11. ICANN 2001: Vienna, Austria

Invited Papers

• Stephen Grossberg:
  The Complementary Brain (Abstract). 3-4
  
• Alessandro Sperduti:
  Neural Networks for Adaptive Processing of Structured Data. 5-12
  
• Florentin Wörgötter:
  Bad Design and Good Performance: Strategies of the Visual System for Enhanced Scene Analysis. 13-18
  

Data Analysis and Pattern Recognition

• Nicol N. Schraudolph:
  Fast Curvature Matrix-Vector Products. 19-26
  
• José R. Dorronsoro, Ana M. González, Carlos Santa Cruz:
  Architecture Selection in NLDA Networks. 27-32
  
• Vicente Ruiz de Angulo, Carme Torras:
  Neural Learning Invariant to Network Size Changes. 33-40
  
• Yves Grandvalet, Florence d'Alché-Buc, Christophe Ambroise:
  Boosting Mixture Models for Semi-supervised Learning. 41-48
  
• Yves Grandvalet:
  Bagging Can Stabilize without Reducing Variance. 49-56
  
• Achim F. Müller, Hans-Georg Zimmermann:
  Symbolic Prosody Modeling by Causal Retro-causal NNs with Variable Context Length. 57-64
  
• Atsushi Sato:
  Discriminative Dimensionality Reduction Based on Generalized LVQ. 65-72
  
• Hirotaka Nakayama, Masao Arakawa, Rie Sasaki:
  A Computational Intelligence Approach to Optimization with Unknown Objective Functions. 73-80
  
• Samuel Kaski, Janne Sinkkonen, Janne Nikkilä:
  Clustering Gene Expression Data by Mutual Information with Gene Function. 81-86
  
• Sepp Hochreiter, A. Steven Younger, Peter R. Conwell:
  Learning to Learn Using Gradient Descent. 87-94
  
• Anita C. Faul, Michael E. Tipping:
  A Variational Approach to Robust Regression. 95-102
  
• Stephen J. Roberts, Christopher Holmes, Dave Denison:
  Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. 103-110
  
• Sara Dolniar, Friedrich Leisch:
  Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering. 111-118
  
• Evangelos Dermatas:
  Direct Estimation of Polynomial Densities in Generalized RBF Networks Using Moments. 119-126
  
• Xavier Parra, Núria Agell, Xari Rovira:
  Generalisation Improvement of Radial Basis Function Networks Based on Qualitative Input Conditioning for Financial Credit Risk Prediction. 127-134
  
• Yoshifusa Ito, Cidambi Srinivasan:
  Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information. 135-140
  
• Mark Zlochin, Yoram Baram:
  The Bias-Variance Dilemma of the Monte Carlo Method. 141-147
  
• Takehiro Nishiyama, Kazuo Tsuchiya, Katsuyoshi Tsujita:
  A Markov Chain Monte Carlo Algorithm for the Quadratic Assignment Problem Based on Replicator Equations. 148-155
  
• Michael Weeks, Jim Austin, Anthony Moulds, Aaron Turner, Zygmunt Ulanowski, Julian Young:
  Mapping Correlation Matrix Memory Applications onto a Beowulf Cluster. 156-163
  
• Alfred Strey, Martin Bange:
  Accelerating RBF Network Simulation by Using Multimedia Extensions of Modern Microprocessors. 164-169
  
• Wai-keung Fung, Yun-Hui Liu:
  A Game-Theoretic Adaptive Categorization Mechanism for ART-Type Networks. 170-176
  
• Irwin W. Sandberg:
  Gaussian Radial Basis Functions and Inner-Product Spaces. 177-182
  
• Masahiro Tanaka:
  Mixture of Probabilistic Factor Analysis Model and Its Applications. 183-188
  
• José María Valls, Pedro Isasi, Inés María Galván:
  Deferring the Learning for Better Generalization in Radial Basis Neural Networks. 189-195
  
• Christophe Lurette, Stéphane Lecoeuche:
  Improvement of Cluster Detection and Labeling Neural Network by Introducing Elliptical Basis Function. 196-202
  
• Krista Lagus, Esa Alhoniemi, Harri Valpola:
  Independent Variable Group Analysis. 203-210
  
• Fatih Köksal, Ethem Alpaydin, Günhan Dündar:
  Weight Quantization for Multi-layer Perceptrons Using Soft Weight Sharing. 211-216
  
• Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik:
  Voting-Merging: An Ensemble Method for Clustering. 217-224
  
