- P. Patrick van der Smagt:
**Minimisation methods for training feedforward neural networks.**1-11

- Michael E. Hasselmo:
**Runaway synaptic modification in models of cortex: Implications for Alzheimer's disease.**13-40

- Kunihiko Fukushima, Masato Okada, Kazuhito Hiroshige:
**Neocognitron with dual C-cell layers.**41-47

- Yoko Yamaguchi, Hiroshi Shimizu:
**Pattern recognition with figure-ground separation by generation of coherent oscillations.**49-63

- David Hestenes:
**Invariant body kinematics: I. Saccadic and compensatory eye movements.**65-77

- David Hestenes:
**Invariant body kinematics: II. Reaching and neurogeometry.**79-88

- Tarek M. Nabhan, Albert Y. Zomaya:
**Toward generating neural network structures for function approximation.**89-99

- Michael D. Lemmon:
**Topologically ordered competitive sampling.**101-111

- Juha Karhunen, Jyrki Joutsensalo:
**Representation and separation of signals using nonlinear PCA type learning.**113-127

- Eric B. Bartlett:
**Dynamic node architecture learning: An information theoretic approach.**129-140

- John M. DeLaurentis, Fred M. Dickey:
**A convexity-based analysis of neural networks.**141-146

- Daniel F. McCaffrey, A. Ronald Gallant:
**Convergence rates for single hidden layer feedforward networks.**147-158

- Gail A. Carpenter:
**A distributed outstar network for spatial pattern learning.**159-168

- Pierre Courrieu:
**Three algorithms for estimating the domain of validity of feedforward neural networks.**169-174

- Christian Cachin:
**Pedagogical pattern selection strategies.**175-181

- Françoise Beaufays, Youssef Abdel-Magid, Bernard Widrow:
**Application of neural networks to load-frequency control in power systems.**183-194

- Anna Esposito, Salvatore Rampone, Roberto Tagliaferri:
**A neural network for error correcting decoding of binary linear codes.**195-202

- Qing Hu, David B. Hertz:
**An inappropriate use of neural networks for forecasting.**203-

- Kanad Chakraborty, Kishan G. Mehrotra, Chilukuri K. Mohan, Sanjay Ranka:
**Response to letter by Q. Hu and D. B. Hertz.**203-204

- Stephen Grossberg:
**Recognition and segmentation of connected characters with selective attention.**205-206

- Kunihiko Fukushima:
**Response to letter by S. Grossberg.**206-207

- Yukio Hayashi:
**Oscillatory neural network and learning of continuously transformed patterns.**219-231

- Joshua Chover:
**Recall via transient neuronal firing.**233-250

- Kaining Wang, Anthony N. Michel:
**Robustness and perturbation analysis of a class of artificial neural networks.**251-259

- Stefan Wimbauer, Nikolaus Klemmer, J. Leo van Hemmen:
**Universality of unlearning.**261-270

- Elias B. Kosmatopoulos, Manolis A. Christodoulou:
**The Boltzmann g-RHONN: A learning machine for estimating unknown probability distributions.**271-278

- Gerald Fahner, Rolf Eckmiller:
**Structural adaptation of parsimonious higher-order neural classifiers.**279-289

- Zhenni Wang, Christine Di Massimo, Ming T. Tham, A. Julian Morris:
**A procedure for determining the topology of multilayer feedforward neural networks.**291-300

- Zaiyong Tang, Gary J. Koehler:
**Deterministic global optimal FNN training algorithms.**301-311

- Danny S. Thomas, Amar Mitiche:
**Asymptotic optimality of pattern recognition by regression analysis.**313-320

- Bagrat Amirikian, Hajime Nishimura:
**What size network is good for generalization of a specific task of interest?**321-329

- Li Deng, Khaled Hassanein, Mohamed I. Elmasry:
**Analysis of the correlation structure for a neural predictive model with application to speech recognition.**331-339

- Robert W. Smalz, Michael Conrad:
**Combining evolution with credit apportionment: A new learning algorithm for neural nets.**341-351

- Sushmita Mitra, Sankar K. Pal:
**Logical operation based fuzzy MLP for classification and rule generation.**353-373

- Apostolos-Paul Nicholas Refenes, Achileas D. Zapranis, Gavin Francis:
**Stock performance modeling using neural networks: A comparative study with regression models.**375-388

- Jun Takeuchi, Yukio Kosugi:
**Neural network representation of finite element method.**389-395

- Salvatore Cavalieri, Antonella Di Stefano, Orazio Mirabella:
**Optimal path determination in a graph by hopfield neural network.**397-404

- Paolo Gaudiano, Dimitrij Surmeli, Frank D. M. Wilson:
**Gated dipoles for operant conditioning.**405-406

- Jennifer L. Raymond, Douglas A. Baxter, Dean V. Buonomano, John H. Byrne:
**Response to letter by Gaudiano et al.**406-407

- Mohammad Bahrami:
**Adaptive control of dynamic systems by back propagation network.**409-

