ICANN '93Proceedings of the International Conferenceon Artificial Neural NetworksAmsterdam, The Netherlands13-16 September 1993

Edited by

Stan Gielen and Bert Kappen

Springer-VerlagLondon Berlin Heidelberg New YorkParis Tokyo Hong KongBarcelona Budapest

Contents

PLENARY CONTRIBUTIONS

A. AertsenDynamic coupling in cortical neural networks

G. E. Hinton and D. van CampKeeping neural networks simple

3

11

PRINCIPLES FROM NEUROBIOLOGY

Memory and selforganization—oral contributions

A. Treves and E. T. Rolls (invited prfper)The autoassociative hypothesis places constraints on hippocampalorganization 21

M. Nakao, Y. Mizutani, K. Watanabe and M. YamamotoMetastability of network attractor and dream sleep 27

S. Wacquant, F. Joublin, F. Spengler, B. Godde, H. R. DinseSomatosensory cortical maps: reorganization following post-ontogenetic plasticity—experiments and theory 31

D. /. Amit and N. BruneiAdequate input for learning in attractor neural networks 37

Memory and selforganization—poster contributions

B. Bruckner and W. ZanderNeurobiological modelling and structured neural networks 43

H. Ikeno and S. UsuiModel analysis of associative learning in the photoreceptor ofmarine mollusc, Hermissenda Crassicornis 47

/. L. Velay, J. C. Gilhodes, B. Ans and Y. CoitonA neural network model for motor shapes learning andprogramming 51

A. Murciano and J. ZamoraLearning through adaptive value: a model working in a variableenvironment 55

£. Lebert and R. H. PhafImproving categorization with CALM maps 59

viii Contents

D. Heinke and H.-M. GrossA simple self-organizing neural network architecture for selectivevisual attention 63

R. Moeller and H.-M. GrossDetection of coincidences and generation of hypotheses—aproposal for an elementary cortical function 67

F. H. GuentherDIVA: a self-organizing neural network model for motorequivalent speech production 71

M. M. van HulleAdaptive non-uniform A/D conversion achieved with anunsupervised learning rule maximizing information-theoreticentropy 75

G. Tambouratzis and T. ) . StonhamOptimal topology-preservation using self-organising logical neuralnetworks 76

M. H. Spigt, D. S. Bree and M. NielenIncorporation of neurobiological aspects of Aplysia's associativeconditioning in neural networks for on-line pattern detection 80

F. A. MonacoDescription on the use of the autogenerative nodal memory model(ANM) as controlling element of an autonomously responsivesystem 81

S. /. MrchevHuman memory—neurocomputer (MeNeCo project): structure forreverbation of the information in N-peaked nets (in STMemory) .... 82

Visuo-motor interaction—oral contributions

/. van Opstal and B. Kappen (invited paper)Neural representation of saccadic eye movements in monkeysuperior colliculus 84

D. Bullock, D. Greve, S. Grossberg and F. H. GuentherA self-organizing neural network for learning a body-centeredinvariant representation of 3-D target position 90

K. Kopecz, C. Engels and G. SchonerDynamic field approach to target selection in gaze control 96

/. F. M. van Brederode and W. ]. SpainDifferences in synaptic input and excitability between superficialand deep pyramidal cells in the cat sensorimotor cortex 102

Visuo-motor interaction—poster contributions

H.-M. R. ArnoldiAn adaptive sensory fusion approach for the superior colliculus .... 107

R. Hosaka and T. NaganoA neural network model for spatial information representation I l l

Contents ix

P. Morasso, V. Sanguineti and T. TsujiA dynamical model for the generation of curved trajectories 115

L. N. KaliaFunctional organisation in the cerebellum 119

D. G. Ruegg, L. Studer and J.-P. GabrielActivation and contraction of a muscle 120

The visual system—oral contributions

O. Sporns, G. Tononi and G. M. Edelman (invited paper)Correlated neuronal activity and behaviour 125

F. Wolf, K. Pawelzik, T. Geisel, D.-S. Kim and T. BonhoefferMap structure from pinwheel position 131

H.-U. Bauer, K. Pawelzik and T. GeiselEmergence of transient oscillations in an ensemble of neurons 136

T. Pomierski, H.-M. Gross and D. WendtA distributed multicolumnar system for primary cortical analysis ofreal-world scenes 142

The visual system—poster contributions

A. ] . NoestSingularities in cortical orientation and direction maps: vortices,strings and bubbles 149

P. GrandguillaumeA new model for spatial frequency and orientation tuning in thevisual cortex based on delayed inputs from the retina 153