• James Cannady, Raymond C. Garcia:
  The Application of Fuzzy ARTMAP in the Detection of Computer Network Attacks. 225-230
  
• Chun Hung Li, Pong Chi Yuen:
  Transductive Learning: Learning Iris Data with Two Labeled Data. 231-236
  
• Achim Lewandowski, Peter Protzel:
  Approximation of Time-Varying Functions with Local Regression Models. 237-246
  

Theory

• Michael Schmitt:
  Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions. 247-252
  
• Michael Schmitt:
  Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension. 253-258
  
• Gérald Gavin:
  Generalization Performances of Perceptrons. 259-264
  
• Olivier Teytaud, Hélène Paugam-Moisy:
  Bounds on the Generalization Ability of Bayesian Inference and Gibbs Algorithms. 265-270
  
• Dörthe Malzahn, Manfred Opper:
  Learning Curves for Gaussian Processes Models: Fluctuations and Universality. 271-276
  
• Vera Kurková, Marcello Sanguineti:
  Tight Bounds on Rates of Neural-Network Approximation. 277-284
  

Kernel Methods

• Volker Tresp, Anton Schwaighofer:
  Scalable Kernel Systems. 285-291
  
• Shigeyuki Oba, Masa-aki Sato, Shin Ishii:
  On-Line Learning Methods for Gaussian Processes. 292-299
  
• Lehel Csató, Dan Cornford, Manfred Opper:
  Online Approximations for Wind-Field Models. 300-307
  
• Shigeo Abe, Takuya Inoue:
  Fast Training of Support Vector Machines by Extracting Boundary Data. 308-313
  
• Eddy Mayoraz:
  Multiclass Classification with Pairwise Coupled Neural Networks or Support Vector Machines. 314-321
  
• Liva Ralaivola, Florence d'Alché-Buc:
  Incremental Support Vector Machine Learning: A Local Approach. 322-330
  
• Koji Tsuda, Gunnar Rätsch, Sebastian Mika, Klaus-Robert Müller:
  Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers. 331-338
  
• Volker Roth:
  Sparse Kernel Regressors. 339-346
  
• Thore Graepel, Mike Goutrié, Marco Krüger, Ralf Herbrich:
  Learning on Graphs in the Game of Go. 347-352
  
• Thomas Melzer, Michael Reiter, Horst Bischof:
  Nonlinear Feature Extraction Using Generalized Canonical Correlation Analysis. 353-360
  
• Ken-ichi Amemori, Shin Ishii:
  Gaussian Process Approach to Stochastic Spiking Neurons with Reset. 361-368
  
• Olivier Teytaud, David Sarrut:
  Kernel Based Image Classification. 369-375
  
• Mohammed El-Beltagy, W. Andy Wright:
  Gaussian Processes for Model Fusion. 376-383
  
• Tony Van Gestel, Johan A. K. Suykens, Jos De Brabanter, Bart De Moor, Joos Vandewalle:
  Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines. 384-389
  
• Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller:
  Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines. 390-398
  
• Chellu Chandra Sekhar, Kazuya Takeda, Fumitada Itakura:
  Close-Class-Set Discrimination Method for Recognition of Stop_Consonant-Vowel Utterances Using Support Vector Machines. 399-404
  
• James T. Kwok:
  Linear Dependency between epsilon and the Input Noise in epsilon-Support Vector Regression. 405-410
  
• Anton Schwaighofer, Volker Tresp:
  The Bayesian Committee Support Vector Machine. 411-420
  

Topographic Mapping

• Peter Tiño, Ian T. Nabney, Yi Sun:
  Using Directional Curvatures to Visualize Folding Patterns of the GTM Projection Manifolds. 421-428
  
• Manuel Martín-Merino, Alberto Muñoz:
  Self Organizing Map and Sammon Mapping for Asymmetric Proximities. 429-435
  
• Michele Milano, Jürgen Schmidhuber, Petros Koumoutsakos:
  Active Learning with Adaptive Grids. 436-442
  
• Ignacio Díaz Blanco, Alberto B. Diez González, Abel A. Cuadrado Vega:
  Complex Process Visualization through Continuous Feature Maps Using Radial Basis Functions. 443-449
  
• Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse:
  A Soft k-Segments Algorithm for Principal Curves. 450-456
  
• Chris Charalambous, George C. Hadjinicola, Eitan Muller:
  Product Positioning Using Principles from the Self-Organizing Map. 457-463
  
