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Artificial neural networks and neural information processing — ICANN/ICONIP 2003. Joint international conference ICANN/ICONIP 2003, Istanbul, Turkey, 26–29, 2003. Proceedings. (English) Zbl 1029.00055
Lecture Notes in Computer Science. 2714. Berlin: Springer. xxii, 1188 p. (2003).

Show indexed articles as search result.

The articles of this volume will be reviewed individually. The preceding conference has been reviewed (see Zbl 1008.68683).
Indexed articles:
Serpen, Gürsel, Adaptive Hopfield network, 3-10 [Zbl 1037.68711]
Inoue, Hirotaka; Narihisa, Hiroyuki, Effective pruning method for a multiple classifier system based on self-generating neural networks, 11-18 [Zbl 1037.68658]
Henderson, James, Structural bias in inducing representations for probabilistic natural language parsing, 19-26 [Zbl 1037.68651]
Matsuyama, Yasuo; Katsumata, Naoto; Kawamura, Ryo, Independent component analysis minimizing convex divergence, 27-34 [Zbl 1037.68683]
Verikas, Antanas; Bacauskiene, Marija; Malmqvist, Kerstin, Selecting salient features for classification committees, 35-42 [Zbl 1037.68727]
Buchtala, Oliver; Hofmann, Alexander; Sick, Bernhard, Fast and efficient training of RBF networks, 43-51 [Zbl 1037.68622]
Liou, Cheng-Yuan; Sou, Un-Cheong, Loading temporal associative memory using the neuronic equation, 52-59 [Zbl 1037.68676]
Weng, Sebastian; Steil, Jochen J., Learning compatibility functions for feature binding and perceptual grouping, 60-67 [Zbl 1037.68732]
Choi, Seungjin, Differential ICA, 68-75 [Zbl 1037.68627]
Barutçuoğlu, Zafer; Alpaydin, Ethem, A comparison of model aggregation methods for regression, 76-83 [Zbl 1037.68616]
Fontenla-Romero, Oscar; Erdogmus, Deniz; Principe, J. C.; Alonso-Betanzos, Amparo; Castillo, Enrique, Linear least-squares based methods for neural networks learning, 84-91 [Zbl 1037.68636]
Pfister, Jean-Pascal; Barber, David; Gerstner, Wulfram, Optimal Hebbian learning: A probabilistic point of view, 92-98 [Zbl 1037.68707]
Kamimura, Ryotaro, Competitive learning by information maximization: Eliminating dead neurons in competitive learning, 99-106 [Zbl 1037.68662]
Agakov, Felix V.; Barber, David, Approximate learning in temporal hidden Hopfield models, 107-114 [Zbl 1037.68606]
Huang, Kaizhu; King, Irwin; Lyu, Michael R., Finite mixture model of bounded semi-naive Bayesian networks classifier, 115-122 [Zbl 1037.68656]
Yoshimoto, Junichiro; Ishii, Shin; Sato, Masa-aki, System identification based on online variational Bayes method and its application to reinforcement learning, 123-131 [Zbl 1037.68735]
Zhang, Kun; Chan, Lai-Wan, Dimension reduction based on orthogonality – A decorrelation method in ICA, 132-139 [Zbl 1037.68736]
Juszczak, Piotr; Duin, Robert P. W., Selective sampling methods in one-class classification problems, 140-148 [Zbl 1037.68661]
Paccanaro, Alberto, Learning distributed representations of high-arity relational data with non-linear relational embedding, 149-156 [Zbl 1037.68703]
Oohira, Takayuki; Yamauchi, Koichiro; Omori, Takashi, Meta-learning for fast incremental learning, 157-164 [Zbl 1037.68701]
Cheung, Yiu-ming, Expectation-MiniMax approach to clustering analysis, 165-172 [Zbl 1037.68626]
Micheli, Alessio; Sona, Diego; Sperduti, Alessandro, Formal determination of context in contextual recursive cascade correlation networks, 173-180 [Zbl 1037.68687]
Byorick, Jeffrey; Polikar, Robi, Confidence estimation using the incremental learning algorithm, Learn++, 181-188 [Zbl 1037.68623]
