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ICANN 99: ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999 1

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Corporate Author:	ICANN (Veranstaltung) Edinburgh (Author)
Format:	Conference Proceeding Book
Language:	English
Published:	London IEE 1999
Series:	Institution of Electrical Engineers: IEE conference publication 470,1
Subjects:	Konferenzschrift
Online Access:	Inhaltsverzeichnis
Physical Description:	XIX, 514 S. Ill., graph. Darst.
ISBN:	0852967217

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adam_text	CONTENTS The Institution of Electrical Engineers is not, as a body, responsible for the opinions expressed by individual authors or speakers. Page No. 1 Invited Paper Products of Experts Professor G E Hinton, University College London, UK 7 Invited Paper Rapid Signal Transmission by Populations of Spiking Neurons Professor W Gerstner, Swiss Federal Institute of Technology (EPFL), Switzerland GENERATIVE MODELS 13 Scaling in a hierarchical unsupervised network Z Ghahramani, A T Korenberg and G E Hinton University College London, UK 19 Multi-layer perceptrons as nonlinear generative models for unsupervised learning: a Bayesian treatment H Lappalainen Helsinki University of Technology, Finland X Giannakopoulos IDSIA, Switzerland 25 A comparison of mixture models for density estimation Ρ Moerland IDIAP, Switzerland 31 Tree-structured belief networks as models of images С К I Williams and X Feng University of Edinburgh, UK ADAPTIVE AND NEURAL ALGORITHMS 1 37 Feedback-linearisation using neural process models J Horn Siemens AG, Germany iv 43 Natural gradient matrix momentum S Scarpetta Salemo University, INFM, Italy and Aston University, UK M Rattray University of Manchester, UK D Saad Aston University, UK 49 A framework for a discrete valued Helmholtz machine R W H Dalzell and A F Murray University of Edinburgh, UK 55 Truncated covariance matrices and Toeplitz methods in Gaussian processes A J Storkey University of Edinburgh, UK VISION 61 A model of VI visual contrast processing utilising long-range connections and recurrent interactions T Hansen and H Neumann University of Ulm, Germany 67 Neural field description suggests feedforward mechanism of state- dependent visual receptive field changes К Suder and F Wörgötter Ruhr-University, Germany T Wennekers University of Ulm, Germany 73 On the influence of threshold variability in a model of the visual cortex H Bartsch, M Stetter and К Obermayer Technische Universität Berlin, Germany 79 The variability of orientation maps in cat visual cortex M Kaschube, F Wolf and T Geisel Max-Planck-Institut für Strömungsforschung, Germany SLöwel Leibniz-Institut fur Neurobiologie, Germany SUPPORT VECTOR MACHINES 85 An information-geometrical method for improving the performance of support vector machine classifiers S-i Amari and S Wu RIKEN Brain Science Institute, Japan 91 Probabilistic interpretations and Bayesian methods for support vector machines Ρ Solüch King s College London, UK 97 Support vector learning for ordinal regression R Herbrich, T Graepel and К Obermayer Technical University of Berlin, Germany 103 Kernel-dependent Support Vector error bounds В Schölkopf GMD FIRST, Germany and Australian National University, Australia J Shawe-Taylor Royal Holloway College, University of London, UK and Australian National University, Australia A J Smola GMD FIRST, Germany and Australian National University, Australia R C Williamson Australian National University, Australia GENERAL APPLICATIONS 109 Bearance of noise on performance and distribution of computations using DTB R J Duro and J Santos Universidade da Coruña, Spain 115 λ- opt neural networks for quadratic assignment problem S Ishii Nara Institute of Science and Technology and ATR Human Information Processing Research Laboratories, Japan H Niitsuma Nara Institute of Science and Technology, Japan 121 Non-linear sub-band processing for binaural adaptive speech- enhancement A Hussain University of Dundee, UK 126 Blind source separation by dynamic graphical models H Attias University College London, UK vi HIPPOCAMPUS AND MAP FORMATION 132 A vision-driven