• Kristof Van Laerhoven:
  Combining the Self-Organizing Map and K-Means Clustering for On-Line Classification of Sensor Data. 464-469
  
• Antonios Atsalakis, Ioannis Andreadis, Nikos Papamarkos:
  Histogram Based Color Reduction through Self-Organized Neural Networks. 470-476
  
• Motonobu Hattori, Hiroya Arisumi, Hiroshi Ito:
  Sequential Learning for SOM Associative Memory with Map Reconstruction. 477-484
  
• Jarkko Venna, Samuel Kaski:
  Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study. 485-491
  
• Méziane Yacoub, Fouad Badran, Sylvie Thiria:
  A Topological Hierarchical Clustering: Application to Ocean Color Classification. 492-499
  
• Michael Dittenbach, Dieter Merkl, Andreas Rauber:
  Hierarchical Clustering of Document Archives with the Growing Hierarchical Self-Organizing Map. 500-508
  

Independent Component Analysis

• Roland Vollgraf, Ingo Schießl, Klaus Obermayer:
  Blind Source Separation of Single Components from Linear Mixtures. 509-514
  
• Konstantinos I. Diamantaras:
  Blind Source Separation Using Principal Component Neural Networks. 515-520
  
• Rubén Martín-Clemente, José I. Acha, Carlos García Puntonet:
  Blind Separation of Sources by Differentiating the Output Cumulants and Using Newton's Method. 521-526
  
• Stephen J. Roberts, William D. Penny:
  Mixtures of Independent Component Analysers. 527-534
  
• Shotaro Akaho:
  Conditionally Independent Component Extraction for Naive Bayes Inference. 535-540
  
• Nikos A. Vlassis:
  Fast Score Function Estimation with Application in ICA. 541-546
  
• Alexander Ypma, Co Melissant, Ole Baunbæk-Jensen, Robert P. W. Duin:
  Health Monitoring with Learning Methods. 547-553
  
• Ioanna Christoyianni, Athanasios Koutras, Evangelos Dermatas, George K. Kokkinakis:
  Breast Tissue Classification in Mammograms Using ICA Mixture Models. 554-560
  
• Athanasios Koutras, Evangelos Dermatas, George K. Kokkinakis:
  Neural Network Based Blind Source Separation of Non-linear Mixtures. 561-567
  
• Nojun Kwak, Chong-Ho Choi, Jin-Young Choi:
  Feature Extraction Using ICA. 568-576
  

Signal Processing

• Edmondo Trentin, Marco Gori:
  Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model. 577-582
  
• Martin Bouchard:
  Faster Convergence and Improved Performance in Least-Squares Training of Neural Networks for Active Sound Cancellation. 583-592
  
• Ilyas Potamitis, Nikos Fakotakis, George K. Kokkinakis:
  Bayesian Independent Component Analysis as Applied to One-Channel Speech Enhancement. 593-600
  
• Bao-Liang Lu, Jonghan Shin, Michinori Ichikawa:
  Massively Parallel Classification of EEG Signals Using Min-Max Modular Neural Networks. 601-608
  
• Arthur Flexer, Herbert Bauer, Claus Lamm, Georg Dorffner:
  Single Trial Estimation of Evoked Potentials Using Gaussian Mixture Models with Integrated Noise Component. 609-616
  
• Peter Sykacek, Stephen J. Roberts, Iead Rezek, Arthur Flexer, Georg Dorffner:
  A Probabilistic Approach to High-Resolution Sleep Analysis. 617-624
  
• Vladimir Cherkassky, Steven Kilts:
  Comparison of Wavelet Thresholding Methods for Denoising ECG Signals. 625-629
  
• G. Sita, A. G. Ramakrishnan:
  Evoked Potential Signal Estimation Using Gaussian Radial Basis Function Network. 630-635
  
• Bernhard Obermaier, Gernot R. Müller, Gert Pfurtscheller:
  'Virtual Keyboard' Controlled by Spontaneous EEG Activity. 636-641
  
• David Sommer, Martin Golz:
  Clustering of EEG-Segments Using Hierarchical Agglomerative Methods and Self-Organizing Maps. 642-649
  
• Wei Lee Woon, David Lowe:
  Nonlinear Signal Processing for Noise Reduction of Unaveraged Single Channel MEG Data. 650-660
  

Time Series Processing

• Sepp Hochreiter, Michael Mozer:
  A Discrete Probabilistic Memory Model for Discovering Dependencies in Time. 661-668
  
