failure Modes in Feedback Error Learning. 277-284
• 
  Karina Odinaev, Igal Raichelgauz, Yehoshua Y. Zeevi: Cliques in Neural Ensembles as Perception Carriers. 285-292
• 
  Atsuo Suemitsu, Masahiko Morita: Neural Network Model of Context-Dependent Neuronal Activity in Inferotemporal Cortex. 293-298
• 
  Alan Rosen, David B. Rosen: A Neural Network Model of the Connectivity of the Biological Somatic Sensors. 299-306
• 
  Rolf Eckmiller, Oliver Baruth, Dirk Neumann: On Human Factors for Interactive Man-Machine Vision: Requirements of the Neural Visual System to transform Objects into Percepts. 307-311
• 
  Lennart Gustafsson, Andrew P. Paplinski: Bimodal Integration of Phonemes and Letters: an Application of Multimodal Self-Organizing Networks. 312-318

Support Vector Machines & Kernel Methods I

• 
  Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano: Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error. 319-326
• 
  Tao Ban, Shigeo Abe: Implementing Multi-class Classifiers by One-class Classification Methods. 327-332
• 
  Daniel T. H. Lai, Nallasamy Mani, Marimuthu Palaniswami: An inexact penalty method for the semiparametric Support Vector Machine classifier. 333-338
• 
  Leonardo V. Ferreira, Eugenius Kaszkurewicz, Amit Bhaya: Parallel Implementation of Gradient-Based Neural Networks for SVM Training. 339-346
• 
  Stefan Lessmann, Sven F. Crone, Robert Stahlbock: An Evaluation of Discrete Support Vector Machines for Cost-Sensitive Learning. 347-354
• 
  Jun Guo, Norikazu Takahashi, Tetsuo Nishi: Convergence Proof of a Sequential Minimal Optimization Algorithm for Support Vector Regression. 355-362

Neurodynamics of Higher-Level Cognitive Behavior I

• 
  J. A. Scott Kelso, Emmanuelle Tognoli: Metastability in the brain. 363-368
• 
  Walter J. Freeman, Giuseppe Vitiello: Exploration of relations between many-body field theory and the nonlinear brain dynamics that underlies cognitive behavior. 369-376
• 
  Leonid I. Perlovsky: Neural Dynamic Logic of Consciousness: the Knowledge Instinct. 377-383
• 
  Steven L. Bressler, Craig G. Richter, Yonghong Chen, Mingzhou Ding: Top-Down Cortical Influences in Visual Expectation. 384-390

Biometrics: Algorithms, Architectures & Applications I

• 
  Yuheng Zhang, Qinghan Xiao: An Optimized Approach for Fingerprint Binarization. 391-395
• 
  Deepak Mishra, Abhishek Yadav, Ashutosh Dwivedi, Prem Kumar Kalra: A Neural Network Using Single Multiplicative Spiking Neuron for Function Approximation and Classification. 396-403
• 
  Wen-Chang Cheng: Neural-Network-Based Photometric Stereo for 3D Surface Reconstruction. 404-410

Towards Human-Level Intelligence

• 
  James A. Anderson, Paul Allopenna: The Ersatz Brain Project: Neural Inspiration, Cognitive Application. 411-418
• 
  Robert Hecht-Nielsen: The Mechanism of Thought. 419-426
• 
  L. Andrew Coward: Constraints on the Design Process for Systems with Human Level Intelligence. 427-434
• 
  Wlodzislaw Duch: Computational Creativity. 435-442
• 
  Alexei V. Samsonovich, Giorgio A. Ascoli, Kenneth A. De Jong: Computational Assessment of the 'Magic' of Human Cognition. 443-450
• 
  Ben Goertzel: Patterns, Hypergraphs and Embodied General Intelligence. 451-458

Complex-Valued Neural Networks II

• 
  Ikuko Nishikawa, Takeshi Iritani, Kazutoshi Sakakibara: Improvements of the Traffic Signal Control by Complex-Valued Hopfield Networks. 459-464
• 
  Zhe Chen, Jinwen Ma: Contrast Functions for Non-circular and Circular Sources Separation in Complex-Valued ICA. 465-472
• 
  Igor N. Aizenberg, Dmitriy Paliy, Jaakko Astola: Multilayer Neural Network based on Multi-Valued Neurons and the Blur Identification Problem. 473-480
• 
  Andriyan Bayu Suksmono, Astri Handayani, Akira Hirose: Snake in Phase Domain: A Method for Boundary Detection of Objects in Phase Images. 481-485
• 
  Howard E. Michel, Abdul Ahad S. Awwal, David Rancour: Artificial Neural Networks Using Complex Numbers and Phase Encoded Weights—Electronic and Optical Implementations. 486-491
• 
  Akira Hirose, Tomoaki Higo, Ken Tanizawa: Holographic Three-Dimensional Movie Generation with Frame Interpolation Using Coherent Neural Networks. 492-497

Reinforcement Learning Applications

• 
  Eric A. Antonelo, Albert-Jan Baerveldt, Thorsteinn S. Rögnvaldsson, Mauricio Figueiredo: Modular Neural Network and Classical Reinforcement Learning for Autonomous Robot Navigation: Inhibiting Undesirable Behaviors. 498-505
• 
  Roman Ilin, Robert Kozma, Paul J. Werbos: Cellular SRN Trained by Extended Kalman Filter Shows Promise for ADP. 506-510
• 
  Farhang Sahba, Hamid R. Tizhoosh, Magdy M. A. Salama: A Reinforcement Learning Framework for Medical Image Segmentation. 511-517
• 
  Hossein Javaherian, Derong Liu, Olesia Kovalenko: Automotive Engine Torque and Air-Fuel Ratio Control Using Dual Heuristic Dynamic Programming. 518-525
• 
  Jan Eriksson, Alessandro E. P. Villa: Artificial Neural Networks simulation of learning of auditory equivalence classes for vowels. 526-533
• 
  Jian Li, Laiwan Chan: Reward Adjustment Reinforcement Learning for Risk-averse Asset Allocation. 534-541