model of hippocampal place cells and temporally asymmetric LTP-induction for action learning A Arleo and W Gerstner EPFL, Swiss Federal Institute of Technology, Switzerland 138 Spatial representations in related environments in a recurrent model of area С A3 of the rat S Káli University College London, UK and MIT, USA PDayan University College London, UK 144 Concentric spatial maps for neural network based navigation G Chao and M G Dyer University of California, Los Angeles, USA ISO Postontogenetic short-term plasticity in the somatosensory system: a neural network model U Dicke Trinity College Dublin, Ireland С W Eurich and H Schwegler Universität Bremen, Germany GENERATIVE MODELS 156 Self-organisation in the SOM with a decreasing neighbourhood function of any width J A Flanagan Helsinki University of Technology, Finland 162 Self-organisation and association for temporal coding К Amemori and S Ishii Nara Institute of Science and Technology, Japan 168 The self-organising map of attribute trees M Peura Helsinki University of Technology, Finland 174 Application of Tree Structured Self-Organising Maps in content- based image retrieval J Laaksonen, M Koskela and E Oja Helsinki University of Technology, Finland VII 180 Exploring competition and co-operation for solving the Euclidean Travelling Salesman Problem by using self-organising map E M Cochrane and J С Cochrane Imperial College, UK 186 Self-organisation of predictive representations J M Herrmann Max-Planck-Institut für Strömungsforschung, Germany К Pawelzik Universität Bremen, Germany T Geisel Max-Planck-Institut für Strömungsforschung, Germany 192 Rectified Gaussian distributions and the identification of multiple cause structure in data D Charles and C Fyfe Paisley University, UK ALGORITHMS 1 198 An adaptive network for encoding data using piecewise linear functions S P Luttrell DERA, UK 204 Fast change point detection in switching dynamics using a hidden Markov model of prediction experts J Kohlmorgen, S Lemm and K-R Müller GMD FIRST, Germany S Liehr and К Pawelzik Institute for Theoretical Physics, Germany 210 Efficient training of RBF networks for classification IT Nabney Aston University, UK 216 Discriminative coding with predictive neural networks С Chavy, В Gas and J L Zarader Université Paris VI, France 221 Multistage building learning based on misclassification measure J Rokui and H Shimodaira Japan Advanced Institute of Science and Technology, Japan 227 Improving the performance of multi-layer Perceptrons where limited training data are available for some classes C R Parikh, M J Pont and N B Jones University of Leicester, UK VIII 233 Local learning by sparse radial basis functions Y Grandvalet and C Ambroise Université de Technologie de Compiègne, France SCanu INSA, France 239 Experimental study on the precision requirements of RBF, RPROP and BPTT training U Vollmer and A Strey University of Ulm, Germany 245 Analysis of spatio-temporal patterns in associative networks of spiking neurons T Wennekers Max-Planck-Institute for Mathematics in the Sciences, Germany VISION 251 Modelling the self-organisation of directional selectivity in the primary visual cortex I Farkaš Slovak Academy of Sciences, Slovak Republic R Miikkulainen University of Texas, USA 257 Emergence of complex cell properties by decomposition of natural images into independent feature subspaces A Hyvärinen and P Hoyer Helsinki University of Technology, Finland 263 Are human scanpaths Levy flights? D Brockmann and T Geisel Max-Planck-Institut für Strömungsforschung, Germany 269 Computing stereoscopic disparity with binocular cortical simple and complex cells F Wörgötter and A Cozzi Ruhr-Universität Bochum, Germany 274 A physicalist approach to first-order analysis of optic flow fields in extrastriate cortical areas S P Sabatini, F Solari, R Carmeli, P Cavalieri and G M Bisio University of Genoa, Italy 280 Neural dynamics in a recurrent network model of primary visual cortex Z Li University College London, UK ix 286 Orientation selective cells emerge in a sparsely coding Bolztmann machine С Weber and К Obermayer Technische Universität Berlin, Germany SUPPORT VECTOR MACHINES 292 