• Felix A. Gers, Douglas Eck, Jürgen Schmidhuber:
  Applying LSTM to Time Series Predictable through Time-Window Approaches. 669-676
  
• Marc Strickert, Thorsten Bojer, Barbara Hammer:
  Generalized Relevance LVQ for Time Series. 677-683
  
• Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber:
  Unsupervised Learning in LSTM Recurrent Neural Networks. 684-691
  
• Hiroshi Murata, Takashi Onoda:
  Applying Kernel Based Subspace Classification to a Non-intrusive Monitoring for Household Electric Appliances. 692-698
  
• Alessio Plebe, Marcello A. Anile, Salvatore Rinaudo:
  Neural Networks in Circuit Simulators. 699-705
  
• Gustavo Camps-Valls, Emilio Soria-Olivas, José David Martín-Guerrero, Antonio J. Serrano-López, Juan José Pérez-Ruixo, N. Víctor Jiménez:
  Neural Networks Ensemble for Cyclosporine Concentration Monitoring. 706-711
  
• Hirotaka Inoue, Yoshinobu Fukunaga, Hiroyuki Narihisa:
  Efficient Hybrid Neural Network for Chaotic Time Series Prediction. 712-718
  
• Juan Antonio Pérez-Ortiz, Jorge Calera-Rubio, Mikel L. Forcada:
  Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks. 719-724
  
• Stanislav Kaleta, Daniel Novotný, Peter Sincak:
  Prediction Systems Based on FIR BP Neural Networks. 725-730
  
• Barbara Hammer:
  On the Generalization Ability of Recurrent Networks. 731-736
  
• Michal Cernanský, Lubica Benusková:
  Finite-State Reber Automaton and the Recurrent Neural Networks Trained in Supervised and Unsupervised Manner. 737-742
  
• Volodymyr Turchenko, Volodymyr Kochan, Anatoly Sachenko:
  Estimation of Computational Complexity of Sensor Accuracy Improvement Algorithm Based on Neural Networks. 743-748
  
• Christian Dietrich, Friedhelm Schwenker, Günther Palm:
  Fusion Architectures for the Classification of Time Series. 749-758
  

Special Session: Agent-Based Economic Modeling

• Bruce Edmonds, Scott Moss:
  The Importance of Representing Cognitive Processes in Multi-agent Models. 759-766
  
• Hans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann:
  Multi-agent FX-Market Modeling Based on Cognitive Systems. 767-774
  
• Taisei Kaizoji:
  Speculative Dynamics in a Heterogeneous-Agent Model. 775-781
  
• Andrea Gaunersdorfer, Cars H. Hommes:
  Nonlinear Adaptive Beliefs and the Dynamics of Financial Markets: The Role of the Evolutionary Fitness Measure. 782-789
  
• Harald Hruschka, Werner Fettes, Markus Probst:
  Analyzing Purchase Data by a Neural Net Extension of the Multinomial Logit Model. 790-798
  

Selforganization and Dynamical Systems

• Heiko Wersing, Helge Ritter:
  Using Maximal Recurrence in Linear Threshold Competitive Layer Networks. 799-805
  
• Jirí Síma, Pekka Orponen:
  Exponential Transients in Continuous-Time Symmetric Hopfield Nets. 806-813
  
• Hugo de Garis, Andrzej Buller, Leo de Penning, Tomasz Chodakowski, Derek Decesare:
  Initial Evolution Results on CAM-Brain Machines (CBMs). 814-819
  
• Christof Teuscher, Eduardo Sanchez:
  Self-Organizing Topology Evolution of Turing Neural Networks. 820-826
  
• Brijnesh J. Jain, Fritz Wysotzki:
  Efficient Pattern Discrimination with Inhibitory WTA Nets. 827-834
  
• Ryotaro Kamimura, Taeko Kamimura:
  Cooperative Information Control to Coordinate Competition and Cooperation. 835-842
  
• Yasuaki Kuroe, Naoki Hashimoto, Takehiro Mori:
  Qualitative Analysis of Continuous Complex-Valued Associative Memories. 843-850
  
• Nils Goerke, Florian Kintzler, Rolf Eckmiller:
  Self Organized Partitioning of Chaotic Attractors for Control. 851-856
  
• W. Andy Wright, Robert E. Smith, Martin Danek, Pillip Greenway:
  A Generalisable Measure of Self-Organisation and Emergence. 857-864
  
• Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber:
  Market-Based Reinforcement Learning in Partially Observable Worlds. 865-873
  
