Neural Networks, Volume 10

Volume 10, Number 1, January 1997

• Allen M. Waxman, Alan N. Gove, David A. Fay, Joseph P. Racamato, James E. Carrick, Michael Seibert, Eugene D. Savoye:
  Color Night Vision: Opponent Processing in the Fusion of Visible and IR Imagery. 1-6
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• Vivek Anumolu, Norman W. Bray, Kevin D. Reilly:
  Neural Network Models of Strategy Development in Children. 7-24
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• Jinwen Ma:
  Simplex Memory Neural Networks. 25-29
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• Athanasios Kehagias, Vassilios Petridis:
  Predictive Modular Neural Networks for Time Series Classification. 31-49
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• Barak Cohen, David Saad, Emanuel Marom:
  Efficient Training of Recurrent Neural Network with Time Delays. 51-59
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• Charles W. Lee:
  Training Feedforward Neural Networks: An Algorithm Giving Improved Generalization. 61-68
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• George D. Magoulas, Michael N. Vrahatis, George S. Androulakis:
  Effective Backpropagation Training with Variable Stepsize. 69-82
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• Masaharu Adachi, Kazuyuki Aihara:
  Associative Dynamics in a Chaotic Neural Network. 83-98
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• Assaf J. Zeevi, Ronny Meir:
  Density Estimation Through Convex Combinations of Densities: Approximation and Estimation Bounds. 99-109
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• Jong-Chen Chen, Michael Conrad:
  Pattern Categorization and Generalization with a Virtual Neuromolecular Architecture. 111-123
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• Renzo Perfetti, Emanuele Massarelli:
  Training Spatially Homogeneous Fully Recurrent Neural Networks in Eigenvalue Space. 125-137
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• Ryan G. Rosandich:
  HAVNET: A New Neural Network Architecture for Pattern Recognition. 139-151
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• Jun Tani, Naohiro Fukumura:
  Self-organizing Internal Representation in Learning of Navigation: A Physical Experiment by the Mobile Robot YAMABICO. 153-159
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• Kumar S. Ray, Jayati Ghoshal:
  Neuro Fuzzy Approach to Pattern Recognition. 161-182
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• Jia Wang, Zhenyuan Wang:
  Using Neural Networks to Determine Sugeno Measures by Statistics. 183-195
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Volume 10, Number 2, March 1997

• Valentin Dragoi:
  A Dynamic Theory of Acquisition and Extinction in Operant Learning. 201-229
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• Robert A. Jacobs, Fengchun Peng, Martin A. Tanner:
  A Bayesian Approach to Model Selection in Hierarchical Mixtures-of-Experts Architectures. 231-241
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• Sheng Ma, Chuanyi Ji, James Farmer:
  An Efficient EM-based Training Algorithm for Feedforward Neural Networks. 243-256
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• Colin Fyfe:
  A Comparative Study of Two Neural Methods of Exploratory Projection Pursuit. 257-262
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• Mattias Ohlsson, Hong Pi:
  A Study of the Mean Field Approach to Knapsack Problems. 263-271
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• Victor Likhovidov:
  Variational Approach to Unsupervised Learning Algorithms of Neural Networks. 273-289
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• Fa-Long Luo, Rolf Unbehauen, Andrzej Cichocki:
  A Minor Component Analysis Algorithm. 291-297
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• Elias B. Kosmatopoulos, Manolis A. Christodoulou, Petros A. Ioannou:
  Dynamical Neural Networks that Ensure Exponential Identification Error Convergence. 299-314
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• Neil A. Thacker, Ian Abraham, Patrick Courtney:
  Supervised Learning Extensions to the CLAM Network. 315-326
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• Michel Cosnard, Eric Goles Ch.:
  Discrete State Neural Networks and Energies. 327-334
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• Paolo Arena, Luigi Fortuna, Giovanni Muscato, Maria Gabriella Xibilia:
  Multilayer Perceptrons to Approximate Quaternion Valued Functions. 335-342
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• Denise Gorse, Adrian J. Sheperd, John G. Taylor:
  The New ERA in Supervised Learning. 343-352
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• Syozo Yasui:
  Convergence Suppression and Divergence Facilitation: Minimum and Joint Use of Hidden Units by Multiple Outputs. 353-367
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• Thomas Elsken:
  Even on Finite Test Sets Smaller Nets may Perform Better. 369-385
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Volume 10, Number 3, April 1997