E. Nelle and F. WorgotterCascaded intracortical inhibition: modeling connection schemes ona large scale simulator 157

K. Pawelzik, J. Deppisch and T. GeiselHidden assembly dynamics and correlated neuronal responses 161

G. Bugmann and J. G. TaylorA model for latencies in the visual system 165

F. ]. Diaz Pernas and J. Lopez CoronadoA neural architecture for textured color image segmentation andrecognition 169

Dynamics of single neurons—oral contributions

L. F. Abbott, G. LeMasson, M. Siegel and E. Murder (invited paper)Activity-dependent modification of intrinsic neuronal properties ... 171

A. van Ooyen and /. van PeltImplications of and activity-dependent neurite outgrowth fordeveloping neural networks 177

C. FyfePCA properties of interneurons 183

x Contents

H. R. Dinse, C. E. Schreiner, F. Spengler, B. Godde and B. HartfielTemporal distributed processing-TDP: a time-based processingscheme accounts for time dependent receptive fields andrepresentational maps 189

Dynamics of single neurons—poster contributions

V. Ldpez, ]. A. Siguenza, J. R. Dorronsoro and S. Carrillo-MenendezStochastic specificity in neural interaction 196

R. Lahoz-Beltra, A. Murciano, J. Zamora, F. Vico, ]. M. Jerez,S. R. Hameroffand } . E. DayhoffA computer simulation model of backwards feedback acrosssynapse via arachidonic acid 200

G. VoucherStudy of a self-learning artificial neuron model 204

N. Katayatna, M. Nakao, Y. Mizutani and M. YamamotoSimulation study on calcium-activated dynamics of compartmentdendrite model 205

A. J. Klaassen and ]. HoekstraOn the adaptive capabilities of pulse-coded cable neurons 206

/. HoekstraA local approximation of the cable equation for implementing alocal interaction model 207

V. Kamiyama, T. Suzuki, H. Ishii and S. UsuiEffect of glutamate uptake on the response dynamics of the retinalhorizontal cell 208

ROBOTICS

Robot vision—oral contributions

F. C. A. Groen, B. ]. A. Krb'se and A. J. Noest (invited paper)Neural networks for robot eye-hand coordination 211

P. KoistinenUnsupervised formation of feature detectors using residual inputs . 219

M. Proestnans, E. Pauwels, L. ]. Van Gool, T. Moons andA. OosterlinckGeometry-driven diffusion: coupled diffusion maps as a model forexcitatory and inhibitory behaviour in vision 224

H. Keuchel, E. von Puttkamer and U. R. ZitnmerSPIN: learning and forgetting surface classifications with dynamicneural networks 230

Robot vision—poster contributions

T. M. H. Dijkstra, E. Argante and C. C. A. M. GielenMotion parallax from catastrophies in scale-space 237

Contents XI

S. T. ToborgStability and convergence control in cooperative integrationnetworks 241

H. Neumann and H. S. StiehlTowards a neural architecture for unified visual contrast andbrightness perception 245

£. Chen-Kuo Tsao and H.-Y. LiaoFuzzy Kohonen clustering networks for reducing search space in3-D object recognition 249

L. Raffo, S. P. Sabatini, G. Indiveri, D. D. Caviglia and G. M. BisioAn active resistor mesh embedding cortical visual processing 250

/. L. Contreras-Vidal and M. AguilarA fast BCS/FCS algorithm for image segmentation 251

Robot control—oral contributions

P. Morasso, V. Sanguineti and T. Tsuji (invited paper)Neural architecture for robot planning 256

/. Heikkonen, P. Koikkalainen and E. OjaFrom situations to actions: motion behavior learning by self-organization 262

T. Wengerek and H. RitterApplication of Q-learning in robot grasping tasks 268

M. Jansen, } . R. Beerhold and R. EckmillerI/O-stability for robot control with a global neural net inversemodel in the feedback loop 274

Robot control—poster contributions

/. M. Vleugels, J. N. Kok and M. H. OvermarsA self-organizing neural network for robot motion planning 281

D. Cliff, I. Harvey and P. HusbandsEvolved recurrent dynamical networks use noise 285

G. Fahner and R. EckmillerThe Bellmann Mapping Machine for nonlinear approximation incontrol policy space 289

/. N. H. Heemskerk and P. T. W. HudsonA real-time robot demonstration controlled by the BSP400neurocomputer 293

/. R. Beerhold, M. Jansen and R. EckmillerFirst results on stable adaptive robot control with RBF networks .... 297

/. /. Arciniegas, K. J. Cios and A. H. EltimsahyFuzzy inference, radial basis functions, and control of flexiblerobotic manipulators 301

N. H.-R. Goerke, C. M. Mullender and R. EckmillerA recurrent trajectory storage network with parceling of theworkspace 305

xii Contents

/. Hakala and R. EckmillerNode allocation and topographical encoding NATEnet for inversekinematics of a 6-DOF robot arm 309