• W. Andy Wright:
  Sequential Strategy for Learning Multi-stage Multi-agent Collaborative Games. 874-884
  

Robotics and Control

• Volker Stephan, Horst-Michael Gross:
  Neural Architecture for Mental Imaging of Sequences Based on Optical Flow Predictions. 885-890
  
• Gunther Heidemann, Helge Ritter:
  Visual Checking of Grasping Positions of a Three-Fingered Robot Hand. 891-898
  
• Andrea Heinze, Horst-Michael Gross:
  Anticipation-Based Control Architecture for a Mobile Robot. 899-905
  
• Nadia Saadia, Yassine Amirat, Jean Pontnaut, Amar Ramdane-Cherif:
  Neural Adaptive Force Control for Compliant Robots. 906-913
  
• Michiyo Suzuki, Toru Yamamoto, Kazuo Kawada, Hiroyuki Sogo:
  A Design of Neural-Net Based Self-Tuning PID Controllers. 914-921
  
• Wai Sum Tang, Cherry Miu Ling Lam, Jun Wang:
  Kinematic Control and Obstacle Avoidance for Redundant Manipulators Using a Recurrent Neural Network. 922-929
  
• Ieroham S. Baruch, Jose Martín Flores, Federico Thomas, Ruben Garrido:
  Adaptive Neural Control of Nonlinear Systems. 930-936
  
• Jinglu Hu, Kotaro Hirasawa:
  A Hierarchical Method for Training Embedded Sigmoidal Neural Networks. 937-942
  
• Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller:
  Towards Learning Path Planning for Solving Complex Robot Tasks. 943-950
  
• Hussain N. Al-Duwaish, Ali Syed Saad Azhar:
  Hammerstein Model Identification Using Radial Basis Functions Neural Networks. 951-956
  
• Martin Hülse, Bruno Lara, Frank Pasemann, Ulrich Steinmetz:
  Evolving Neural Behaviour Control for Autonomous Robots. 957-962
  
• Anand Panangadan, Michael G. Dyer:
  Construction by Autonomous Agents in a Simulated Environment. 963-970
  
• Masazumi Katayama:
  A Neural Control Model Using Predictive Adjustment Mechanism of Viscoelastic Property of the Human Arm. 971-976
  
• Yasuhiro Wada, Yuichi Kaneko, Eri Nakano, Rieko Osu, Mitsuo Kawato:
  Multi Joint Arm Trajectory Formation Based on the Minimization Principle Using the Euler-Poisson Equation. 977-986
  

Vision and Image Processing

• Kunihiko Fukushima:
  Neocognitron of a New Version: Handwritten Digit Recognition. 987-992
  
• Alex Cozzi, Myron Flickner, Jianchang Mao, Shivakumar Vaithyanathan:
  A Comparison of Classifiers for Real-Time Eye Detection. 993-999
  
• Axel Wismüller, Oliver Lange, Dominik R. Dersch, Klaus Hahn, Gerda L. Leinsinger:
  Neural Network Analysis of Dynamic Contrast-Enhanced MRI Mammography. 1000-1005
  
• Antonios Atsalakis, Nikos Papamarkos, Charalambos Strouthopoulos:
  A New Adaptive Color Quantization Technique. 1006-1012
  
• Margarita Kuzmina, Eduard A. Manykin, Irina Surina:
  Tunable Oscillatory Network for Visual Image Segmentation. 1013-1019
  
• Seok-Woo Jang, Gye-Young Kim, Hyung-Il Choi:
  Detecting Shot Transitions for Video Indexing with FAM. 1020-1025
  
• Jan Wieghardt, Hartmut S. Loos:
  Finding Faces in Cluttered Still Images with Few Examples. 1026-1033
  
• Antonio Chella, Maria Donatella Guarino, Roberto Pirrone:
  Description of Dynamic Structured Scenes by a SOM/ARSOM Hierarchy. 1034-1041
  
• Yin Huang, Ponnuthurai N. Suganthan, Shankar M. Krishnan, Xiang Cao:
  Evaluation of Distance Measures for Partial Image Retrieval Using Self-Organizing Map. 1042-1047
  
• Xiang Cao, Ponnuthurai N. Suganthan:
  Video Sequence Boundary Detection Using Neural Gas Networks. 1048-1053
  
• George N. Votsis, Nikolaos D. Doulamis, Anastasios D. Doulamis, Nicolas Tsapatsoulis, Stefanos D. Kollias:
  A Neural-Network-Based Approach to Adaptive Human Computer Interaction. 1054-1059
  