Neuroscience & Computational Neuroscience II

• 
  Huaien Luo, Sadasivan Puthusserypady: NARX Neural Networks for Dynamical Modelling of fMRI Data. 542-546
• 
  Nathan A. Dunn, Jonathan T. Pierce-Shimomura, John S. Conery, Shawn R. Lockery: Clustered Neural Dynamics Identify Motifs for Chemotaxis in Caenorhabditis elegans. 547-554
• 
  Hiroyuki Kambara, Kyoungsik Kim, Duk Shin, Makoto Sato: Motor Control-Learning Model for Reaching Movements. 555-562
• 
  Thierry Viéville: About biologically plausible trajectory generators. 563-572
• 
  Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma: Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method. 573-580
• 
  Il Park, Dongming Xu, Thomas B. DeMarse, Jose C. Principe: Modeling of Synchronized Burst in Dissociated Cortical Tissue: An Exploration of Parameter Space. 581-586

Support Vector Machines & Kernel Methods II

• 
  Boyang Li, Jinglu Hu, Kotaro Hirasawa, Pu Sun, Marko Marko: Support Vector Machine with Fuzzy Decision-Making for Real-world Data Classification. 587-592
• 
  Jayadeva, Reshma Khemchandani, Suresh Chandra: Regularized Least Squares Fuzzy Support Vector Regression for Time Series Forecasting. 593-598
• 
  Jiyoung Sun, Sungzoon Cho: Pattern Selection for Support Vector Regression based on Sparseness and Variability. 599-602
• 
  Shian-Chang Huang, Tung-Kuang Wu: Wavelet-Based Relevance Vector Machines for Stock Index Forecasting. 603-609
• 
  Matthew Boardman, Thomas P. Trappenberg: A Heuristic for Free Parameter Optimization with Support Vector Machines. 610-617
• 
  Andrea Boni, Alessandro Zorat: FPGA Implementation of Support Vector Machines with Pseudo-Logarithmic Number Representation. 618-624

Neurodynamics of Higher-Level Cognitive Behavior II

• 
  Daniel S. Levine: Modeling the Evolution of Decision Rules in the Human Brain. 625-631
• 
  Robert Kozma: Influence of Criticality on 1/f^alphaSpectral Characteristics of Cortical Neuron Populations. 632-637
• 
  Colin Molter, Utku Salihoglu, Hugues Bersini: How to prevent spurious data in a chaotic brain. 638-644
• 
  Emílio Del Moral Hernandez: Fragmented Basins of Attraction of Recursive Processing Elements in Associative Neural Networks and its Impact on Pattern Recovery Performance. 645-652
• 
  Jin Zhang, Guang Li, Walter J. Freeman: Application of Novel Chaotic Neural Networks to Mandarin Digital Speech Recognition. 653-658
• 
  José Luis Rosselló, Sebastiàn A. Bota, Vicens Canals, Ivan de Paúl, Jaume Segura: A Fully CMOS Low-Cost Chaotic Neural Network. 659-663

Biometrics: Algorithms, Architectures & Applications II

• 
  S. Nalin Pradeep, Mayur D. Jain, C. Prakash, Raman Balasubramanian: Palmprint Recognition: Two level Structure Matching. 664-669
• 
  Robert Paquet, Abbas Z. Kouzani: Advances in 3D-Based Face Recognition. 670-675
• 
  Svetlana N. Yanushkevich: Synthetic Biometrics: A Survey. 676-683
• 
  Stephane Armand, Michael Blumenstein, Vallipuram Muthukkumarasamy: Off-line Signature Verification using the Enhanced Modified Direction Feature and Neural-based Classification. 684-691
• 
  Youngchan Han, Jungwoo Nam, Nohjun Park, Hakil Kim: Resolution and Distortion Compensation based on Sensor Evaluation for Interoperable Fingerprint Recognition. 692-698
• 
  Mosaab Daoud, Stefan C. Kremer: Neural and Statistical Classification to Families of Bio-sequences. 699-704

Fuzzy Neural Networks

• 
  Richard Jayadi Oentaryo, Michel Pasquier: GENSOFNN-YAGER: A Novel Hippocampus-like Learning Memory System Realizing Yager Inference. 705-712
• 
  Dipti Srinivasan, Saptak Sanyal, Woei Wan Tan: Hybrid Neuro-Fuzzy Technique for Automated Traffic Incident Detection. 713-719
• 
  Mingyu Zhong, Bryan Rosander, Michael Georgiopoulos, Georgios C. Anagnostopoulos, Mansooreh Mollaghasemi, Samuel Richie: Experiments with Safe ARTMAP and Comparisons to Other ART Networks. 720-727
• 
  Shuangwen Sheng, Robert X. Gao: Optimization of ANFIS with Applications in Machine Defect Severity Classification. 728-734
• 
  Chin-Ming Hong, Chih-Ming Chen, Shyuan-Yi Chen, Chao-Yen Huang: A Novel and Efficient Neuro-Fuzzy Classifier for Medical Diagnosis. 735-741
• 
  Kai Keng Ang, Chai Quek: Rough set-based neuro-fuzzy system. 742-749