Mixtures of Gaussian process priors JCLemm Universität Münster, Germany 298 Confidence bounds for the generalisation performances of linear combination of functions G Gavin and A Elisseeff Université Lumière, France 304 Classification on proximity data with LP-machines Τ Graepel and R Herbrich Technische Universität Berlin, Germany В Schölkopf and A Smola Australian National University, Australia and GMD FIRST, Germany P Bartlett Australian National University, Australia K-R Müller GMD FIRST, Germany К Obermayer Technische Universität Berlin, Germany R Williamson Australian National University, Australia 310 Estimating the sample complexity of a multi-class discriminant model Y Guermeur Université Paris 6, France A Elisseeff and H Paugam-Moisy Université Lumière Lyon 2, France 316 The wall histogram method S Sablatnög, G K Kraetzschmar, S Enderle and G Palm University of Ulm, Germany 323 Neural networks with periodic and monotonie activation functions: a comparative study in classification problems J M Sopeña Universität de Barcelona, Spain E Romero and R Alquézar Universität Politècnica Catalunya, Spain APPLICATIONS 1 329 Using reinforcement learning for engine control R Schoknecht and M Riedmiller Universität Karlsruhe, Germany 335 Paper curl prediction- neural networks applied to the papermaking industry P J Edwards, A F Murray, G Papadopoulos, M F Gordon and A R Wallace University of Edinburgh, UK J Barnard Tullis Russell, UK 341 Towards predicting neural net control of macro-econometric multi-compartment models J A Donath, T Frontzek and R Eckmiller University of Bonn, Germany 347 Selection of features for the classification of wood board defects P A Estévez and M Fernández University of Chile, Chile R J Alcock and M S Packianather Cardiff University, UK 353 Hard contact surface tracking for industrial manipulators with orientation control and (SR) position based force control R Maaß, V Zahn, M Dapper, M Fuchs and R Eckmiller University of Bonn, Germany 359 Learning to predict a context-free language: Analysis of dynamics in recurrent hidden units M Bodén, J Wiles, В Tonkes and A Blah- University of Queensland, Australia 365 Combining multiple neural nets for visual feature selection and classification G Heidemann and H Ritter University of Bielefeld, Germany 371 Keyword selection method for characterising text document maps К Lagus and S Kaski Helsinki University of Technology, Finland xi CEREBELLUM AND HIPPOCAMPUS 377 Modelling retinal mosaic development with dendritic outgrowth and lateral cell movement S J Eglen University of Edinburgh, UK A van Ooyen Netherlands Institute for Brain Research, The Netherlands 383 Developmental evolution of dendritic morphology in a multi- compartmental neuron model A G Rust and R Adams University of Hertfordshire, UK 389 The septo-hippocampal system and anxiety: a robot simulation J F Kazer and A J С Sharkey University of Sheffield, UK 395 Capturing movement responses of single cells in the human basal ganglia using hidden Markov models N M Branston University College London, UK WEl-Deredy University College London and Liverpool John Moores University, UK 401 Modelling the frontal lobes in health and disease N R Taylor and J G Taylor King s College London, UK 407 A cortical architecture for parallel anticipation of sensorimotor sequences A Heinze, V Stephan, D Surmeli and Н -M Gross Technical University Ilmenau, Germany 413 The role of activity in corpus callosum development in the visual cortex T Hely Santa Fe Institute, USA HEORY 419 Optimal hyperplane classifier based on entropy number bound К Tsuda Electrotechnical Laboratory, Japan 425 Validity of TAP equations in neural networks MAR Leisink and H J Kappen University of Nijmegen, The Netherlands 431 New information theoretical approach to the storage capacity of neural networks with binary weights H Suyari and I Matsuba Chiba University, Japan 437 Approximate learning curves for Gaussian processes P Sollich King s College London, UK VISUAL APPLICATIONS 443 On appropriate modelling strategies for estimating land cover areas from satellite imagery H G Lewis, M S Nixon and M Brown University of Southampton, UK 449 