N. A. BorgheseLearning optimal control using neural networks 313

F. Bini Verona, F. E. Lauria, M. Sette and S. ViscoA boolean net as an adaptive and universal robot control 317

/. W. M. van Dam, B. J. A. Krose and F. C. A. GroenTransforming occupancy grids under robot motion 318

A. Martinengo, M. Campani and V. TorreComplex tasks and robots 319

COGNITIVE CONNECTIONISM

Neural networks, natural language and artificial intelligence—oral contributions

A. Nijholt (invited paper)NN approaches to natural language: context and trends 323

C. Szepesvdri and A. LorinczIntegration of ANNs and dynamic concepts to an adaptive andself-organizing agent 331

N. K. KusabovLearning fuzzy production rules for approximate reasoning inconnectionist production systems 337

M. Boden and A. NarayananA representational architecture for nonmonotonic inheritancestructures 343

Neural networks, natural language and artificial intelligence—poster contributions

/. P. Banquet and J. L. Contreras-VidalSpectral timing and integration of multimodel systemic processes .. 350

R. BlasigNet-to-rule transformation using penalty functions 354

R. G. EvansTeaching homing behaviour to a neural state machine 358

/. Aleksander and H. MortonNeural/iconic understanding of the visual world 362

C. R. LemmenConnectionist "symbol" systems: cognition as the sum of analogy,exemplar manipulation and language 366

F. van der VeldeSymbol-manipulation with attractor neural networks 370

Contents XIII

y. AjiokaA consideration on visual strategy of fovea and saccadic movementfrom experimental results 371

J. Aleksander and H. MortonIconic language representation in a recursive neural system 372

N. J. SalesMiniature language acquisition tasks using dynamic weightlesssystems 373

K. WeiglActivity curvature: a new approach to perception 374

L. K. MichalisAn outline for a theory of the emotions 375

Natural language and speech recognition—oral contributions

P. HaffnerAlpha-Beta TDNN implement "fuzzy" connectionist timealignment in speech recognition 377

A. Mellouk and P. GallinariContinuous speech recognition predictive systems 383

/. Mantysalo, K. Torkkola and T. KohonenHandling context-dependencies in speech by LVQ 389

Natural language and speech recognition—poster contributions

M. F. J. DrossaersAn analytically transparent network for sequence recognition 396

A. Stevenin and P. GallinariConceptual clustering using a connectionist approach 400

A. Hoekstra and M. F. J. DrossaersAn extended Kohonen feature map for sentence recognition 404

T. HonkelaNeural nets that discuss: a general model of communication basedon self-organizing maps 408

G. A. Carpenter and K. K. GovindarajanNeural network and nearest neighbor comparison of speakernormalization methods for vowel recognition 412

H. Behme, W. D. Brandt and H. W. StrubeSpeech recognition by hierarchical segment classification 416

T. Hiltunen, L. Leinonen andj. KangasVisualization and classification of voice quality with the self-organizing map 420

D.-S. Kim and S.-Y. LeeWeighted distance measure for speaker-independent digitrecognition with hidden-control neural network 421

xiv Contents

M. Paping, H. W. Strube and T. GramssModulation-frequency encoding of speech with applications toneural speech recognizers 422

S. H. ParfittFunctional compositionality: a G.N.U. approach 423

PHYSICAL AND MATHEMATICAL THEORY

Novel architectures and learning rules—oral contributions

T. Martinetz (invited paper)Competitive Hebbian learning rule forms perfectly topologypreserving maps 427

M. D. PlumbleyApproximating optimal information transmission using localHebbian algorithms in a double feedback loop 435

B. de VriesTime-varying neural networks for large tasks 441

/. SchmidhuberA "self-referential" weight matrix 446

Novel architecture and learning rules—poster contributions

F. Piazza, A . Uncini and M. ZenobiNeural network complexity reduction using adaptive polynomialactivation functions 452

A . J. M. Russel and Th. E. SchoutenFIELDNET, a dynamic network for pattern classification 456

/. SchmidhuberReducing the ratio between learning complexity and number oftime varying variables in fully recurrent nets 460

M. Hamamoto, J. Kamruzzaman and Y. KumagaiDeletion of trained patterns by incremental learning in artificialneural network using Fahlman-Lebiere learning algorithm 464

/. GrabecCascade neural network developed for time series prediction 468

A . de Pddua BragaOn the information capacity of auto-associative RAM-based neuralnetworks 472

R. Dunay and G. HorvdthModified CMAC neural network architectures for nonlineardynamic system modeling 473

C. £. Pedreira and N. M. RoehlPreliminary results on adaptively trained neural networks 474

A . KorgulNetworks for learning and differentiating an input-outputmapping 475

Contents xv

H. Somers and A. WoodDesign vs. training of neural machines 476

K. W. Wojciechowski, M. A. Brdys and Z. R. SwiderCounterexample of Witsenhausen under set-bounded model ofuncertainty and its neural net solver 477