• Anastasios D. Doulamis, Klimis S. Ntalianis, Nikolaos D. Doulamis, Stefanos D. Kollias:
  Adaptable Neural Networks for Unsupervised Video Object Segmentation of Stereoscopic Sequences. 1060-1068
  

Computational Neuroscience

• Masayuki Kikuchi, Youhei Akashi:
  A Model of Border-Ownership Coding in Early Vision. 1069-1074
  
• Christoph Kayser, Wolfgang Einhäuser, Olaf Dümmer, Peter König, Konrad P. Körding:
  Extracting Slow Subspaces from Natural Videos Leads to Complex Cells. 1075-1080
  
• Stefan D. Wilke:
  Neural Coding of Dynamic Stimuli. 1081-1086
  
• Ken-ichi Amemori, Shin Ishii:
  Resonance of a Stochastic Spiking Neuron Mimicking the Hodgkin-Huxley Model. 1087-1094
  
• Baran Çürüklü, Anders Lansner:
  Spike and Burst Synchronization in a Detailed Cortical Network Model with I-F Neurons. 1095-1102
  
• Leslie S. Smith:
  Using Depressing Synapses for Phase Locked Auditory Onset Detection. 1103-1108
  
• Robert Haschke, Jochen J. Steil, Helge Ritter:
  Controlling Oscillatory Behaviour of a Two Neuron Recurrent Neural Network Using Inputs. 1109-1114
  
• Bernd Porr, Florentin Wörgötter:
  Temporal Hebbian Learning in Rate-Coded Neural Networks: A Theoretical Approach towards Classical Conditioning. 1115-1120
  
• Tadashi Yamazaki:
  A Mathematical Analysis of a Correlation Based Model for the Orientation Map Formation. 1121-1128
  
• Emmanuel Daucé:
  Learning from Chaos: A Model of Dynamical Perception. 1129-1134
  
• Fanni Misják, Máté Lengyel, Péter Érdi:
  Episodic Memory and Cognitive Map in a Rate Model Network of the Rat Hippocampus. 1135-1140
  
• Carsten Schauer, Horst-Michael Gross:
  A Model of Horizontal 360° Object Localization Based on Binaural Hearing and Monocular Vision. 1141-1146
  
• Cornelius Weber:
  Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex. 1147-1152
  
• Yuichi Sakumura, Norio Konno, Kazuyuki Aihara:
  Markov Chain Model Approximating the Hodgkin-Huxley Neuron. 1153-1162
  

Connectionist Cognitive Science

• Stuart N. Wrigley, Guy J. Brown:
  A Neural Oscillator Model of Auditory Attention. 1163-1170
  
• Pierre-Yves Oudeyer:
  Coupled Neural Maps for the Origins of Vowel Systems. 1171-1176
  
• Massih-Reza Amini, Patrick Gallinari:
  Learning for Text Summarization Using Labeled and Unlabeled Sentences. 1177-1184
  
• Qing Ma, Bao-Liang Lu, Masaki Murata, Michinori Ichikawa, Hitoshi Isahara:
  On-Line Error Detection of Annotated Corpus Using Modular Neural Networks. 1185-1192
  
• DaeEun Kim, Jaeho Lee:
  Instance-Based Method to Extract Rules from Neural Networks. 1193-1198
  
• Victoria J. Hodge, Jim Austin:
  A Novel Binary Spell Checker. 1199-1204
  
• Neill R. Taylor, John G. Taylor:
  Neural Nets for Short Movements in Natural Language Processing. 1205-1210
  
• Timo Koskela, Jukka Heikkonen, Kimmo Kaski:
  Using Document Features to Optimize Web Cache. 1211-1216
  
• Yasuhiro Wada, Kei Ohkawa, Keiichi Sumita:
  Generation of Diversiform Characters Using a Computational Handwriting Model and a Genetic Algorithm. 1217-1224
  
• Ryotaro Kamimura, Taeko Kamimura:
  Information Maximization and Language Acquisition. 1225-1232
  
• Steve Womble, Stefan Wermter:
  A Mirror Neuron System for Syntax Acquisition. 1233-1238
  
• Douglas Eck:
  A Network of Relaxation Oscillators that Finds Downbeats in Rhythms. 1239-1247
  
• Minoru Fukumi, Yasue Mitsukura, Norio Akamatsu:
  Knowledge Incorporation and Rule Extraction in Neural Networks. 1248-1254
  

Last update Tue May 21 16:51:19 2013 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page