Applications of cellular neural networks (CNN) to grey scale image filtering MAJ Moran and JAF Muñoz Universidad de Extremadura, Spain 455 Automatic contour extraction in images using a 2-D hidden Markov model О Gérard Laboratoires d Electronique Philips and Université Pierre et Marie Curie, France F d Alché-Buc Université Pierre et Marie Curie, France S Markram-Ebeid Laboratoires d Electronique Philips, France P Gallinari Université Pierre et Marie Curie, France T Artières Université de Cergy-Pontoise, France 461 A multi-resolution filling-in model for brightness perception W Sepp and H Neumann Universität Ulm, Germany TEMPORAL NETWORKS AND HARDWARE 467 Using temporal information in input features of neural networks E Fuchs and В Sick University of Passau, Germany XIII 473 Time delay estimation with hidden Markov models M Azzouzi and IT Nabney Aston University, UK 479 Spatially continuous learning systems: artificial neural networks in a bulk material continuum J E Steck and S R Skinner Wichita State University, USA A Cruz-Cabrera Digital Optics Corporation, USA M Yang and E C Behrman Wichita State University, USA 485 Clustering with spiking neurons I Opher and D Horn Tel Aviv University, Israel B Quenet ESPCI, France PCA AND ICA 491 Regression using independent component analysis, and its connection to multi-layer perceptrons A Hyvärinen Helsinki University of Technology, Finland 497 Local PCA learning with resolution-dependent mixtures of Gaussiane P Meinicke and H Ritter University of Bielefeld, Germany 503 Non-stationary independent component analysis R Everson and S J Roberts Imperial College London, UK 509 Variational principal components C M Bishop Microsoft Research, UK ADAPTIVE AND NEURAL ALGORITHMS 2 515 Rule extraction from binary neural networks M Muselli and D Liberati Istituto per і Circuiti Elettronici, Italy 521 Régularisation of mixture density networks L U Hjorth and I T Nabney Aston University, UK 527 SDTs: Sparse dynamic trees N J Adams and С К I Williams University of Edinburgh, UK 533 Régularisation of RBF-networks with the Bayesian evidence scheme D Husmeier and S J Roberts Imperial College of Science, Technology and Medicine, UK BIOLOGICAL TEMPORAL NETWORKS 539 Time-slicing: a model for cerebellar function based on synchronisation, reverberation and time windows W M Kistler and J L van Hemmen Technische Universität München, Germany 545 Avalanches of activity in a network of integrate-and-fire neurons with stochastic input С W Eurich Universität Bremen, Germany U Ernst Max-Planck-Institut für Strömungsforschung, Germany 551 Is a biological temporal learning rule compatible with learning Synfire chains? D C Sterrati University of Edinburgh, UK 557 An optimal connection radius for long-range synchronisation R Маех and E De Schutter University of Antwerp, Belgium THEORY 563 VC dimension bounds for higher-order neurons M Schmitt Ruhr-Universität Bochum, Germany 569 Local gain adaptation in stochastic gradient descent N N Schraudolph IDSIA, Switzerland xv 575 Linear programs for automatic accuracy control in regression A Smola, В Schölkopf and G Ratsch GMD FIRST, Germany and Australian National University, Australia 581 Maximising information about a noisy signal with a single non¬ linear neuron J Orwell Kingston University, UK M D Plumbley King s College London, UK 587 Simultaneous ¿/»-approximations of polynomials and derivatives on the whole space Y Ito Aichi-Gakuin University, Japan 593 Quadratic programming for learning sparse codes D Endres and P Földiák University of St Andrews, UK 597 Local minima and plateaus in multilayer neural networks K Fukumizu and S-i Amari Brain Science Institute, RIKEN, Japan APPLICATIONS 2 603 An adaptive support vector regression filter: a signal detection application R Rosipal and M Girolami University of Paisley, UK 608 Piecewise affine neural networks and nonlinear control: stability results C -А Lehalle and R Azencott Ecole Normale Supérieure de Cachan, France 613 Rule-extraction from radial basis function networks K J McGarry, J Tait, S Wermter and J Maclntyre University of Sunderland, UK 619 Chemical structure matching using correlation matrix memories