Posters

• 
  Seiji Miyoshi, Masato Okada: Statistical Mechanics of Online Learning for Ensemble Teachers. 750-755
• 
  Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa: Training Radial Basis Functions by Gradient Descent. 756-762
• 
  Sana'a W. Al-Sayegh: Hybrid Neural Network. 763-770
• 
  Yingfeng Wang, Xiaoqin Zeng: Using a Sensitivity Measure to Improve Training Accuracy and Convergence for Madalines. 771-777
• 
  Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sarti, Franco Scarselli, Marco Maggini, Marco Gori: A Comparison between Recursive Neural Networks and Graph Neural Networks. 778-785
• 
  Jing Li, Bao-Liang Lu: A New Supervised Clustering Algorithm Based on Min-Max Modular Network with Gaussian-Zero-Crossing Functions. 786-793
• 
  Wieslaw Sienko, Dariusz Zamojski: Hamiltonian Neural Networks Based Classifiers and Mappings. 794-798
• 
  Ming Dong, Jing Wu: Localized Support Vector Machines for Classification. 799-805
• 
  Hazem M. El-Bakry, Qiangfu Zhao: Fast Neural Implementation of PCA for Face Detection. 806-811
• 
  Chee Wee Phua, Alan Blair: An Improved Minibrain That Learns Through Both Positive and Negative Feedback. 812-819
• 
  Seungtaek Kim, Sungzoon Cho: Prototype based outlier detection. 820-826
• 
  Jianchuan Yin, Fang Dong, Nini Wang: A Novel Sequential Learning Algorithm for RBF Networks and Its Application to Dynamic System Identification. 827-834
• 
  Salvatore Calcagno, Antonino Greco, Francesco Carlo Morabito, Mario Versaci: A Comparison between Soft Computing and Statistic Approaches to Identify Plasma Columns in Tokamak Reactors. 835-842
• 
  Juha Karhunen, Tomas Ukkonen: Generalizing Independent Component Analysis for Two Related Data Sets. 843-850
• 
  Erika Coppola, Barbara Tomassetti, Marco Verdecchia, Frank S. Marzano, Guido Visconti: Small-catchment flood forecasting and drainage network extraction using computational intelligence. 851-858
• 
  S. Mohammad Sadeghzadeh, Meghdad Ansarian: Neuro-Fuzzy Control of SSSC and SMES for Transient Stability Improvement of Power System Transmission Lines. 859-863
• 
  Huilan Jiang, Tangsheng Liu, Mengbin Wang: Direct Estimation of Fault Tolerance of Feed Forward Neural Networks in Pattern Recognition. 864-869
• 
  Jianghua Bao, Paul W. Munro: Structural Mapping with Identical Elements Neural Network. 870-874
• 
  Narri Yadaiah, Lakshman Singh, Raju S. Bapi, V. Seshagiri Rao, Bulusu Lakshmana Deekshatulu, Atul Negi: MultisensorData Fusion Using Neural Networks. 875-881
• 
  Ahmad Banakar, Mohammad Fazle Azeem: Generalized Wavelet Neural Network Model and its Application in Time Series Prediction. 882-886
• 
  Ana M. González, José R. Dorronsoro: A Note on Conjugate Natural Gradient Training of Multilayer Perceptrons. 887-891
• 
  Giuseppe Acciani, Gioacchino Brunetti, Ernesto Chiarantoni, Girolamo Fornarelli: Automatic Evaluation of Flaws in Pipes by means of Ultrasonic Waveforms and Neural Networks. 892-898
• 
  Robert X. Gao, Changting Wang, Ruqiang Yan, Arnaz Malhi: A Neural Network Approach to Bearing Health Assessment. 899-906
• 
  Justin Bray, Brijesh Verma, Xue Li, Wade He: A Neural Network based Technique for Automatic Classification of Road Cracks. 907-912
• 
  Rozaida Ghazali, Abir Jaafar Hussain, Wael El-Deredy: Application of Ridge Polynomial Neural Networks to Financial Time Series Prediction. 913-920
• 
  Sai-Ho Ling, F. H. Frank Leung, Hak-Keung Lam: A Variable Node-to-Node-Link Neural Network and Its Application to Hand-Written Recognition. 921-928
• 
  Tiago V. Barra, George Barreto Bezerra, Leandro Nunes de Castro, Fernando J. Von Zuben: An Immunological Density-Preserving Approach to the Synthesis of RBF Neural Networks for classification. 929-935
• 
  Cuimei Bo, Zhiquan Wang, Jinguo Lin, Shi Zhang, Guangming Zhang: The Online Models based Fault Tolerant Control for Multiple Sensor Fault of Multi-variable Nonlinear Processes. 936-943
• 
  Elham Bavafa, Mohammad Javad Yazdanpanah: Image Compression using an Enhanced Self Organizing Map Algorithm with Vigilance Parameter. 944-949
• 
  Haruna Matsushita, Yoshifumi Nishio: Tentacled Self-Organizing Map for Effective Data Extraction. 950-957
• 
  John Hammond, Daniel MacClean, Iren Valova: A Parallel Implementation of a Growing SOM Promoting Independent Neural Networks over Distributed Input Space. 958-965
• 
  Simon O'Keefe: SOM-Based Sparse Binary Encoding for AURA Classifier. 966-972
• 
  Cihan Oguz, Martha A. Gallivan: Identification of a Dynamic Model for a Thin Film Deposition Process using a Self-Organizing Map. 973-980
• 
  Yangsheng Chen, Gangfeng Yan: Multi-Sensors Data Tracking Fusion Based on a Neural Network Filter. 981-984
• 
  Hsin-Chang Yang, Chung-Hong Lee: NaviSOM: Automatic Construction of Navigational Structure for Web Pages using Self-organizing Maps. 985-992
• 
  Gilles Hermann, Patrice Wira, Jean-Philippe Urban: Bi-directional Modularity to Learn Visual Servoing Tasks. 993-1000
• 
  Hikaru Mogami, Masahiko Otake, Naoki Kouno, Yuko Osana: Self-Organizing Map with Refractoriness and Its Application to Image Retrieval. 1001-1006
• 
  Hamed Shah-Hosseini: The Time Adaptive Self-Organizing Map is a Neural Network Based on Artificial Immune System. 1007-1014
• 
  Zhigang Zeng, Jun Wang: Synthesis of Bipolar Associative Memories Based on Cellular Neural Networks with Two-dimensional Space-invariant Templates. 1015-1020
• 
  Ivo Petras: A Note on the Fractional-Order Cellular Neural Networks. 1021-1024
• 
  Anke Meyer-Bäse, Vera Thümmler, Fabian J. Theis: Stability Analysis of an Unsupervised Competitive Neural Network. 1025-1028
• 
  Anke Meyer-Bäse, R. Roberts, S. Joshi: Robust Stability Analysis of a Class of Noise Perturbed Two-Time Scale Neural Networks. 1029-1032
• 
  Dong-Shong Liang, Yaw-Hwang Chen, Chun-Min Wen, Chun-Da Tu, Kwang-Jow Gan, Cher-Shiung Tsai: The Design of MOS-NDR-Based Cellular Neural Network. 1033-1035
• 
  Xiaodong Gu: A New Approach to Image Authentication using Local Image Icon of Unit-linking PCNN. 1036-1041
• 
  Narri Yadaiah, G. Sowmya: Neural Network Based State Estimation of Dynamical Systems. 1042-1049
• 
  David Verstraeten, Benjamin Schrauwen, Dirk Stroobandt: Reservoir-based techniques for speech recognition. 1050-1053
• 
  ZhiHang Chen, Chengwen Ni, Yi Lu Murphey: Neural Network Approaches for Text Document Categorization. 1054-1060
• 
  Mohammad Fazle Azeem, Ahmad Banakar, Vinod Kumar: Comparative Study of Different Types of Wavelet Functions in Neural Network. 1061-1066
• 
  Rigui Zhou, Hong Yuan Zheng, Nan Jiang, Qiulin Ding: Self-Organizing Quantum Neural Network. 1067-1072
• 
  Pei Ling Lai, Gayle Leen, Colin Fyfe: A Comparison of Stochastic Processes and Artificial Neural Networks for Canonical Correlation Analysis. 1073-1077
• 
  Tuan A. Duong, De-Ling Liu, Isik Kanik: Neural Network Prediction of Reduced Ion Mobility of Chemical Compound Based on Molecular Structure. 1078-1084
• 
  Kuo-Chen Li, Dar-Jen Chang, Yuan Yan Chen: High-speed Bi-directional Function Approximation using Plausible Neural Networks. 1085-1090
• 
  Lech M. Grzesiak, Bartlomiej Ufnalski: Neural-Network-based Programmable State Feedback Controller for Induction Motor Drive. 1091-1097
• 
  Piotr Ciskowski: Efficient Modeling of Contextual Mappings by Context-dependent Feedforward and Recurrent Neural Nets. 1098-1105
• 
  Dixin Guo, Jimin Chen, Yuhong Cheng: Laser Cutting Parameters Optimization Based on Artificial Neural Network. 1106-1111
• 
  Almila Bahar, Evren Giiner, Canan Özgen, Ugur Halici: Design of State Estimators for the Inferential Control of an Industrial Distillation Column. 1112-1115