• Alessandro Sperduti:
  On the Computational Power of Recurrent Neural Networks for Structures. 395-400
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• Gustavo Deco, Ralph Neuneier, Bernd Schürmann:
  Non-parametric Data Selection for Neural Learning in Non-stationary Time Series. 401-407
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• Matthias Blume, Sadik C. Esener:
  An Efficient Mapping of Fuzzy ART onto a Neural Architecture. 409-411
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• Tatsuo Kitajima, Ken-ichi Hara:
  An Integrated Model for Activity-dependent Synaptic Modifications. 413-421
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• Yasuhiro Sagawa:
  A Function of Neural Networks Generating End- and Side-inhibition in the Primary Visual Cortex. 423-429
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• Marc M. Van Hulle:
  Topology-preserving Map Formation Achieved with a Purely Local Unsupervised Competitive Learning Rule. 431-446
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• David A. Sprecher:
  A Numerical Implementation of Kolmogorov's Superpositions II. 447-457
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• Srinivasa V. Chakravarthy, Joydeep Ghosh:
  Function Emulation Using Radial Basis Function Networks. 459-478
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• Dirk Husmeier, John G. Taylor:
  Predicting Conditional Probability Densities of Stationary Stochastic Time Series. 479-497
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• Philippe De Wilde:
  The Magnitude of the Diagonal Elements in Neural Networks. 499-504
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• Christian Schittenkopf, Gustavo Deco, Wilfried Brauer:
  Two Strategies to Avoid Overfitting in Feedforward Networks. 505-516
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• Xiao-Hu Yu, Guo-An Chen:
  Efficient Backpropagation Learning Using Optimal Learning Rate and Momentum. 517-527
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• Roelof K. Brouwer:
  Automatic Growing of a Hopfield Style Network During Training for Classification. 529-537
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• Behnam S. Arad, Ahmed El-Amawy:
  On Fault Tolerant Training of Feedforward Neural Networks. 539-553
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• Maria Alberta Alberti, Alberto Bertoni, Paola Campadelli, Giuliano Grossi, Roberto Posenato:
  A Neural Algorithm for MAX-2SAT: Performance Analysis and Circuit Implementation. 555-560
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• P. P. Raghu, B. Yegnanarayana:
  Multispectral Image Classification Using Gabor Filters and Stochastic Relaxation Neural Network. 561-572
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• Yi Cheng, Thomas W. Karjala, David M. Himmelblau:
  Closed Loop Nonlinear Process Identification Using Internally Recurrent Nets. 573-586
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Volume 10, Number 4, June 1997

• Christian Mazza:
  On the Storage Capacity of Nonlinear Neural Networks. 593-597
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• Sherif Hashem:
  Optimal Linear Combinations of Neural Networks. 599-614
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• Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
  NL_q Theory: A Neural Control Framework with Global Asymptotic Stability Criteria. 615-637
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• V. W. Noonburg:
  Threshold-dependent Limit Cycles in a Nonlinear Network Model. 639-648
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• Maartje E. J. Raijmakers, Peter C. M. Molenaar:
  Exact ART: A Complete Implementation of an ART Network. 649-669
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• David D. Vogel, William Boos:
  Sparsely Connected, Hebbian Networks with Strikingly Large Storage Capacities. 671-682
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• Gustavo Deco, Lucas C. Parra:
  Non-linear Feature Extraction by Redundancy Reduction in an Unsupervised Stochastic Neural Network. 683-691
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• Jean-François Leber, Andreas Jarosch:
  OpenSim: A Flexible Distributed Neural Network Simulator with Automatic Interactive Graphics. 693-703
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• Jianfeng Feng, Hong Pan, Vwani P. Roychowdhury:
  Linsker-type Hebbian Learning: A Qualitative Analysis on the Parameter Space. 705-720
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• Javier E. Vitela, Jaques Reifman:
  Premature Saturation in Backpropagation Networks: Mechanism and Necessary Conditions. 721-735
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• Chin-Der Wann, Stelios C. A. Thomopoulos:
  A Comparative Study of Self-organizing Clustering Algorithms Dignet and ART2. 737-753
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• Chee Peng Lim, Robert F. Harrison:
  Modified Fuzzy ARTMAP Approaches Bayes Optimal Classification Rates: An Empirical Demonstration. 755-774
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Volume 10, Number 5, July 1997