da Silva, Ivan Nunes, Stability and convergence analysis of a neural model applied in nonlinear systems optimization, 189-197 [Zbl 1037.68697]
Ikeda, Kazushi, Generalization error analysis for polynomial kernel methods – algebraic geometrical approach, 201-208 [Zbl 1037.68657]
Matías, José M.; González-Manteiga, Wenceslao, Regularized kriging: The support vectors method applied to kriging, 209-216 [Zbl 1037.68681]
Muñoz, Alberto; Martín de Diego, Isaac; Moguerza, Javier M., Support vector machine classifiers for asymmetric proximities, 217-224 [Zbl 1037.68692]
Uçar, Aysegül; Demir, Yakup; Güzelis, Cüneyt, Fuzzy model identification using support vector clustering method, 225-233 [Zbl 1037.68725]
Lorena, Ana Carolina; de Carvalho, André C. P. L. F., Human splice site identification with multiclass support vector machines and bagging, 234-241 [Zbl 1037.68678]
Weiss, Olaf; Ziehe, Andreas; Herzel, Hanspeter, Optimizing property codes in protein data reveals structural characteristics, 245-252 [Zbl 1037.68730]
Ito, Yoshifusa; Srinivasan, Cidambi, Multicategory Bayesian decision using a three-layer neural network, 253-261 [Zbl 1037.68659]
Mavroudi, Seferina; Dragomir, Andrei; Papadimitriou, Stergios; Bezerianos, Anastasios, Integrating supervised and unsupervised learning in self organizing maps for gene expression data analysis, 262-270 [Zbl 1037.68684]
Oba, Shigeyuki; Sato, Masa-aki; Ishii, Shin, Prior hyperparameters in Bayesian PCA, 271-279 [Zbl 1037.68699]
Corchado, Emilio; Fyfe, Colin, Relevance and kernel self-organising maps, 280-287 [Zbl 1037.68629]
Sung, JaeMo; Bang, Sung-Yang, Hierarchical Bayesian network for handwritten digit recognition, 291-298 [Zbl 1037.68715]
Jain, Brijnesh J.; Wysotzki, Fritz, A novel neural network approach to solve exact and inexact graph isomorphism problems, 299-306 [Zbl 1037.68660]
Neumann, Peter; Sick, Bernhard; Arndt, Dirk; Gersten, Wendy, Evolutionary optimisation of RBF network architectures in a direct marketing application, 307-315 [Zbl 1037.68695]
Hofmann, Alexander; Schmitz, Carsten; Sick, Bernhard, Intrusion detection in computer networks with neural and fuzzy classifiers, 316-324 [Zbl 1037.68655]
Knoblauch, Andreas, Optimal matrix compression yields storage capacity 1 for binary Willshaw associative memory, 325-332 [Zbl 1037.68668]
de Ridder, Dick; Kouropteva, Olga; Okun, Oleg; Pietikäinen, Matti; Duin, Robert P. W., Supervised locally linear embedding, 333-341 [Zbl 1037.68738]
Tax, David M. J.; Müller, Klaus-R., Feature extraction for one-class classification, 342-349 [Zbl 1037.68718]
Lecoeuche, Stéphane; Lurette, Christophe, Auto-adaptive and dynamical clustering neural network, 350-358 [Zbl 1037.68673]
Grabczewski, Krzysztof; Jankowski, Norbert, Transformations of symbolic data for continuous data oriented models, 359-366 [Zbl 1037.68644]
Acciani, Giuseppe; Fornarelli, Girolamo; Liturri, Luciano, Comparing fuzzy data sets by means of graph matching technique, 367-374 [Zbl 1037.68605]
Cutzu, Florin, How to do multi-way classification with two-way classifiers, 375-382 [Zbl 1037.68631]
Wersing, Heiko; Eggert, Julian; Körner, Edgar, Sparse coding with invariance constraints, 385-392 [Zbl 1037.68733]
Fukushima, Kunihiko, Restoring partly occluded patterns: A neural network model with backward paths, 393-400 [Zbl 1037.68638]
Matsuda, Yoshitatsu; Yamaguchi, Kazunori, The InfoMin criterion: An information theoretic unifying objective function for topographic mappings, 401-408 [Zbl 1037.68682]