- W. H. Schiffmann:
**Response to letter by M. Bahrami.**409-410

- Qi Jia, Katsuyuki Hagiwara, Naohiro Toda, Shiro Usui:
**Equivalence relation between the back propagation learning process of an FNN and that of an FNNG.**411-

- Masakazu Matsugu, Alan L. Yuille:
**Spatiotemporal information storage in a content addressable memory using realistic neurons.**419-439

- Nur Arad, Eric L. Schwartz, Zvi Wollberg, Yehezkel Yeshurun:
**Acoustic binaural correspondence used for localization of natural acoustic signals.**441-447

- Morris W. Hirsch:
**Saturation at high gain in discrete time recurrent networks.**449-453

- Hidefumi Katsuura, David A. Sprecher:
**Computational aspects of Kolmogorov's superposition theorem.**455-461

- Robert L. Coultrip, Richard H. Granger:
**Sparse random networks with LTP learning rules approximate Bayes classifiers via Parzen's method.**463-476

- J. J. Kosowsky, Alan L. Yuille:
**The invisible hand algorithm: Solving the assignment problem with statistical physics.**477-490

- Kevin S. Van Horn, Tony R. Martinez:
**The minimum feature set problem.**491-494

- Michael Georgiopoulos, Juxin Huang, Gregory L. Heileman:
**Properties of learning in ARTMAP.**495-506

- Thomas Martinetz, Klaus Schulten:
**Topology representing networks.**507-522

- Y. Guan, Trevor G. Clarkson, John G. Taylor, Denise Gorse:
**Noisy reinforcement training for pRAM nets.**523-528

- Fu-Lai Chung, Tong Lee:
**Fuzzy competitive learning.**539-551

- Jun Tani, Naohiro Fukumura:
**Learning goal-directed sensory-based navigation of a mobile robot.**553-563

- Leonid I. Perlovsky:
**A model-based neural network for transient signal processing.**565-572

- Daniel C. Chin:
**A more efficient global optimization algorithm based on Styblinski and Tang.**573-574

- Jean-François Vibert, Khashayar Pakdaman, Noureddine Azmy:
**Interneural delay modification synchronizes biologically plausible neural networks.**589-607

- Lei Xu, Adam Krzyzak, Alan L. Yuille:
**On radial basis function nets and kernel regression: Statistical consistency, convergence rates, and receptive field size.**609-628

- Jun Wang:
**A deterministic annealing neural network for convex programming.**629-641

- Sukhan Lee, Rhee Man Kil:
**Redundant arm kinematic control with recurrent loop.**643-659

- Vicken Kasparian, Celal Batur, H. Zhang, Joseph Padovan:
**Davidon least squares-based learning algorithm for feedforward neural networks.**661-670

- Leonid I. Perlovsky, John Jaskolski:
**Maximum likelihood adaptive neural controller.**671-680

- Laura I. Burke:
**Neural methods for the traveling salesman problem: Insights from operations research.**681-690

- Roberto Battiti, Anna Maria Colla:
**Democracy in neural nets: Voting schemes for classification.**691-707

- Charles M. Bachmann, Scott A. Musman, Dong Luong, Abraham Schultz:
**Unsupervised BCM projection pursuit algorithms for classification of simulated radar presentations.**709-728

- Kumpati S. Narendra, Snehasis Mukhopadhyay:
**Adaptive control of nonlinear multivariable systems using neural networks.**737-752

- Kiyotoshi Matsuoka, Mitsuru Kawamoto:
**A neural network that self-organizes to perform three operations related to principal component analysis.**753-765

- Luis Gonzalez Sotelino, Marco Saerens, Hugues Bersini:
**Classification of temporal trajectories by continuous-time recurrent nets.**767-776

- Galina L. Rogova:
**Combining the results of several neural network classifiers.**777-781

- Ali A. Minai, Ronald D. Williams:
**Perturbation response in feedforward networks.**783-796

- Keihiro Ochiai, Naohiro Toda, Shiro Usui:
**Kick-out learning algorithm to reduce the oscillation of weights.**797-807

- Brian A. Telfer, Harold Szu:
**Energy functions for minimizing misclassification error with minimum-complexity networks.**809-817

- Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
**Static and dynamic stabilizing neural controllers, applicable to transition between equilibrium points.**819-831

- Kootala P. Venugopal, Abhijit S. Pandya, Raghavan Sudhakar:
**A recurrent neural network controller and learning algorithm for the on-line learning control of autonomous underwater vehicles.**833-846

- E. V. Krishnamurthy:
**Unsolvability, complexity, and neural networks.**847-848

- Kevin T. Judd, Kazuyuki Aihara:
**Response to letter by E. V. Krishnamurthy.**848-849

- Stephen Grossberg, John G. Taylor:
**Introduction: 1994 Special issue.**863-

- Gary G. Blasdel, Klaus Obermayer:
**Putative strategies of scene segmentation in monkey visual cortex.**865-881