Y. Zhang, G. E. Hearn and P. SenA modified learning algorithm for backpropagation network 478

M. C. Hernandez, F. X. Albizuri, A. d'Anjou, M. Gratia andF. J. TorrealdeaHigh-order Boltzmann machines for MAX-SAT and SAT 479

V. KecmanEBP algorithm can work with hard limiters 480

K. K. Rennolls, A. Soper, P. Robbins and R. GuthrieStochastic neural networks 481

K. Eder, H. Geiger and W. BrauerA neurophysiologically motivated neural network model and itsapplication to the superposition problem 482

R.-VV. BrauseA symmetrical lateral inhibition network for PCA and featuredecorrelation 486

W. WienholtMinimizing the system error in feedforward neural networks withevolution strategy 490

S. G. RomaniukProve of convergence of extended divide and conquer networks .... 494

J. GlocknerMonotonic incrementation of backpropagation networks 498

A. Hoist and A. LansnerA multi-layer extension of a Bayesian neural network 499

D. Anguita, M. Pampolini, G. Parodi and R. ZuninoYPROP: yet another accelerating technique for the backpropagation 500

T. Denoeux and R. LengelleAutomatic construction of multilayer networks for non linearregression 501

S. Bengio, Y. Bengio, J. Cloutier and J. GecseiGeneralization of a parametric learning rule 502

D. Obradovic and G. DecoSupervised learning for decorrelated Gaussian networks 503

N. Kunstmann, C. Hillermeier and P. TavanAssociative memories that can form hypotheses: phase codednetwork architectures 504

£. Mousset and A. FarajA formal link between multilayer perceptrons and a generalizationof linear discriminant analysis 508

xvi Contents

R. S. Neville and T. J. StonhamAdaptive critic and probabilistic logic nets 509

W. J. DaunichtDEFAnet2—advancements of a deterministic functionapproximator 510

B. Levin and A . LansnerDocument retrieval and protein sequence matching using a neuralnetwork 511

/. M. Cano lzquierdo, Y. A . Dimitriadis and J. Ldpez CoronadoA fuzzy neural architecture for supervised learning andclassification of temporal sequences 512

M. BorgaHierarchical reinforcement learning 513

E. FieslerConnectivity maximization of layered neural networks forsupervised learning 514

Ch. Molina, P. Baylou and M. NajimThe overlapped tessellaton: a supervised neural rule 515

C. A . Hem&ndez, J. Espt, K. Nakayama and M. FerndndezIABP: Interval Arithmetic Backpropagation 516

y. Kumagai, J. Kamruzzaman and J. L. PerezArchitecture of associative memory with reduced cross talk and itsperformance formulation 517

R. S. Neville and T. J. StonhamAugmentation of generalisation in probabilistic logic nets 518

H.-C. Fu and J. J. ShannFuzzy expert networks 519

Stochastic dynamical systems—oral contributions

B. Kappen (invited paper)Using Boltzmann Machines for probability estimation 521

T. S. RognvaldssonBrownian motion updating of multi-layered perceptrons 527

T. M. HeskesGuaranteed convergence of learning in neural networks 533

£. O. Postma, H. J. van den Herik and P. T. W. HudsonActivity-conserving dynamics for neural networks 539

Stochastic dynamical systems—poster contributions

M. YamasakiThe lower bound of the capacity for a neural network withmultiple hidden layers 546

Contents

V. Vysniauskas, F. C. A. Groen and B. J. A. KroseA method for finding the optimal number of learning samples andhidden units for function approximation with a feedforwardnetwork 550

P. Bakker, S. Phillips and J. WilesThe N-2-N encoder: a matter of representation 554

W. Wiegerinck and B. KappenOptimizing the architecture of multi-layer perceptrons for one-dimensional classification 558

H. Elsimary, S. Mashali and S. ShaheenNeural networks and genetic algorithms: improving the faulttolerance capabilities 562

H. S. TohEntropy of perceptrons 563

M. K. Arras and P. ProtzelAssessing generalization by 2-D receptive field visualization 564

y. F. Yam and T. W. S. ChowA fast training algorithm for feedforward neural networks 565

M. Seki and S. MoriImprovement of the convergence of the learning using themodified back-propagation method 566

Selforganization—oral contributions

H. Ritter (invited paper)Parametrized self-organizing maps 568

C. Hillermeier, N. Kunstmann and P. TavanPopulation dynamics on the basis of vector quantization: a methodfor auto-association and classification 576