• 
  Sandeep Chandana, René V. Mayorga: Rough Set Theory based Neural Network Architecture. 1116-1122
• 
  Kazushi Ikeda: On Geometric Structure of Quasi-Additive Learning Algorithms. 1123-1127
• 
  Pablo Zegers, Jose G. Johnson: Consistent Density Function Estimation with Multilayer Perceptrons. 1128-1135
• 
  Yonghong Huang, Deniz Erdogmus, Santosh Mathan, Misha Pavel: Comparison of Linear and Nonlinear Approaches on Single Trial ERP Detection in Rapid Serial Visual Presentation Tasks. 1136-1142
• 
  Pei Ling Lai, Colin Fyfe: A Latent Variable Implementation of Canonical Correlation Analysis for Data Visualisation. 1143-1149
• 
  Chih-Cheng Yang, Wan-Jui Lee, Shie-Jue Lee: Learning of Kernel Functions in Support Vector Machines. 1150-1155
• 
  Hirotaka Nakayama, Yeboon Yun: Support Vector Regression Based on Goal Programming and Multi-objective Programming. 1156-1161
• 
  Rameswar Debnath, Haruhisa Takahashi: SVM Training: Second-Order Cone Programming versus Quadratic Programming. 1162-1168
• 
  Ivor W. Tsang, James T. Kwok, Shutao Li: Learning the Kernel in Mahalanobis One-Class Support Vector Machines. 1169-1175
• 
  Satarupa Banerjee, Lillian N. Cassel: Web Host Access Tool: A Support Vector Machine Approach. 1176-1183
• 
  Kien-Ping Chung, Kok Wai Wong, Chun Che Fung: Reducing User Log size in an Inter-Query Learning Content Based Image Retrieval (CBIR) System with a Cluster Merging approach. 1184-1191
• 
  Jayadeva, Reshma Khemchandani, Suresh Chandra: Regularized Least Squares Twin SVR for the Simultaneous Learning of a Function and its Derivative. 1192-1197
• 
  Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría: Online Kernel Canonical Correlation Analysis for Supervised Equalization of Wiener Systems. 1198-1204
• 
  Kuo-Ping Wu, Sheng-De Wang: Choosing the Kernel parameters of Support Vector Machines According to the Inter-cluster Distance. 1205-1211
• 
  Takashi Onoda, Hiroshi Murata, Seiji Yamada: Non-Relevance Feedback Document Retrieval based on One Class SVM and SVDD. 1212-1219
• 
  Ben Goertzel, James Venuto: Accurate SVM Text Classification for Highly Skewed Data Using Threshold Tuning and Query-Expansion-Based Feature Selection. 1220-1225
• 
  Deborah Duong, James Venuto, Ben Goertzel, Ryan Richardson, Shawn Bohner, Edward A. Fox: Support Vector Machines to Weight Voters in a Voting System of Entity Extractors. 1226-1230
• 
  Bai Yifeng, Xiao Jian, Yu Long: Kernel Partial Least-Squares Regression. 1231-1238
• 
  Iryna Nischenko, Elsa M. Jordaan: Confidence of SVM Predictions using a Strangeness Measure. 1239-1246
• 
  Bao Rong Chang, Hsiu Fen Tsai: Financial Prediction Applications Using Quantum-Minimized Composite Model ASVR/NGARCH. 1247-1253
• 
  Sunho Park, Seungjin Choi: Rao-Blackwellized Particle Filtering for Sequential Speech Enhancement. 1254-1259
• 
  Ulf Johansson, Tuve Löfström, Rikard König, Lars Niklasson: Building Neural Network Ensembles using Genetic Programming. 1260-1265
• 
  Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez: Pruning in Ordered Regression Bagging Ensembles. 1266-1273
• 
  Marcin Korytkowski, Leszek Rutkowski, Rafal Scherer: On Combining Backpropagation with Boosting. 1274-1277
• 
  Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Designing a Multilayer Feedforward Ensembles with Cross Validated Boosting Algorithm. 1278-1283
• 
  Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Designing a New Multilayer Feedforward Modular Network for Classification Problems. 1284-1289
• 
  Pavel Kordík, Jan Saidl, Miroslav Snorek: Evolutionary Search for Interesting Behavior of Neural Network Ensembles. 1290-1293
• 
  Dingding Chen, John Quirein, Harry Smith, Syed Hamid, Jeff Grable, S. Reed: Variable Input Neural Network Ensembles in Generating Synthetic Well Logs. 1294-1301
• 
  Kin Keung Lai, Lean Yu, Shouyang Wang, Wei Huang: Neural-Network-based Metalearning for Distributed Text Information Retrieval. 1302-1309
• 
  Rodrigo G. F. Soares, Alixandre Santana, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto: Using Accuracy and Diversity to Select Classifiers to Build Ensembles. 1310-1316
• 
  Hazem M. El-Bakry: A Simple Design for High Speed Normalized Neural Networks Implemented in the Frequency Domain for Pattern Detection. 1317-1324
• 
  Hazem M. El-Bakry: Fast Co-operative Modular Neural Processors for Human Face Detection. 1325-1332
• 
  Gao Daqi, Li Jie: Kernel Fisher Discriminants and Kernel Nearest Neighbor Classifiers: A Comparative Study for Large-Scale Learning Problems. 1333-1338
• 
  Jahangheer S. Shaik, Mohammed Yeasin: Visualization of High Dimensional Data using an Automated 3D Star Co-ordinate System. 1339-1346
• 
  Jiayan Jiang, LiMing Zhang: Extending Manifold Leaning Algorithms by Neural Networks. 1347-1353
• 
  Yuexian Hou, Jingyi Wu, Pilian He: Improving classification precision by implicit kernels motivated by manifold learning. 1354-1359
• 
  Qingzhong Liu, Andrew H. Sung: Recursive Feature Addition for Gene Selection. 1360-1367
• 
  Ashok Patel, Bart Kosko: Mutual-Information Noise Benefits in Brownian Models of Continuous and Spiking Neurons. 1368-1375
• 
  Akaysha C. Tang, Matthew T. Sutherland, Christopher J. McKinney, Jing-Yu Liu, Yan Wang, Lucas C. Parra, Adam D. Gerson, Paul Sajda: Classifying Single-Trial ERPs from Visual and Frontal Cortex during Free Viewing. 1376-1383
• 
  Vahid Taimouri, Gholam-Ali Hossein-Zadeh, Hamid Soltanian-Zadeh: Spatially Adaptive Kernels for Adaptive Spatial Filtering of fMRI Data. 1384-1388
• 
  Mohammad Soleymani, Gholam-Ali Hossein-Zadeh, Hamid Soltanian-Zadeh: Fixed and Random Effect Analysis of Multi-subject Spatial Activation Maps in Wavelet Domain. 1389-1392
• 
  Narendra S. Chaudhari, Nirmal Dagdee, Meng Joo Er: Hard-limiter Neuron based Turing Machine Simulation with Constant Time Read/Write Operation. 1393-1397
• 
  Jong-Pil Lee, Dae-Jong Lee, Pyeong-Shik Ji, Jae-Yoon Lim, Sung-Soo Kim: Diagnosis of Power Transformer using Fuzzy Clustering and Radial Basis Function Neural Network. 1398-1404
• 
  Hong-Dar Lin, Chih-Hao Chien: Automated Detection of Color Non-Uniformity Defects in TFT-LCD. 1405-1412
• 
  Seung-Hyun Lee, Jaekyoung Moon, Minho Lee: A Region of Interest Based Image Segmentation Method using a Biologically Motivated Selective Attention Model. 1413-1420
• 
  Satoshi Matsuda: A Neural Network Model for the Decision-Making Process Based on ANP. 1421-1426
• 
  Abel Nyamapfene, Khurshid Ahmad: Unsupervised Multi-net Simulation: An Application to Child Development. 1427-1433
• 
  Yuta Ishikawa, Ryohei Nakano: Landscape of a Likelihood Surface for a Gaussian Mixture and its use for the EM Algorithm. 1434-1440
• 
  Yuta Wada, Ken-ichi Tokunaga: Estimation of stochastic representation of via-points in human motion control by reinforcement learning. 1441-1446
• 
  Robert G. Escalante, Heidar A. Malki: Comparison of Artificial Neural Network Architectures and Training Algorithms for Solving the Knight's Tours. 1447-1450
• 
  Rong-Jong Wai, Jeng-Dao Lee, Chia-Chin Chu: Intelligent Decoupled Control for Linear Induction Motor Drive. 1451-1457
• 
  Zhenfu Bi, Fusheng Wang, Congcong Liu: Getting parameters in power systems based on adaptive linear neural network. 1458-1462
• 
  Lichen Liang, Vladimir Cherkassky, David A. Rottenberg: Spatial SVM for feature selection and fMRI activation detection. 1463-1469
• 
  Khalid Benabdeslem: Descendant hierarchical support vector machine for multi-class problems. 1470-1475
• 
  Yoshitsugu Kakemoto, Shinichi Nakasuka: The Learning and Dynamics of VSF-Network. 1476-1482