Morita, Satoru, Short-term memory optical flow image, 409-416 [Zbl 1037.68691]
Miravet, Carlos; Rodríguez, Francisco B., A hybrid MLP-PNN architecture for fast image superresolution, 417-424 [Zbl 1037.68689]
Bax, Ingo; Bekel, Holger; Heidemann, Gunther, Recognition of gestural object reference with auditory feedback, 425-432 [Zbl 1037.68617]
Ozalevli, Erhan; Higgins, Charles M., Multi-chip implementation of a biomimetic VLSI vision sensor based on the Adelson-Bergen algorithm, 433-440 [Zbl 1037.68702]
Le, Quan; Bengio, Samy, Client dependent GMM-SVM models for speaker verification, 443-451 [Zbl 1037.68672]
Deviren, Murat; Daoudi, Khalid, Frequency and wavelet filtering for robust speech recognition, 452-460 [Zbl 1037.68633]
Hoffmann, Heiko; Möller, Ralf, Unsupervised learning of a kinematic arm model, 463-470 [Zbl 1037.68654]
Yamamoto, Toru; Kurozumi, Ryota; Fujisawa, Shoichiro, A design of CMAC based intelligent PID controllers, 471-478 [Zbl 1037.68734]
Schoknecht, Ralf; Riedmiller, Martin, Learning to control at multiple time scales, 479-487 [Zbl 1037.68710]
Muthuraman, Sethuraman; Maxwell, Grant; MacLeod, Christopher, The evolution of modular artificial neural networks for legged robot control, 488-495 [Zbl 1037.68693]
te Boekhorst, Rene; Lungarella, Max; Pfeifer, Rolf, Dimensionality reduction through sensory-motor coordination, 496-503 [Zbl 1037.68739]
Chokshi, Kaustubh; Wermter, Stefan; Weber, Cornelius, Learning localisation based on landmarks using self-organisation, 504-511 [Zbl 1037.68628]
Long, Zhi-ying; Yao, Li; Zhao, Xiao-jie; Pei, Liu-qing; Xue, Gui; Dong, Qi; Peng, Dan-ling, Spatial independent component analysis of multitask-related activation in fMRI data, 515-522 [Zbl 1037.68677]
Aussem, Alex, Closed loop stability of FIR-recurrent neural networks, 523-529 [Zbl 1037.68612]
Sohn, Jun-Il; Lee, Minho, Selective noise cancellation using independent component analysis, 530-537 [Zbl 1037.68713]
Harrington, Edward, Expert mixture methods for adaptive channel equalization, 538-545 [Zbl 1037.68649]
Maeda, Michiharu, A relaxation algorithm influenced by self-organizing maps, 546-553 [Zbl 1037.68679]
Doğan, Hatice; Güzelis, Cüneyt, A gradient network for vector quantization and its image compression applications, 554-561 [Zbl 1037.68634]
Zoeter, Onno; Heskes, Tom, Multi-scale switching linear dynamical systems, 562-569 [Zbl 1037.68737]
Lendasse, Amaury; Wertz, Vincent; Verleysen, Michel, Model selection with cross-validations and bootstraps – application to time series prediction with RBFN models, 573-580 [Zbl 1037.68675]
Pal, Srimanta; Das, Jyotirmay; Majumdar, Kausik, A hybrid neural architecture and its application to temperature prediction, 581-588 [Zbl 1037.68704]
Miazhynskaia, Tatiana; Dorffner, Georg; Dockner, Engelbert J., Risk management application of the recurrent mixture density network models, 589-596 [Zbl 1037.68686]
Vidal, Carmen; Suárez, Alberto, Hierarchical mixtures of autoregressive models for time-series modeling, 597-604 [Zbl 1037.68728]
Wen, Dou; Yan, Jia; Zhong, Liu; Peng, Zou, A simple constructing approach to build P2P global computing overlay network, 607-614 [Zbl 1037.68731]
Lajbcygier, Paul, Option pricing with the product constrained hybrid neural network, 615-621 [Zbl 1037.68671]
Lehtimäki, Pasi; Raivio, Kimmo; Simula, Olli, Self-organizing operator maps in complex system analysis, 622-629 [Zbl 1037.68674]