B. FritzkeVector quantization with a growing and splitting elastic net 580

A. OssenLearning topology-preserving maps using self-supervisedbackpropagation 586

Selforganization—poster contributions

K. MollerA multiassociative memory for control 593

R. Der and M. HerrmannPhase transitions in self-organized feature maps 597

/. Schmidhuber and D. PrelingerUnsupervised extraction of predictable abstract features 601

G. /. Toth and A. LorinczGenetic algorithm with migration on topology conserving maps 605

S. ZrehenAnalyzing Kohonen maps with geometry 609

xviii Contents

M. /. BerchtoldA comparison between classical unsupervised classifiers and ART3neural networks 613

A. M. Fanelli, F. Abbattista, C. Mangia and N. AbbattistaA dynamic procedure for neural network design 617

B. FreislebenPCA in a network with full lateral connections 618

M. Guler and H. KiligNon-uniform cellular automata 619

H. BayerSUSOM—"Supervised" Self-Organizing Maps 620

Dynamical systems—oral contributions

M. Tsodyks, 1. Mitkov and H. Sompolinsky (invited paper)Synchrony in integrate-and-fire networks 622

/. H. van Deemter and H. A. K. MastebroekA neural network for motion detection 628

W. Gerstner and J. L. van HemmenSpikes or rates?—stationary, oscillatory, and spatio-temporal statesin an associative network of spiking neurons 633

A. R. BulsaraCooperative stochastic effects in globally coupled bistable elements

639

Dynamical systems—poster contributions

R. Glasius, A. Komoda and C. C. A. M. GielenBiologically inspired neural network for trajectory formation andobstacle avoidance 646

M. E. J. Raijmakers and P. C. M. MolenaarCatastrophic phase transitions in exact ART networks 650

M. Conti, S. Orcioni and C. TurchettiAnalysis of chaotic behaviour in dynamical systems using analogneural networks 654

P. NtourntoufisA dynamically generalising weightless neural element 658

y. UesakaVector quantization by neuro-dynamical system 662

C. A. van Vreeswijk and L. F. AbbottThe effect of synaptic time constants on firing patterns inpopulations of spiking neurons 666

A. Babloyantz and J.-A. SepulchreInformation processing by spatio-temporal chaotic networks 670

F. GiannakopoulosHysteresis phenomena and bifurcation of periodic solutions in amathematical model of cortical dynamics 676

Contents XIX

£. Goles and M. MatamalaComputing complexity of symmetric quadratic neural networks .... 677

C. Szepesvdri and A. LorinczTopology learning solved by extended objects: a neural networkmodel : 678

A. Bischoff and B. SchurmannHigher order neural networks in a unified learning scheme 679

K. Jin'no and T. SaitoOn a simple hysteresis network 683

y. HayashiSwitching the vector field according to the input of an oscillatoryneural network 684

A. Y. Loskutov and V. M. TereshkoProcessing of information encoded in coupled one-dimensionalmaps 685

/. Segovia, J. Rios, M. Lerma and D. BarriosFeedback in single continuous neurons 686

A. LabbiA neural network for decision making in dynamic environments ... 687

A. Garliauskas and R. AndziusChaos in neural networks at nonlinear synapses 688

/. Tian, J. Tai and X. ZhangStability conditions for nonlinear continuous random neuralnetworks 689

Attractor neural networks—oral contributions

T. L. H. Watkin, K. Y. M. Wong and A. Rau (invited paper)Optimal classification with multilayer networks 691

£. Ventouras, C. Papageorgiou, N. K. Uzunoglu, A. Rabavilas andC. StefanisAn attractor network model for the generation of event-relatedpotentials using integrative synapses 698

A. N. JourjineNovel Liapunov functions for additive neural networks 704

S. AkahoCapacity and error correction ability of sparsely encodedassociative memory with forgetting process 707

Attractor neural networks—poster contributions

H. N. Schaller and K. EhrenbergerDefining the attractor of a recurrent neural network by booleanexpressions 712

P. Lukowicz, K.-R. Miiller and W. M. SeilerUsing REDUCE for replica calculations 716

xx Contents

A. C. C. Coolen and D. SherringtonEquilibrium statistical mechanics of non-symmetric neuralnetworks 722

P. Perez and G. SaliniStorage of words by coupling Hopfield nets 726

D. /. Amit and S. FusiConstraints on learning in dynamic synapses 730

M. MatamalaRecursive construction of neural networks with long periodicbehavior 734

N. HendrichPhase-space gardening in the binary-couplings memory network .. 735

T. Tambouratzis and D. TambouratzisThe relationship between choice of representation, networkstructure and performance in Harmony Theory networks 736