• Irwin W. Sandberg, Lilian Xu:
  Uniform Approximation and Gamma Networks. 781-784
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• Vladimir I. Makarenko, John P. Welsh, Eric J. Lang, Rodolfo R. Llinás:
  A New Approach to the Analysis of Multidimensional Neuronal Activity: Markov Random Fields. 785-789
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• Edgar Koerner, Hiroshi Tsujino, Tomohiko Masutani:
  A Cortical-type Modular Neural Network for Hypothetical Reasoning. 791-814
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• Bruce Fischl, Michael A. Cohen, Eric L. Schwartz:
  The Local Structure of Space-variant Images. 815-831
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• Hideki Kakeya, Toshiki Kindo:
  Eigenspace Separation of Autocorrelation Memory Matrices for Capacity Expansion. 833-843
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• Alexander A. Frolov, Dusan Húsek, Igor P. Muraviev:
  Informational Capacity and Recall Quality in Sparsely Encoded Hopfield-like Neural Network: Analytical Approaches and Computer Simulation. 845-855
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• Jürgen Schmidhuber:
  Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability. 857-873
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• John A. Flanagan:
  Analysing a Self-organising Algorithm. 875-883
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• Lutz Prechelt:
  Investigation of the CasCor Family of Learning Algorithms. 885-896
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• Xiaodong Tian, Anthony Kuh:
  Performance Bounds for Single Layer Threshold Networks when Tracking a Drifting Adversary. 897-906
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• Charles L. Wilson, James L. Blue, Omid M. Omidvar:
  Training Dynamics and Neural Network Performance. 907-923
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• Chee Peng Lim, Robert F. Harrison:
  An Incremental Adaptive Network for On-line Supervised Learning and Probability Estimation. 925-939
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• Shin Ishii, Masa-aki Sato:
  Chaotic Potts Spin Model for Combinatorial Optimization Problems. 941-963
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Volume 10, Number 6, August 1997

• Kunihiko Fukushima, Yoshio Yamaguchi, Masato Okada:
  Neural Network Model of Spatial Memory: Associative Recall of Maps. 971-979
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• Piërre van de Laar, Tom Heskes, Stan C. A. M. Gielen:
  Task-Dependent Learning of Attention. 981-992
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• Eric O. Postma, H. Jaap van den Herik, Patrick T. W. Hudson:
  SCAN: A Scalable Model of Attentional Selection. 993-1015
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• Mark Moll, Risto Miikkulainen:
  Convergence-Zone Episodic Memory: Analysis and Simulations. 1017-1036
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• Miguel A. Andrade, Federico Morán:
  Receptive Field Map Development by Anti-Hebbian Learning. 1037-1052
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• Cyril Goutte, Lars Kai Hansen:
  Regularization with a Pruning Prior. 1053-1059
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• Vera Kurková, Paul C. Kainen, Vladik Kreinovich:
  Estimates of the Number of Hidden Units and Variation with Respect to Half-Spaces. 1061-1068
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• Jean-Gabriel Attali, Gilles Pagès:
  Approximations of Functions by a Multilayer Perceptron: a New Approach. 1069-1081
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• Roberto Odorico:
  Learning Vector Quantization with Training Count (LVQTC). 1083-1088
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• Hanzhong Gu, Haruhisa Takahashi:
  Estimating Learning Curves of Concept Learning. 1089-1102
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• Kazuo Yamanaka, Masahiro Agu, Teruyuki Miyajima:
  A Continuous-Time Asynchronous Boltzmann Machine. 1103-1107
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• Jinwen Ma:
  The Stability of the Generalized Hopfield Networks in Randomly Asynchronous Mode. 1109-1116
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• M. Paul Gough:
  Associative List Memory. 1117-1131
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• Chuanyi Ji, Demetri Psaltis:
  Network Synthesis through Data-Driven Growth and Decay. 1133-1141
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• Michele Zamparelli:
  Genetically Trained Cellular Neural Networks. 1143-1151
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• Miroslaw Galicki, Herbert Witte, Jens Dörschel, Michael Eiselt, Gert Grießbach:
  Common Optimization of Adaptive Preprocessing Units and a Neural Network during the Learning Period. Application in EEG Pattern Recognition. 1153-1163
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Volume 10, Number 7, October 1997

• Walter J. Freeman:
  Three Centuries of Category Errors in Studies of the Neural Basis of Consciousness and Intentionality. 1175-1183
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• John G. Taylor, Hans-W. Müller-Gärtner:
  Non-Invasive Analysis of Awareness. 1185-1194
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• James Newman, Bernard J. Baars, Sung-Bae Cho:
  A Neural Global Workspace Model for Conscious Attention. 1195-1206
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• John G. Taylor:
  Neural networks for consciousness. 1207-1225
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• Edmund T. Rolls:
  Consciousness in Neural Networks? 1227-1240
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• Erich Harth:
  From Brains to Neural Nets to Brains. 1241-1255
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• Jeffrey A. Gray, Catalin V. Buhusi, Nestor A. Schmajuk:
  The Transition from Automatic to Controlled Processing. 1257-1268
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• Javier Ropero Peláez:
  Plato's theory of ideas revisited. 1269-1288
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• Mitsuyuki Nakao, Iwao Honda, Miroslav Musila, Mitsuaki Yamamoto:
  Metastable associative network models of dream sleep. 1289-1302
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• Chris Browne, Richard G. Evans, Nick J. Sales, Igor Aleksander:
  Consciousness and neural cognizers: a review of some recent approaches. 1303-1316
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• Ron Sun:
  Learning, action and consciousness: a hybrid approach toward modelling consciousness. 1317-1331
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• Robert Alan Brown:
  Consciousness in a Self-Learning, Memory-Controlled, Compound Machine. 1333-1343
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Volume 10, Number 8, November 1997