Güneş, Filiz; Cengiz, Yavuz, Optimization of a microwave amplifier using neural performance data sheets with genetic algorithms, 630-637 [Zbl 1037.68648]
Tang, Tong Boon; Chen, Hsin; Murray, Alan F., Adaptive stochastic classifier for noisy pH-ISFET measurements, 638-645 [Zbl 1037.68716]
Garfield, Sheila; Wermter, Stefan, Comparing support vector machines, recurrent networks, and finite state transducers for classifying spoken utterances, 646-653 [Zbl 1037.68641]
Prudêncio, Ricardo B. C.; Ludermir, Teresa B., Selecting and ranking time series models using the NOEMON approach, 654-661 [Zbl 1037.68708]
Terzi, Serdal; Saltan, Mehmet; Yildirim, Tulay, Optimization of the deflection basin by genetic algorithm and neural network approach, 662-669 [Zbl 1037.68720]
Hernández-Espinosa, Carlos; Fernández-Redondo, Mercedes; Ortiz-Gómez, Mamen, Inversion of a neural network via interval arithmetic for rule extraction, 670-677 [Zbl 1037.68652]
Park, Sang-Jae; Ban, Sang-Woo; Shin, Jang-Kyoo; Lee, Minho, Implementation of visual attention system using bottom-up saliency map model, 678-685 [Zbl 1037.68705]
Chen, Y. H.; Tseng, C. L.; Fu, Hsin-Chia; Pao, H. T., A self-growing probabilistic decision-based neural network for anchor/speaker identification, 686-694 [Zbl 1037.68625]
Albayrak, Songül, Unsupervised clustering methods for medical data: An application to thyroid gland data, 695-701 [Zbl 1037.68607]
Blekas, Konstantinos; Fotiadis, Dimitrios I.; Likas, Aristidis, Protein sequence classification using probabilistic motifs and neural networks, 702-709 [Zbl 1037.68621]
Becerikli, Yasar; Oysal, Yusuf; Konar, Ahmet Ferit, On a dynamic wavelet network and its modeling application, 710-718 [Zbl 1037.68618]
Cambio, Roberta; Hendry, David C., Low power digital neuron for SOM implementations, 721-728 [Zbl 1037.68624]
Kawaguchi, Masashi; Kondo, Kazuyuki; Jimbo, Takashi; Umeno, Masayoshi, Direction selective two-dimensional analog circuits using biomedical vision model, 729-736 [Zbl 1037.68665]
Beiu, Valeriu; Avedillo, Maria J.; Quintana, Jose M., Review of capacitive threshold gate implementations, 737-744 [Zbl 1037.68620]
Beiu, Valeriu, Constructive threshold logic addition. A synopsis of the last decade, 745-752 [Zbl 1037.68619]
Türel, Özgür; Likharev, Konstantin, CrossNets: Neuromorphic networks for nanoelectronic implementation, 753-760 [Zbl 1037.68723]
Greco, Alberto; Riga, Thomas; Cangelosi, Angelo, The acquisition of new categories through grounded symbols: An extended connectionist model, 763-770 [Zbl 1037.68645]
van der Voort van der Kleij, Gwendid T.; de Kamps, Marc; van der Velde, Frank, A neural model of binding and capacity in visual working memory, 771-778 [Zbl 1037.68740]
Kursin, Andrei, Neural network: Input anticipation may lead to advanced adaptation properties, 779-785 [Zbl 1037.68670]
Ohigashi, Yu; Omori, Takashi; Morikawa, Koji; Oka, Natsuki, Acceleration of game learning with prediction-based reinforcement learning – toward the emergence of planning behavior, 786-793 [Zbl 1037.68700]
Humphries, Mark D.; Prescott, Tony J.; Gurney, Kevin N., The interaction of recurrent axon collateral networks in the basal ganglia, 797-804 [Zbl 1049.92501]
Hafner, Verena Vanessa; Fend, Miriam; Lungarella, Max; Pfeifer, Rolf; König, Peter; Körding, Konrad Paul, Optimal coding for naturally occurring whisker deflections, 805-812 [Zbl 1049.92500]
Weber, Cornelius; Wermter, Stefan, Object localisation using laterally connected “what” and “where” associator networks, 813-820 [Zbl 1049.91520]