Learning and generalization—oral contributions

M. Anthony and S. B. HoldenOn the power of linearly weighted neural networks 738

G. Deco, W. Finnoff and H. G. ZimmermannElimination of overtraining by a mutual information network 744

G. P. Drago and S. RidellaCascade correlation: an incremental tool for functionapproximation 750

Learning and generalization—poster contributions

M. Anthony and J. Shawe-TaylorBounds on the complexity of testing and loading neurons 756

R. KamimuraPrincipal hidden unit analysis with minimum entropy method 760

S. CanuEmpirical criteria to compare the performance of neuro algorithms 764

£. D. Di Claudio, R. Parisi and G. OrlandiLS-backpropagation algorithm for training multilayer perceptrons . 768

/. Bellido and £. FieslerDo backpropagation trained neural networks have normal weightdistributions? 772

F. M. Frattale Mascioli and G. MartinelliA constructive algorithm for binary mapping 776

S. Geva and J. SitteBOXES revisited 777

M. Ibn Kahla, Z. Faraj and F. CastanieMathematical properties of multi-layer adaptive filters 778

Contents xxi

G. C. Cawley, M. I. Heywood and P. D. NoakesWeight zero enhancement in speech synthesis using neuralnetworks 779

£. /. W. Boers, H. Kuiper, B. L. M. Happel and 1. G. Sprinkhuizen-KuyperBiological metaphors in designing modular artificial neuralnetworks 780

C. Barker and T. MartinetzLearning and generalization controlled by contradiction 781

W. J. Daunicht, R. Steiner and H. FranzExtraction of symbolic statements from synaptic weights 782

H. Kurokawa, C.-Y. Ho and S. MoriA novel back propagation algorithm with optimal number ofhidden units 783

A . Konig, A . Korn, F. Quint and M. GlesnerTwo neural models for fast category learning—neural associativememories and the restricted Coulomb energy model 784

/. Mrsic-FlogelStorage capacity results for decomposed structures of generalizingRAM nodes 785

APPLICATIONS

Industrial applications—oral contributions

C. M. BishopNovelty detection and neural network validation 789

T. Poppe and T. MartinetzEstimating material properties for process optimization 795

W. Yan and B. R. UpadhyayaHybrid digital signal processing and neural networks forautomated diagnostics using eddy current inspection 799

Industrial applications—poster contributions

P. Morasso, A . Pareto, S. Pagliano and V. SanguinetiSelf-organizing neural network for diagnosis 806

W. T. C. van Luenen, P. J. de Jager, J. van Amerongen andH. M. FrankenLimitations of adaptive critic control schemes 810

A . Medvedev and G. HillerstromPeriodic disturbance rejection: a neural network approach 814

D. Butz, K. Noack and W. BrauerRepresentation of real-valued functions by a three-layered artificialneural network with topologically ordered input and output units . 818

xxii Contents

/. M. Bishop and S. WestlandPrediction of reflectance values: towards the integration of neuraland conventional colorimetry 822

M. Lehtokangas, J. Saarinen, P. Huuhtanen and K. KaskiNeural network modeling and prediction of multivariate timeseries using predictive MDL principle 826

S. Margarita and A . BeltrattiDynamics of a neural network-based financial market 830

D. Dasgupta and D. R. McGregorEvolving neurocontrollers for pole balancing 834

P. BurrascanoBackpropagation vector quantization for satellite coverage plansoptimization 838

S.-C. Lee, J.-M. Wu and C.-Y. LiouSequential self-organization for the traveling salesman problem .... 842

Z. Taha and S. OmatuInvariant process control using neural networks 846

H. HyotyniemiOptimal control of dynamic systems using self-organising maps .... 850

T. CatfolisMonitoring a control system with a hybrid neural networkarchitecture 854

/. Vanhala, P. Pakarinen and K. KaskiPaper web profile and analysis using neural networks 855

P. Elo, J. Saarinen, K. Kaski, P. Pakarinen, H. Kiiskinnen, S. Kaijaluotoand K. EdelmannModelling of quality properties in paper drying with multilayerperceptron network 856

F. Qendro, R. Lengelle, T. Denceux and P. GaillardInterpolation of stationary non-linear time series by an optimizedneural network 857

R. E. Uhrig, I. Alguindigue and A . Loskewicz-BuczakTwo-sensor neural network modeling for fault detection 858

N. A . Jalel and J. R. LeighModelling the fed batch fermentation process using artificial neuralnetworks 859

W. Kessler, D. Ende, R. W. Kessler and W. RosenstielIdentification of car body steel by an optical on line system and aKohonen's self-organizing map 860

G. /. T6th, T. Szakdcs and A . LorinczSimulation of pulsed laser material processing controlled by anextended self-organizing Kohonen feature map 861