Neural Hardware II

• 
  Yan Meng: A Mobile Vision System with Reconfigurable Intelligent Agents. 1483-1488
• 
  Hiroomi Hikawa: Vector Quantization System Based on Scalar SOM/AND-OR Hybrid Network. 1489-1496
• 
  Alejandro Linares-Barranco, Rafael Paz-Vicente, Gabriel Jiménez, Juan L. Pedreño-Molina, Javier Molina-Vilaplana, Juan López Coronado: AER Neuro-Inspired interface to Anthropomorphic Robotic Hand. 1497-1504
• 
  Katsutoshi Saeki, Yugo Hayashi, Yoshifumi Sekine: Extraction of Phase Information Buried in Fluctuation of a Pulse-type Hardware Neuron Model Using STDP. 1505-1510
• 
  Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu, Peter M. Kelly: On the Design of a Low Power Compact Spiking Neuron Cell Based on Charge-Coupled Synapses. 1511-1517
• 
  Puxuan Dong, Griff L. Bilbro, Mo-Yuen Chow: Implementation of Artificial Neural Network for Real Time Applications Using Field Programmable Analog Arrays. 1518-1524

Supervised Learning I

• 
  César Hervás-Martínez, Francisco J. Martínez-Estudillo, Pedro Antonio Gutiérrez: Classification by means of Evolutionary Product-Unit Neural Networks. 1525-1532
• 
  Pablo Zegers, Jose G. Johnson: Exponential Transitions: Telltale Sign of Consistency in Learning Systems. 1533-1539
• 
  Haruhiko Takase, Hidehiko Kita, Terumine Hayashi: Fault tolerant training algorithm for multi-layer neural networks focused on hidden unit activities. 1540-1545
• 
  Chang Liu, Jing Hua, Lixin Wang, Ruwei Dai: An Integrative Neural Network with Feedback Control for Classification. 1546-1553
• 
  Dario Albesano, Roberto Gemello, Pietro Laface, Franco Mana, Stefano Scanzio: Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting. 1554-1561
• 
  Mark Brudnak: Vector-Valued Support Vector Regression. 1562-1569