Hirose, Akira; Hamano, Toshihiko, Influence of membrane warp on pulse propagation time, 821-829 [Zbl 1049.92513]
Papliński, Andrew P.; Gustafsson, Lennart, Detailed learning in narrow fields – towards a neural network model of autism, 830-838 [Zbl 1049.92508]
Mayor, Julien; Gerstner, Wulfram, Online processing of multiple inputs in a sparsely-connected recurrent neural network, 839-845 [Zbl 1037.68685]
Jolivet, Renaud; Lewis, Timothy J.; Gerstner, Wulfram, The spike response model: A framework to predict neuronal spike trains, 846-853 [Zbl 1049.92009]
Casile, Antonino; Giese, Martin, Roles of motion and form in biological motion recognition, 854-862 [Zbl 1049.92006]
Tsapatsoulis, Nicolas; Wallace, Manolis; Kasderidis, Stathis, Improving the performance of resource allocation networks through hierarchical clustering of high-dimensional data, 867-874 [Zbl 1037.68722]
Apolloni, B.; Brega, A.; Malchiodi, D.; Palmas, G.; Zanaboni, A. M., Learning rule representations from Boolean data, 875-882 [Zbl 1037.68609]
Nürnberger, Andreas; Detyniecki, Marcin, Weighted self-organizing maps: Incorporating user feedback, 883-890 [Zbl 1037.68698]
Gallinari, Patrick; Bidel, Sylvain; Lemoine, Laurent; Piat, Frédéric; Artières, Thierry, Classification and tracking of hypermedia navigation patterns, 891-900 [Zbl 1037.68639]
Gelenbe, Erol; Núñez, Arturo, Self-aware networks and quality of service, 901-908 [Zbl 1037.68642]
Kasderidis, Stathis; Taylor, John G.; Tsapatsoulis, Nicolas; Malchiodi, Dario, Drawing attention to the dangerous, 909-916 [Zbl 1037.68664]
Martin, Trevor P., ASK – acquisition of semantic knowledge, 917-924 [Zbl 1037.68680]
Pertselakis, Minas; Frossyniotis, Dimitrios; Stafylopatis, Andreas, An adaptable Gaussian neuro-fuzzy classifier, 925-932 [Zbl 1037.68706]
Tzouvaras, Vassilis; Stamou, Giorgos; Kollias, Stefanos, Knowledge refinement using fuzzy compositional neural networks, 933-940 [Zbl 1037.68724]
Minami, Motoi; Hirose, Akira, Phase singular points reduction by a layered complex-valued neural network in combination with constructive Fourier synthesis, 943-950 [Zbl 1037.68688]
Kinjo, Mitsunaga; Sato, Shigeo; Nakajima, Koji, Quantum adiabatic evolution algorithm for a quantum neural network, 951-958 [Zbl 1037.68667]
Suksmono, Andriyan Bayu; Hirose, Akira, Adaptive beamforming by using complex-valued multi layer perceptron, 959-966 [Zbl 1037.68714]
Vaucher, Gilles, A complex-valued spiking machine, 967-976 [Zbl 1037.68726]
Nemoto, Iku, The behavior of the network consisting of two complex-valued Nagumo-Sato neurons, 977-984 [Zbl 1037.68694]
Kuroe, Yasuaki; Yoshida, Mitsuo; Mori, Takehiro, On activation functions for complex-valued neural networks – existence of energy functions, 985-992 [Zbl 1037.68669]
Nitta, Tohru, The computational power of complex-valued neuron, 993-1000 [Zbl 1037.68696]
Gündüz, Şule; Özsu, M. Tamer, Recommendation models for user accesses to web pages, 1003-1010 [Zbl 1037.68647]
Karakahya, Hakan; Yazgan, Bingül; Ersoy, Okan K., A spectral-spatial classification algorithm for multispectral remote sensing data, 1011-1017 [Zbl 1037.68663]
Tansel, Ibrahim N.; Singh, Reen Nripjeet; Chen, Peng; Kropas-Hughes, Claudia V., Neural network based material identification and part thickness estimation from two radiographic images, 1018-1025 [Zbl 1037.68717]
Bao, W. Y.; Chen, P.; Tansel, I. N.; Reen, N. S.; Yang, S. Y.; Rincon, D., Selection of optimal cutting conditions by using the genetically optimized neural network system (GONNS), 1026-1032 [Zbl 1037.68615]