R. One and A . LansnerProcess modelling using artificial neural networks 862

Contents XXIII

K. Nabeshima, E. Ttirkcan and O CiftciogluReal-time nuclear power plant monitoring with adaptively trainedneural network 863

A. UltschSelf organized feature maps for monitoring and knowledgeacquisition of a chemical process 864

S. Cai, H. Toral and J. QiuFlow regime identification by a self-organising neural network 868

/. Beckmann, W. J. Daunicht and V. HombergFunctional electrical stimulation with neural network controlledstate feedback 869

P. TernaArtificial interacting agents for stock market experiments: thecross-target method 870

O. Ciftcioglu and E. TtirkcanNeural network training by parameter optimization approach 871

M. Csanddi and A. LorinczNeural network analysis of the Hungarian party-state system 872

£. /. Williams and M. J. DenhamModelling time-varying industrial processes using MLP networks . 873

Pattern recognition I—oral contributions

W. J. M. Epping, S. M. Oudshoff and F. V. Abbots (invited paper)Lithofacies indentification from wireline logs—bringing neuralnetworks to application 875

G. Dorffner, P. Rappelsberger and A. FlexerUsing selforganizing feature maps to classify EEG coherence maps 882

M. Busemann, J. Dunker, G. Hartmann, K. O. Krauter, E. Seidenbergand H. WiemersBuilding an artificial retina for distance- and orientation-invariantpattern recognition 888

/. ProriolMLP-RBF: a cooperative multi-modular neural network applicationin high-energy physics 894

Pattern recognition I—poster contributions

O. Simula, A. Visa and K. ValkealahtiOperational cloud classifier based on the topological feature map .. 899

G. Tambouratzis, D. Patel and T. J. StonhamImage segmentation using a self-organising logical neural network 903

S. /. McKenna, A. Y. Cairns and I. W. RickettsHigh-resolution classification of Papanicolauo smear cells usingback-propagation neural networks 907

xxiv Contents

R. C. Watt, G. Maslana, M. Navabi, S. Hill, D. Boujak, A. Gale andK. MylreaArtificial neural networks detect subtle differences betweenanesthetics 911

R. Ritz and J. L. van HemmenPattern segmentation and feature linking as simultaneousprocesses in an associative network of spiking neurons 914

C.-y. Liou and H.-C. YangSpatial topology distance for handprinted character recognition .... 918

S. K. Halgamuge, W. Poechmueller, S. Ting, M. Hoehn and M. GlesnerIdentification of underwater sonar images using fuzzy-neuralarchitecture FuNe I 922

P. WeierichFault detection in multivariate time series with a coding approach . 926

B. LemariePractical implementation of a radial basis function network forhandwritten digit recognition 930

S. Skoneczny, R. Foltyniewicz and M. SitnikAn efficient method of neural network application to recognizingof handwritten digits in zip codes 934

P. A. Hughes and P. D. NoakesThe application of average gradient matrices for fingerprintclassification using neural networks 938

L. D'Agnese, A. Ferro, G. Parodi and R. ZuninoNeural architectures for motion tracking 939

B. Moobed, L. Montoliu, J.-D. Gascuel and M. WeinfeldA multi-agent classifier using associative networks in parallel 940

K. Nakayama, O. Hasegawa and C. HernandezHandwritten alphabet and digit character recognition usingskeleton pattern mapping with structural constraints 941

L. L. Lee and T. BergerOptimization of a signature verification system using neuralnetworks 942

J.-H. LimIncremental case-based pattern classifier 943

S. Skoneczny and R. FoltyniewiczCepstral blur identification by neural network for image restorationpurpose 944

O. Yadid-Pecht and M. GurReduced pattern recognizing neural nets 945

M. MokhtariDigit recognition by the random neural network using supervisedlearning 946

K. H. LeeDetecting abnormalities in MRI images using the differencemethod 947

Contents

/. M. Thijssen, H. J. Huisman, M. S. Klein Gebbink, J. T. M. Verhoevenand Th. E. SchoutenNeural networks for the echographic diagnosis of diffuse liverdiseases 948

Pattern recognition II—oral contributions

£. H. L. Aarts and H. P. Stehouwer (invited paper)Neural networks and the travelling salesman problem 950

U. Bodenhausen and S. MankeAutomatically structured neural networks for handwrittencharacter and word recognition 956

X. Ding, T. Denaeux and F. HellocoTracking rain cells in radar images using multilayer neuralnetworks 962

C.-T. Sun, J.-S. Jang and C. Y. FuNeural network analysis of plasma spectra 968

Pattern recognition II—poster contributions

S. Kaski and S.-L. JoutsiniemiMonitoring EEG signal with self-organizing map 974

K. Jeschke, J. Reinhardt and J. A. MaruhnInvariant pattern recognition with recovery of transformationparameters 978

W. Konen and J. C. VorbruggenApplying dynamic link matching to object recognition in real worldimages 982

R. LamontagnePerformance of the backpropagation neural network forrecognition of radio signals using time-domain features 986