Modeling the Evolution & Acquisition of Language

• 
  Leonid I. Perlovsky: Integrated Emotions, Cognition, and Language. 1570-1575
• 
  Angelo Cangelosi, Emmanouil Hourdakis, Vadim Tikhanoff: Language Acquisition and Symbol Grounding Transfer with Neural Networks and Cognitive Robots. 1576-1582
• 
  José F. Fontanari, Leonid I. Perlovsky: Meaning creation and communication in a community of agents. 1583-1588
• 
  Anastasios-Antonios Toulkeridis, Vassilios Petridis: From Signaling to Word-Combination, a Layered Approach. 1589-1595
• 
  Francis C. K. Wong, James W. Minett, William S.-Y. Wang: Reassessing Combinatorial Productivity Exhibited by Simple Recurrent Networks in Language Acquisition. 1596-1603
• 
  Nancy Chang, Eva Mok: A Structured Context Model for Grammar Learning. 1604-1611

Applications of Support Vector Machines & Kernel Methods

• 
  Feihong Wu: Comparing Kernels for Predicting Protein Binding Sites from Amino Acid Sequence. 1612-1616
• 
  Wei-Chiang Hong, Ping-Feng Pai, Shun-Lin Yang, Robert Theng: Highway traffic forecasting by support vector regression model with tabu search algorithms. 1617-1621
• 
  Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu: Local Support Vector Regression for Financial Time Series Prediction. 1622-1627
• 
  Nancy Arana-Daniel, Eduardo Bayro-Corrochano: MIMO SVMs for 3D object classification. 1628-1635
• 
  D. Srikrishna Satish, C. Chandra Sekhar: Kernel based Clustering and Vector Quantization for Speech Segmentation. 1636-1641
• 
  Clodoaldo Ap. M. Lima, Rafael Ferrari, Helder Knidel, C. Junqueira, Romis de Faissol Attux, João Marcos Travassos Romano, Fernando J. Von Zuben: Support Vector Clustering Applied to Digital Communications. 1642-1648

Performance Prediction Challenge I

• 
  Isabelle Guyon, Amir Reza Saffari Azar Alamdari, Gideon Dror, Joachim M. Buhmann: PerformancePrediction Challenge. 1649-1656
• 
  Roman W. Lutz: LogitBoost with Trees Applied to the WCCI 2006 Performance Prediction Challenge Datasets. 1657-1660
• 
  Gavin C. Cawley: Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs. 1661-1668
• 
  Corinne Dahinden: Classification with Tree-Based Ensembles Applied to the WCCI 2006 Performance Prediction Challenge Datasets. 1669-1672
• 
  Wei Chu: Model Selection: An Empirical Study on Two Kernel Classifiers. 1673-1679
• 
  Marc Boullé: Regularization and Averaging of the Selective Naive Bayes classifier. 1680-1688

Computational Intelligence in Power Systems I - Identification & Estimation

• 
  Ekrem Gursoy, Dagmar Niebur: On-line Estimation of Electric Power System Active Loads. 1689-1694
• 
  Joy Mazumdar, Ganesh K. Venayagamoorthy, Ronald G. Harley, Franklin C. Lambert: Echo State Networks for Determining Harmonic Contributions from Nonlinear Loads. 1695-1701
• 
  Kwang Y. Lee: System-Type Neural Network Architectures for Power Systems. 1702-1709
• 
  Innocent Kamwa, Baraboi Baraboi, René Wamkeue: Sensorless ANN-Based Speed Estimation of Synchronous Generators: Improved Performance through Physically Motivated Pre-filters. 1710-1718
• 
  Wenxin Liu, David A. Cartes, Ganesh K. Venayagamoorthy: Particle Swarm Optimization based Defensive Islanding of Large Scale Power System. 1719-1725

Signal Processing & Multi-Media

• 
  Pinaki Shankar Chanda, Sungjin Park, Tae Ik Kang: A Binaural Synthesis with Multiple Sound Sources Based on Spatial Features of Head-related Transfer Functions. 1726-1730
• 
  Jia-Ching Wang, Jhing-Fa Wang, Kuok Wai He, Cheng-Shu Hsu: Environmental Sound Classification using Hybrid SVM/KNN Classifier and MPEG-7 Audio Low-Level Descriptor. 1731-1735
• 
  Masaya Ohta, Hideyuki Yamada, Katsumi Yamashita: BER Performance Improvement of Biased PCC-OFDM with Neural Phase Rotator by Suppressing ICI. 1736-1741
• 
  Ross W. Deming, Shawn Higbee, Derek Dwyer, Michael Welser, Leonid I. Perlovsky, Paola Pellegrini: Adaptive Estimation for Spectral-Temporal Characterization of Energetic Transient Events. 1742-1749
• 
  Hung-Jen Wang, Chuan-Yu Chang, Sheng-Wen Pan: A DWT-based Robust Watermarking Scheme with Fuzzy ART. 1750-1757
• 
  Xin Song, Jinkuan Wang, Yinghua Han, Dan Tian: Neural Network-Based Robust Adaptive Beamforming. 1758-1763

Supervised Learning II

• 
  Andreas Hansson, Lars Niklasson: Using Segmentation to Control the Retrieval of Data. 1764-1769
• 
  Ken Chen, Bao-Liang Lu, James T. Kwok: Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers. 1770-1775
• 
  David A. Elizondo, Ralph Birkenhead, Éric D. Taillard: The Generalisation of the Recursive Deterministic Perceptron. 1776-1783
• 
  Miao Kang, Dominic Palmer-Brown: A Multi-layer ADaptive FUnction Neural Network (MADFUNN) for Analytical Function Recognition. 1784-1789
• 
  Ryotaro Kamimura: Supervised Information Maximization by Weighted Distance. 1790-1796
• 
  Benjamin Schrauwen, Jan M. Van Campenhout: Backpropagation for Population-Temporal Coded Spiking Neural Networks. 1797-1804