Gueorguieva, Natacha; Valova, Iren, Building RBF neural network topology through potential functions, 1033-1040 [Zbl 1037.68646]
Bayrak, C.; Chen, Z.; Norton, J.; Preissl, H.; Lowery, C.; Eswaran, H.; Wilson, J. D., Use of magnetomyographic (MMG) signals to calculate the dependency properties of the active sensors in myometrial activity monitoring, 1041-1048 [Zbl 1049.92512]
Daud, Taher; Zebulum, Ricardo; Duong, Tuan; Ferguson, Ian; Padgett, Curtis; Stoica, Adrian; Thakoor, Anil, Speed enhancement with soft computing hardware, 1049-1056 [Zbl 1037.68632]
Göksu, Hüseyin; Wunsch, Donald C. II, Neural networks applied to electromagnetic compatibility (EMC) simulations, 1057-1063 [Zbl 1037.68643]
Shakev, Nikola G.; Topalov, Andon V.; Kaynak, Okyay, Sliding mode algorithm for online learning in analog multilayer feedforward neural networks, 1064-1072 [Zbl 1037.68712]
Yang, Jack Y.; Yang, Mary Qu; Ersoy, Okan K., Exploring protein functional relationships using genomic information and data mining techniques, 1073-1080 [Zbl 1049.92506]
Bedingfield, Susan E.; Smith, Kate A., Predicting bad credit risk: An evolutionary approach, 1081-1088 [Zbl 1049.91510]
Fischer, Amber D.; Dagli, Cihan H., Indirect differentiation of function for a network of biologically plausible neurons, 1089-1099 [Zbl 1037.68635]
Gao, X. W.; Podladchikova, L.; Shaposhnikov, D., Application of vision models to traffic sign recognition, 1100-1105 [Zbl 1037.68640]
Raouzaiou, Amaryllis; Ioannou, Spiros; Karpouzis, Kostas; Tsapatsoulis, Nicolas; Kollias, Stefanos; Cowie, Roddy, An intelligent scheme for facial expression recognition, 1109-1116 [Zbl 1037.68709]
Athanaselis, Theologos; Fotinea, Stavroula-Evita; Bakamidis, Stelios; Dologlou, Ioannis; Giannopoulos, Georgios, Signal enhancement for continuous speech recognition, 1117-1124 [Zbl 1037.68611]
Fotinea, Stavroula-Evita; Bakamidis, Stelios; Athanaselis, Theologos; Dologlou, Ioannis; Carayannis, George; Cowie, Roddy; Douglas-Cowie, E.; Fragopanagos, N.; Taylor, John G., Emotion in speech: Towards an integration of linguistic, paralinguistic, and psychological analysis, 1125-1132 [Zbl 1036.68532]
Taylor, John G.; Fragopanagos, N.; Cowie, Roddy; Douglas-Cowie, E.; Fotinea, Stavroula-Evita; Kollias, Stefanos, An emotional recognition architecture based on human brain structure, 1133-1140 [Zbl 1037.68719]
Won, Hong-Hee; Cho, Sung-Bae, Neural network ensemble with negatively correlated features for cancer classification, 1143-1150 [Zbl 1049.92511]
Shi, S. Y. M.; Suganthan, P. N., Feature analysis and classification of protein secondary structure data, 1151-1158 [Zbl 1049.92505]
Chung, I-Fang; Huang, Chuen-Der; Shen, Ya-Hsin; Lin, Chin-Teng, Recognition of structure classification of protein folding by NN and SVM hierarchical learning architecture, 1159-1167 [Zbl 1049.92502]
Huang, Chuen-Der; Chung, I-Fang; Pal, Nikhil Ranjan; Lin, Chin-Teng, Machine learning for multi-class protein fold classification based on neural networks with feature gating, 1168-1175 [Zbl 1049.92503]
Pal, Nikhil Ranjan; Chakraborty, Debrup, Some new features for protein fold prediction, 1176-1183 [Zbl 1049.92504]
MSC:
00B25 Proceedings of conferences of miscellaneous specific interest
68-06 Proceedings, conferences, collections, etc. pertaining to computer science
68T05 Learning and adaptive systems in artificial intelligence
92B20 Neural networks for/in biological studies, artificial life and related topics
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