H. Ushida, T. Takagi and T. YamaguchiConceptual fuzzy sets application to facial expression recognitionusing associative memory system 990

K. Fukushima, M. Okada, K. Yamauchi, M. Ohno and K. HiroshigeNeocognitron with non-uniform receptive fields 994

A. Iwata and Y. SuwaHand-written character recognition by a structured self-growingneural network "CombNET-II" 998

R. Natowicz, F. Bosio and S. SeanSegmentation of image sequences using self-organizing featuremaps 1002

G. An and W. J. M. EppingCombining neural-network and statistical methods in seismic first-arrival picking 1006

M. F. Augusteijn, K. A. Shaw and R. J. WatsonA study of neural network input data for ground coveridentification in satellite images 1010

xxvi Contents

/. Kamruzzaman, Y. Kumagai and H. HikitaOn generalization ability of cascaded neural net architecture 1014

M. /. van Gils and P. J. M. CluitmansAssessing the latency of peak Pa in auditory evoked potentialsusing neural networks 1015

Z. Wang, G. Sylos Labini and M. De SarioA self-organizing network of alterable competitive layer for patterncluster 1016

B. V. Mehta, R. Soni, L. Vij and L. C. RabeloPrediction of secondary structures of proteins: comparison ofneural networks (fuzzy ARTMAP) and statistical techniques 1017

£. CarlsonCognitive grammar and map digitization 1018

D. Flotzinger, J. Kalcher and G. PfurtschellerOn-line learning with learning vector quantization: a case study ofEEG classification 1019

S. S. Jumpertz and E. J. GarciaImage sequence coding using a neural vector quantization 1020

N. Gaitanis, G. Kapogianopoulos and D. A. KarrasMinimum distance pattern classifiers based on a new distancemetric 1021

R. Kohlus and M. BottlingerKnowledge extraction by self organising maps 1022

M. Giacomini, T. Parisini, C. Ruggiero and R. SacileApplication of the sensitivity algorithm in biological fields 1023

Neural hardware and software—oral contributions

K. F. Goser (invited paper)Challenge of ANN to microelectronics 1025

l.-S. Han and K.-H. AhnImplementation of million connections neural hardward withURAN-I 1030

U. Ramacher, W. Raab, J. Anlauf, J. Beichter, U. Hachmann, N. Brills,M. Wefieling, £. Sicheneder, R. Manner, J. Gldfi and A. WurzMultiprocessor and memory architecture of the neurocomputerSYNAPSE-1 1034

H. Speckmann, P. Thole and W. RosenstielCOKOS: A Coprocessor for Kohonen's Selforganizing map 1040

Neural hardware and software—poster contributions

A. Kanig, X. Geng and M. GlesnerHardware implementation of Kohonen's feature map by scalar andSIMD-array processors 1046

S. B. Colak and F. P. WiddershovenA nonlinear electronic layer for distributed neural nets 1050

Contents xxvii

B. Kreimeier, M. Shone, R. Steiner and R. EckmillerHow to find a near optimal mapping of neural networks ontomessage passing multicomputers 1054

P. Masa, K. Hoen and H. Wallinga20 million patterns per second VLSI neural network patternclassifier 1058

/. B. LontHigh-density analog-EEPROM based neural network 1062

V. Petridis and K. ParaschidisA simple training law suitable for on-chip learning 1066

P. WilkeSimulation of neural networks and genetic algorithms in adistributed computing environment using NeuroGraph 1070

A. d'Acierno and R. VaccaroA parallel implementation of the back-propagation of errorslearning algorithm on a SIMD parallel computer 1074

L. G. Vuurpijl and Th. SchoutenCONVIS, a distributed environment for control and visualizationof neural network simulation programs 1078

P. Kotilainen, J. Saarinen and K. KaskiMapping of some neural network algorithms to a general purposeparallel neurocomputer 1082

S. M. M. JoostenArchitecture of low cost, large scale neural networks 1083

/. WangA generalized recurrent neural network for matrix inversion 1084

V. Petridis, P. Adamidis and K. G. MargaritisOn the realization of back-propagation on a transputer basedsystem 1085

C. LehmannSelf-organisation of large feature maps using local computations:analysis and VLSI integration 1086

G. W. Hong and S. D. LeeNEUROCOBOL: a COBOL-like neural network simulationlanguage based on the layer macro definition 1087

M. A. RubinEncapsulated objects for neural network simulation 1088

T. TambouratzisA harmony theory network solution to the N-Queens problem 1089

Author Index 1091