J Austin, A Turner, M Turner and К Lees University of York, UK 625 The study of micro-arousals using neural network analysis of the EEG M Zamora and L Tarassenko University of Oxford, UK xvi 631 Analysis of 1С fabrication processes using self-organising maps S Rüping University of Paderborn, Germany J Müller Robert Bosch GmbH, Germany 637 Application of a reduced Hopfield neural net on dynamic routing in real time communication network L Zhang and Z Liu Beijing University of Posts and Telecommunications, People s Republic of China 643 Optimisation of surface component mounting on the printed circuit board using SOM-TSP method K Fujimura, К Obu-Cann and H Tokutaka Tottori University, Japan TEMPORAL NETWORKS AND HARDWARE HARDWARE PAPERS: 649 A neural network model for an electronic nose based on quartz- crystal microbalance sensors M Nakamura and I Sugimoto NTT Lifestyle and Environmental Technology Laboratories, Japan 655 A nonlinear oscillator network circuit for image segmentation with double-threshold phase detection H Ando, M Miyake, T Morie, M Nagata and A Iwata Hiroshima University, Japan 661 Towards an FPGA based reconfigurable computing environment for neural network implementations J Zhu, G J Milne and В К Günther University of South Australia, Australia TEMPORAL NETWORKS PAPERS: 667 Structure evolution for time-delay neural networks В Sick University of Passau, Germany 673 Efficient encodings of finite automata in discrete-time recurrent neural networks R C Carrasco, J Oncina and M Forcada Universität ďAlacant, Spain XVII 678 Recursive Bayesian modelling of time series by neural networks Τ Dodd and С Harris University of Southampton, UK 684 Computationally efficient locally-recurrent neural networks for on-line signal processing A Hussain University of Dundee, UK J J Soraghan and I Shim University of Strathclyde, UK 690 A neural network for scene segmentation based on compact astable oscillators J Cosp and J Madrenas Universität Politécnica de Catalunya, Spain PCA AND ICA 696 Independent component analysis by the PFANN neural network S Fiori and P Burrascano University of Perugia, Italy 702 On information maximisation and blind signal deconvolution ARöbel Technical University of Berlin, Germany 708 Using noise to form a minimal overcomplete basis С Fyfe and D Charles University of Paisley, UK 714 A new adaptive architecture: analogue synthesiser of orthogonal functions V Chesnokov De Montfort University, UK ALGORITHMS 2 720 Neural associative processing of document images SEM O Keefe and J Austin University of York, UK 726 Self-organisingly emerging activeness architecture realised by coherent neural networks AHirose University of Tokyo, Japan XVIII 732 Stimulus segmentation in a stochastic neural network with exogenous signals S Stroeve, В Kappen and S Gielen University of Nijmegen, The Netherlands 738 Feature extraction algorithms for pattern classification S Goodman and A Hunter University of Sunderland, UK 743 Learning error-correcting output codes from data E Alpaydin Bogaziçi University, Turkey E Mayoraz IDIAP, Switzerland 749 Selecting features in neurofuzzy modelling by multiobjective genetic algorithms С Emmanouilidis, A Hunter, J Maclntyre and С Сох University of Sunderland, UK 755 One sensor learning from another S Enderle, G Kraetzschmar, S Sablatnög and G Palm University of Ulm, Germany 761 Recurrent learning of input-output stable behaviour in function space: a case study with the Roessler attractor J J Steil and H Ritter University of Bielefeld, Germany COGNITIVE MODELLING 767 Analysing psychotherapy process time series using neural maps T Villmann and A Hessel Universität Leipzig, Germany 773 High capacity neural networks for familiarity discrimination R Bogacz, M W Brown and C Giraud-Carrier University of Bristol, UK 779 IACAPA: Modelling recognition and learning of people with an interactive activation and competition model S V Stevenage and H G Lewis University of Southampton, UK 785 Synergy of spectral and ear model features for neural speech recognition R Gemello, D Albesano and F Mana CSELT, Italy XIX 791 ESyNN - a model to abstractly emulate synchronisation in neural