Data Mining & Knowledge Discovery

• 
  Francesca Trentini, Markus Hagenbuchner, Alessandro Sperduti, Franco Scarselli: A Self-Organising Map Approach for Clustering of XML Documents. 1805-1812
• 
  Nghia Tran, Christophe G. Giraud-Carrier, Kevin D. Seppi, Sean Warnick: Cooperation-based Clustering for Profit-maximizing Organizational Design. 1813-1817
• 
  Elsa M. Jordaan, Iryna Nischenko: Data Analysis and Confidence based on SVM Density Estimation. 1818-1824
• 
  Haixuan Yang, Irwin King, Michael R. Lyu: Predictive Random Graph Ranking on the Web. 1825-1832
• 
  Koichi Odajima, Yoichi Hayashi, Rudy Setiono: Greedy rule generation from discrete data and its use in neural network rule extraction. 1833-1839
• 
  Michael J. Watts, Susan P. Worner: Using MLP to Determine Abiotic Factors In uencing the Establishment of Insect Pest Species. 1840-1845

Probabilistic & Information-Theoretic Methods

• 
  Yiwen Wang, António R. C. Paiva, Jose C. Principe: A Monte Carlo Sequential Estimation for Point Process Optimum Filtering. 1846-1850
• 
  Jian-Wu Xu, Puskal P. Pokharel, António R. C. Paiva, Jose C. Principe: Nonlinear Component Analysis Based on Correntropy. 1851-1855
• 
  Aysegul Gunduz, Anant Hegde, Jose C. Principe: Correntropy as a Novel Measure for Nonlinearity Tests. 1856-1862
• 
  Jose Delpiano, Pablo Zegers: Semi-Autonomous Neural Networks Differential Equation Solver. 1863-1869
• 
  Mingyu Zhong, Dave Coggeshall, Ehsan Ghaneie, Thomas Pope, Mark Rivera, Michael Georgiopoulos, Georgios C. Anagnostopoulos, Mansooreh Mollaghasemi, Samuel Richie: Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks. 1870-1877
• 
  Felix Feger, Irena Koprinska: Co-training using RBF Nets and Different Feature Splits. 1878-1885

Model Selection

• 
  Imhoi Koo, Rhee Man Kil: Nonlinear Model Selection Based on the Modulus of Continuity. 1886-1893
• 
  Matti Kääriäinen: Semi-Supervised Model Selection Based on Cross-Validation. 1894-1899
• 
  Mathias M. Adankon, Mohamed Cheriet: New Formulation of SVM for Model Selection. 1900-1907
• 
  Timo Similä, Jarkko Tikka: Common Subset Selection of Inputs in Multiresponse Regression. 1908-1915
• 
  David L. Donoho, Victoria Stodden: Breakdown Point of Model Selection When the Number of Variables Exceeds the Number of Observations. 1916-1921
• 
  Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Kunapuli, Jong-Shi Pang: Model Selection via Bilevel Optimization. 1922-1929

Bioinformatics & Bio-Medical Engineering I

• 
  Feng Chu, Lipo Wang: Applying RBF Neural Networks to Cancer Classification Based on Gene Expressions. 1930-1934
• 
  Nicholas Stepenosky, Robi Polikar, John Kounios, Christopher M. Clark: Ensemble Techniques with Weighted Combination Rules for Early Diagnosis of Alzheimer's Disease. 1935-1941
• 
  Xiaoxu Han: Finding Phylogenetically Informative Genes by Estimating Multispecies Gene Entropy. 1942-1949
• 
  Wei Jiang, Seong G. Kong, Gregory D. Peterson: Continuous Heartbeat Monitoring Using Evolvable Block-based Neural Networks. 1950-1957
• 
  Vitoantonio Bevilacqua, Giuseppe Mastronardi, Filippo Menolascina, Paolo Pannarale, Antonio Pedone: A Novel Multi-Objective Genetic Algorithm Approach to Artificial Neural Network Topology Optimisation: The Breast Cancer Classification Problem. 1958-1965
• 
  Davide Anguita, Sandro Ridella, Dario Sterpi: Testing the Augmented Binary Multiclass SVM on Microarray Data. 1966-1968

Computational Intelligence in Power Systems II - Diagnosis & Control

• 
  Li Liu, David A. Cartes, Wenxin Liu: Application of Particle Swarm Optimization to PMSM Stator Fault Diagnosis. 1969-1974
• 
  Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes: Neural Network based Decentralized Excitation Control of Large Scale Power Systems. 1975-1981
• 
  Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Harley: Design of Optimal PI Controllers for Doubly Fed Induction Generators Driven by Wind Turbines Using Particle Swarm Optimization. 1982-1987
• 
  Ahmed Ali Abdalla Esmin: Loss Power Minimization Using Particle Swarm Optimization. 1988-1992
• 
  Alma Y. Alanis, Edgar N. Sanchez, Alexander G. Loukianov: Discrete- Time Recurrent Neural Induction Motor Control using Kalman Learning. 1993-2000

Military & Security Applications

• 
  Gymama E. Slaughter, Rosalyn S. Hobson: Artificial Neural Network for Temporal Impedance Recognition of Neurotoxins. 2001-2008
• 
  Paul E. Keller, Douglas L. McMakin, Thomas E. Hall, David M. Sheen: Use of a Neural Network to Identify Man-made Structure in Millimeter-Wave Images for Security Screening Applications. 2009-2014
• 
  Alireza A. Dibazar, Abhijith Bangalore, Hyung-Ook Park, Sageev T. George, Walter M. Yamada, Theodore W. Berger: Hardware Implementation of Dynamic Synapse Neural Networks for Acoustic Sound Recognition. 2015-2022
• 
  Nathan Brannon, Gregory Conrad, Timothy Draelos, John Seiffertt, Donald C. Wunsch: Information Fusion and Situation Awareness using ARTMAP and Partially Observable Markov Decision Processes. 2023-2030
• 
  Hung-Hsu Tsai, Kuo-Chun Wang, Chi-Chih Liu: Robust Watermarking in Wavelet Domain Using Rank Order and Genetic Algorithm for Image Authorization. 2031-2038
• 
  Maryam Arvandi, Shuwei Wu, Alireza Sadeghian, William W. Melek, Isaac Woungang: Symmetric Cipher Design Using Recurrent Neural Networks. 2039-2046