• Shun-ichi Amari, Tianping Chen, Andrzej Cichocki:
  Stability Analysis of Learning Algorithms for Blind Source Separation. 1345-1351
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• Masataka Watanabe, Kazuyuki Aihara:
  Chaos in Neural Networks Composed of Coincidence Detector Neurons. 1353-1359
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• Igor V. Tetko, Alessandro E. P. Villa:
  Efficient Partition of Learning Data Sets for Neural Network Training. 1361-1374
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• Osamu Hoshino, Noriaki Usuba, Yoshiki Kashimori, Takeshi Kambara:
  Role of Itinerancy Among Attractors as Dynamical Map in Distributed Coding Scheme. 1375-1390
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• Tohru Nitta:
  An Extension of the Back-Propagation Algorithm to Complex Numbers. 1391-1415
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• Adam Kowalczyk:
  Estimates of Storage Capacity of Multilayer Perceptron with Threshold Logic Hidden Units. 1417-1433
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• Fritz Stäger, Mukul Agarwal:
  Three Methods to Speed up the Training of Feedforward and Feedback Perceptrons. 1435-1443
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• Fouad Badran, Sylvie Thiria:
  Neural Network Smoothing in Correlated Time Series Context. 1445-1453
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• John J. McKeown, Fabio Stella, Gary Hall:
  Some numerical aspects of the training problem for feed-forward neural nets. 1455-1463
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• J. A. Dente, Rui Vilela Mendes:
  Characteristic Functions and Process Identification by Neural Networks. 1465-1471
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• Gail A. Carpenter:
  Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks. 1473-1494
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• Young-Sup Hwang, Sung Yang Bang:
  An Efficient Method to Construct a Radial Basis Function Neural Network Classifier. 1495-1503
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• Hengchang Dai, Colin MacBeth:
  Effects of Learning Parameters on Learning Procedure and Performance of a BPNN. 1505-1521
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• Buyurman Baykal, Anthony G. Constantinides:
  A Neural Approach to the Underdetermined-Order Recursive Least-Squares Adaptive Filtering. 1523-1531
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• Michael Schmitt:
  Proving Hardness of Neural Network Training Problems. 1533-1534
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Volume 10, Number 9, December 1997

• Leonid I. Perlovsky, Charles P. Plum, Peter R. Franchi, Elihu J. Tichovolsky, David Choi, Bertus Weijers:
  Einsteinian neural network for spectrum estimation. 1541-1546
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• Guy J. Brown, DeLiang L. Wang:
  Modelling the perceptual segregation of double vowels with a network of neural oscillators. 1547-1558
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• Edmund T. Rolls, Alessandro Treves, David Foster, Conrado J. Pérez-Vicente:
  Simulation studies of the CA3 hippocampal subfield modelled as an attractor neural network. 1559-1569
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• Roy Glasius, Andrzej Komoda, Stan C. A. M. Gielen:
  The Population Vector, an unbiased estimator for non-uniformly distributed neural maps. 1571-1582
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• Stephen Grossberg, Niall McLoughlin:
  Cortical dynamics of three-dimensional surface perception: Binocular and half-occluded scenic images. 1583-1605
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• Mark Girolami, Colin Fyfe:
  An extended exploratory projection pursuit network with linear and nonlinear anti-hebbian lateral connections applied to the cocktail party problem. 1607-1618
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• Peter Whittle:
  Artificial memories: Capacity, basis rate and inference. 1619-1626
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• Makoto Hirahara, Natsuki Oka, Toshiki Kindo:
  Associative memory with a sparse encoding mechanism for storing correlated patterns. 1627-1636
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• Mick Turner, Jim Austin:
  Matching performance of binary correlation matrix memories. 1637-1648
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• Koichi Niijima:
  Learning of associative memory networks based upon cone-like domains of attraction. 1649-1658
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• Wolfgang Maass:
  Networks of spiking neurons: The third generation of neural network models. 1659-1671
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• Isao Tokuda, Tomomasa Nagashima, Kazuyuki Aihara:
  Global bifurcation structure of chaotic neural networks and its application to traveling salesman problems. 1673-1690
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• Csaba Szepesvári, Szabolcs Cimmer, András Lörincz:
  Neurocontroller using dynamic state feedback for compensatory control. 1691-1708
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• Bruno Apolloni, Diego de Falco, John G. Taylor:
  pRAM layout optimisation. 1709-1716
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• Hee-Yeal Yu, Sung Yang Bang:
  An improved time series prediction by applying the layer-by-layer learning method to FIR neural networks. 1717-1729
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• Maria Marinaro, Salvatore Rampone, Roberto Tagliaferri:
  Response to the letter by Li and Cao. 1731-1732
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