networks H Dürer and Τ Waschulzik Universität Bremen, Germany 797 A spatio-temporal neural network applied to visual speech recognition A R Baig, R Séguier and G Vaucher Supélec, France 803 Response of an excitatory-inhibitory neural network to external stimulation: an application to image segmentation SSinha Indian Institute of Science, India J Basak Indian Statistical Institute, India 809 Invited Paper Beyond Independent Components Dr A Hyvärinen, Helsinki University of Technology, Finland MODEL COMBINATION AND CLUSTERING 815 Deriving cluster analytic distance functions from Gaussian mixture models M E Tipping Microsoft Research, UK 821 Mixture conditional density estimation with the EM algorithm N Vlassis and B Kröse University of Amsterdam, The Netherlands 826 Covariance-based weighting for optimal combination of model predictions W D Penny, D Husmeier and S J Roberts Imperial College, UK 832 A neural-Bayesian approach to survival analysis В Bakker and T Heskes University of Nijmegen, The Netherlands 838 Classification using localised mixtures of experts P Moerland IDIAP, Switzerland XX 844 Minimum entropy data partitioning S J Roberts, R Everson and I Rezek Imperial College of Science, Technology and Medicine, UK CLASSIFICATION ALGORITHMS 850 Learning to forget: Continual prediction with LSTM F A Gers, J Schmidhuber and F Cummins IDSIA, Switzerland 856 How irrelevant inputs affect MLP pattern based learning С Goerick Ruhr-Universität Bochum, Germany 862 Neural network training using multi-channel data with aggregate labelling N McGrogan University of Oxford, UK C M Bishop Microsoft Research, UK L Tarassenko University of Oxford, UK 868 Backtracking deterministic annealing for constraint satisfaction problems H Wersing and H Ritter University of Bielefeld, Germany 874 Hypothesis verification based on classification at unequal error rates U Kreßel, F Lindner, С Wöhler and A Linz DaimlerChrysler, Germany 880 Adaptive margin Support Vector Machines for classification learning R Herbrich Royal HoĽoway, University of London, UK and Technical University of Berlin, Germany J Weston Royal Holloway, University of London, UK COGNITIVE MODELLING 886 Extended encoding/decoding of embedded structures using connectionist networks L Niklasson University of Skövde, Sweden xxi 892 Stochastic models for surface information extraction in texts M-R Amini, H Zaragoza and Ρ Gallinari LIP6 University of Paris 6, France 898 Recurrent neural network learning for text routing S Wermter, G Arevian and С Panchev University of Sunderland, UK 904 Vicarious learning in mobile neurally controlled agents: the V- MAXSON architecture F L Crabbe and M G Dyer University of California Los Angeles, USA 910 MLP emulation of N-gram models as a first step to connectionist language modelling M J Castro Universität Politècnica de Valencia, Spain F Prat Universität Jaume I, Spain F Casacuberta Universität Politècnica de Valencia, Spain 916 A constructivist neural network model of German verb inflection in agrammatic aphasia G Westermann and D Willshaw University of Edinburgh, UK M Репке Heinrich-Heine Universität Düsseldorf, Germany VECTOR QUANTISATION 922 Non-linear dimensionality reduction with input distances preservation L Garrido Universität de Barcelona, Spain S Gómez Universität Rovira i Virgili, Spain J Roca Universität de Barcelona, Spain 928 An analysis of initial state dependence in generalised LVQ A Sato NEC Corporation, Japan 934 Generative vector quantisation M Westerdijk, D Barber and W Wiegerinck University of Nijmegen, The Netherlands XXII 940 Fast winner search for SOM-based monitoring and retrieval of high-dimensional data S Kaski Helsinki University of Technology, Finland 946 A self-organising map for clustering probabilistic models J Hollmén Helsinki University of Technology, Finland V Tresp Siemens AG, Germany О Simula Helsinki University of Technology, Finland 952 Active topographic mapping of proximities M Hasenjäger and H Ritter Universität Bielefeld, Germany К Obermayer Technical University of Berlin, Germany COMMERCIAL AND MEDICAL APPLICATIONS COMMERCIAL PAPERS 958 Neural network approach to improving fault location in local