Evolutionary Approaches for Supervised Learning

• 
  Myoung Soo Park, Jin Young Choi: Fast Incremental Learning Algorithm using Evolutionary Logic Networks for Real-Value Inputs. 2047-2054
• 
  Michael J. Watts: Nominal-scale Evolving Connectionist Systems. 2055-2059
• 
  Eric Granger, Philippe Henniges, Luiz S. Oliveira, Robert Sabourin: Particle Swarm Optimization of Fuzzy ARTMAP Parameters. 2060-2067
• 
  Marek Bundzel, Peter Sincak: Combining Gradient and Evolutionary Approaches to the Artificial Neural Networks Training According to Principles of Support Vector Machines. 2068-2074
• 
  Rodrigo Pasti, Leandro Nunes de Castro: An Immune and a Gradient-Based Method to Train Multi-Layer Perceptron Neural Networks. 2075-2082
• 
  Helder Knidel, Fernando J. Von Zuben, Leandro Nunes de Castro: A Supervised Constructive Neuro-Immune Network for Pattern Classification. 2083-2089

Financial Engineering

• 
  Chai Quek, Michel Pasquier, Neha Kumar: A Novel Recurrent Neural Network Based Prediction System for Trading. 2090-2097
• 
  Georgi M. Dimirovski, Cvetko J. Andreeski: How Good ANN Identification of Post-Stabilization Inflation Dynamics Can Be? 2098-2105
• 
  Weizhong Yan, Piero P. Bonissone: Designing a Neural Network Decision System for Automated Insurance Underwriting. 2106-2113
• 
  Jagdish Chandra Patra, Weineng Lim, Pramod Kumar Meher, Ee-Luang Ang: Financial Prediction of Major Indices using Computational Efficient Artificial Neural Networks. 2114-2120
• 
  Lori L. DeLooze: Attack Characterization and Intrusion Detection using an Ensemble of Self-Organizing Maps. 2121-2128
• 
  Kin Keung Lai, Kaijian He, Chi Xie, Shou Chen: Market Risk Measurement for Crude Oil: A Wavelet Based VaR Approach. 2129-2136

Ensemble & Other Meta-Learning Algorithms

• 
  Feng Xue, Raj Subbu, Piero P. Bonissone: Locally Weighted Fusion of Multiple Predictive Models. 2137-2143
• 
  Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.: Combining Diversity and Classification Accuracy for Ensemble Selection in Random Subspaces. 2144-2151
• 
  Egar Sanchez, Salvador A. Pintos, Néstor V. Queipo: Toward an Optimal Ensemble of Kernel-based Approximations with Engineering Applications. 2152-2158
• 
  Shibendra S. Pobi, Lawrence O. Hall: Predicting Juvenile Diabetes from Clinical Test Results. 2159-2165
• 
  Paul F. Evangelista, Mark J. Embrechts, Boleslaw K. Szymanski: Data Fusion for Outlier Detection through Pseudo-ROC Curves and Rank Distributions. 2166-2173
• 
  Marcílio Carlos Pereira de Souto, Daniel S. A. de Araujo, Bruno L. C. da Silva: Cluster Ensemble for Gene Expression Microarray Data: Accuracy and Diversity. 2174-2180

Performance Prediction Challenge II

• 
  Eugene Tuv, Alexander Borisov, Kari Torkkola: Feature Selection Using Ensemble Based Ranking Against Artificial Contrasts. 2181-2186
• 
  Jörg D. Wichard: Model Selection in an Ensemble Framework. 2187-2192
• 
  Vladimir Nikulin: Learning with Mean-Variance Filtering, SVM and Gradient-based Optimization. 2193-2200
• 
  Yu-Yen Ou, Hao-Geng Hung, Yen-Jen Oyang: A Study of Supervised Learning with Multivariate Analysis on Unbalanced Datasets. 2201-2205

Bioinformatics & Bio-Medical Engineering II

• 
  Fernando Rios-Gutiérrez, Rocío Alba-Flores, Khaled Ejaz, Glenn Nordehn, Nicholas Andrisevic, Stanley Burns: Classification of Four Types of Common Murmurs using Wavelets and a Learning Vector Quantization Network. 2206-2213
• 
  Bancha Charumporn, Toru Fujinaka, Michifumi Yoshioka, Sigeru Omatu: Compact Electronic Nose Systems Using Metal Oxide Gas Sensors for Fire Detection Systems. 2214-2217
• 
  Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Koki Matsumura, Mariko Hatakeyama: Function Approximation Approach to the Inference of Normalized Gaussian Network Models of Genetic Networks. 2218-2225
• 
  Carlos A. M. Del Carpio, Mohamed Ismael, Eiichiro Ichiishi, Michihisa Koyama, Momoji Kubo, Akira Miyamoto: An Evolving Automaton for RNA Secondary Structure Prediction. 2226-2233
• 
  Andrew Skabar, Dennis Wollersheim, Tim Whitfort: Multi-label Classification of Gene Function using MLPs. 2234-2240

Computational Intelligence in Power Systems III - Control of FACTS Devices

• 
  Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley: An Interval Type-II Robust Fuzzy Logic Controller for a Static Compensator in a Multimachine Power System. 2241-2248
• 
  Ruben Tapia-Olvera, Juan M. Ramirez: Power Systems Neural Voltage Control by a StatCom. 2249-2254
• 
  Tridib K. Das, Sandhya R. Jetti, Ganesh K. Venayagamoorthy: Optimal Design of SVC Damping Controllers with Wide Area Measurements Using Small Population based PSO. 2255-2260
• 
  Swakshar Ray, Ganesh K. Venayagamoorthy: Real-Time Implementation of an Optimal Transient Neurocontroller for a GCSC. 2261-2266
• 
  P. Z. Haro, Juan M. Ramirez: SSSC's Adaptive Neural Control. 2267-2273
• 
  M. Tripathy, Sukumar Mishra, Ganesh K. Venayagamoorthy: Bacteria Foraging: A New Tool for Simultaneous Robust Design of UPFC Controllers. 2274-2280

Posters

• 
  Azhar Salim, Faramarz Valafar: Reconstruction of Gene Regulatory Networks from Temporal Microarray Data Using Pattern Recognition Techniques. 2281-2286
•