telephone networks P Zhou and J Austin University of York, UK 964 A new neuro-fuzzy system for efficient ATM traffic control J J Custodio and M Tascón University of Valladolid, Spain M Merino Universidad Pontificia de Salamanca, Spain Y A Dimitriadis University of Valladolid, Spain 970 Neural-based queueing system modelling for service quality estimation in B-ISDN networks A Aussem Université Blaise Pascal, France S Rouxel and R Marie IRISA, France 976 Effectiveness of feature extraction in neural network architectures for novelty detection J F D Addison, S Wermter and J Maclntyre University of Sunderland, UK XXIII MEDICAL PAPERS 982 KBANNs and the classification of 31P MRS of malignant mammary tissues M Sordo, H Buxton and D Watson University of Sussex, UK 988 Recognition of gene regulatory sequences by bagging of neural networks G Thijs and Y Moreau Katholieke Universiteit Leuven, Belgium S Rombauts Flemish Institute for Biotechnology and University of Gent, Belgium В de Moor Katholieke Universiteit Leuven, Belgium Ρ Rouzé INRA, France and University of Gent, Belgium COMPUTATIONAL NEUROSCIENCE 994 Can fly tangential neurons be used to estimate self-motion? Μ Ο Franz and T R Neumann MPI für biologische Kybernetik, Germany M Plagge WSI, Germany H A Mallot MPI für biologische Kybernetik, Germany A Zeli WSI, Germany 1000 Influence of dendritic morphology on axonal competition A van Ooyen Netherlands Institute for Brain Research, The Netherlands D J Willshaw University of Edinburgh, UK 1006 The effects of intrinsic noise on pattern recognition in a model pyramidal cell B P Graham University of Edinburgh, UK 1012 Understanding the PSTH response to synaptic input A Herrmann and W Gerstner Swiss Federal Institute of Technology (EPFL), Switzerland xxiv 1017 Statistical models and sensory attention Ρ Dayan University College London, UK R S Zemel University of Arizona, USA 1023 Components of brain activity - data analysis for fMRI S Dodel, J M Herrmann and T Geisel Max Planck Institute for Fluid Dynamics, Germany xxv
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institution	BVB
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physical	XIX, 514 S. Ill., graph. Darst.
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series	Institution of Electrical Engineers: IEE conference publication
series2	Institution of Electrical Engineers: IEE conference publication IEE conference publications
spelling	ICANN (Veranstaltung) 9 1999 Edinburgh Verfasser (DE-588)10005805-X aut ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999 1 London IEE 1999 XIX, 514 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Institution of Electrical Engineers: IEE conference publication 470,1 IEE conference publications ... (DE-588)1071861417 Konferenzschrift gnd-content (DE-604)BV013052043 1 Institution of Electrical Engineers: IEE conference publication 470,1 (DE-604)BV001889735 470,1 Digitalisierung TU Muenchen application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008893733&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999 Institution of Electrical Engineers: IEE conference publication
subject_GND	(DE-588)1071861417
title	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999
title_auth	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999
title_exact_search	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999
title_full	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999 1
title_fullStr	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999 1
title_full_unstemmed	ICANN 99 ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999 1
title_short	ICANN 99
title_sort	icann 99 ninth international conference on artificial neural networks 7 10 september 1999
title_sub	ninth International Conference on Artificial Neural Networks ; 7 - 10 September 1999
topic_facet	Konferenzschrift
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008893733&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV013052043 (DE-604)BV001889735
work_keys_str_mv	AT icannveranstaltungedinburgh icann99ninthinternationalconferenceonartificialneuralnetworks710september19991

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