- Stephen Grossberg, Steven J. Olson:
**Rules for the cortical map of ocular dominance and orientation columns.**883-894

- Robert K. Cunningham, Allen M. Waxman:
**Diffusion-enhancement bilayer: Realizing long-range apparent motion and spatiotemporal grouping in a neural architecture.**895-924

- Stephen R. Jackson, Richard T. Marrocco, Michael I. Posner:
**Networks of anatomical areas controlling visuospatial attention.**925-944

- Mike W. Oram, David I. Perrett:
**Modeling visual recognition from neurobiological constraints.**945-972

- Samuel Kaski, Teuvo Kohonen:
**Winner-take-all networks for physiological models of competitive learning.**973-984

- Bart L. M. Happel, Jacob M. J. Murre:
**Design and evolution of modular neural network architectures.**985-1004

- Daniel L. Alkon, Kim T. Blackwell, Garth S. Barbour, Susan A. Werness, Thomas P. Vogl:
**Biological plausibility of synaptic associative memory models.**1005-1017

- Wolfgang Konen, Thomas Maurer, Christoph von der Malsburg:
**A fast dynamic link matching algorithm for invariant pattern recognition.**1019-1030

- Theodore W. Berger, Gilbert A. Chauvet, Robert J. Sclabassi:
**A biologically based model of functional properties of the hippocampus.**1031-1064

- Neil Burgess, Michael Recce, John O'Keefe:
**A model of hippocampal function.**1065-1081

- Ivan A. Bachelder, Allen M. Waxman:
**Mobile robot visual mapping and localization: A view-based neurocomputational architecture that emulates hippocampal place learning.**1083-1099

- Daniel Bullock, John C. Fiala, Stephen Grossberg:
**A neural model of timed response learning in the cerebellum.**1101-1114

- Kuniharu Arai, Edward L. Keller, Jay A. Edelman:
**Two-dimensional neural network model of the primate saccadic system.**1115-1135

- Jim-Shih Liaw, Ananda Weerasuriya, Michael A. Arbib:
**Snapping: A paradigm for modeling coordination of motor synergies.**1137-1152

- Paul C. Bressloff, John G. Taylor:
**Dynamics of compartmental model neurons.**1153-1165

- Raju S. Bapi, Daniel S. Levine:
**Modeling the role of frontal lobes in sequential task performance. I. Basic structure and primacy effects.**1167-1180

- John G. Taylor:
**Goals, drives, and consciousness.**1181-1190

- Benedikt K. Humpert:
**Improving back propagation with a new error function.**1191-1192

- Hideki Hayakawa, Shinya Nishida, Yasuhiro Wada, Mitsuo Kawato:
**A computational model for shape estimation by integration of shading and edge information.**1193-1209

- Naonori Ueda, Ryohei Nakano:
**A new competitive learning approach based on an equidistortion principle for designing optimal vector quantizers.**1211-1227

- Stefan Jockusch, Helge Ritter:
**Self-organizing maps: Local competition and evolutionary optimization.**1229-1239

- Kunikazu Kobayashi, Toyoshi Torioka, Nobuhiko Ikeda:
**Fundamental consideration on self-formation of recognition cells.**1241-1252

- Norio Baba, Yoshio Mogami, Motokazu Kohzaki, Yasuhiro Shiraishi, Yutaka Yoshida:
**A hybrid algorithm for finding the global minimum of error function of neural networks and its applications.**1253-1265

- Kenji Araki, Toshimichi Saito:
**An associative memory including time-variant self-feedback.**1267-1271

- Ronald R. Yager:
**Modeling and formulating fuzzy knowledge bases using neural networks.**1273-1283

- Burkhard Lenze:
**How to make sigma-pi neural networks perform perfectly on regular training sets.**1285-1293

- Alexander Shustorovich:
**A subspace projection approach to feature extraction: The two-dimensional gabor transform for character recognition.**1295-1301

- Hiroshi Ohno, Toshihiko Suzuki, Keiji Aoki, Arata Takahasi, Gunji Sugimoto:
**Neural network control for automatic braking control system.**1303-1312

- Thomas Wagner, Friedrich G. Boebel:
**Testing synergetic algorithms with industrial classification problems.**1313-1321

- Thomas P. Caudell, Scott D. G. Smith, Richard Escobedo, Michael Anderson:
**NIRS: Large scale ART-1 neural architectures for engineering design retrieval.**1339-1350

- Brendan L. Rogers:
**New neural multiprocess memory model for adaptively regulating associative learning.**1351-1378

- Tao Wang:
**Improving recall in associative memories by dynamic threshold.**1379-1385

- Anne-Johan Annema, Klaas Hoen, Hans Wallinga:
**Learning behavior and temporary minima of two-layer neural networks.**1387-1404

- Roberto Brunelli:
**Training neural nets through stochastic minimization.**1405-1412

- Bill G. Horne, Don R. Hush:
**On the node complexity of neural networks.**1413-1426

- Patrick Thiran, Martin Hasler:
**Self-organization of a one-dimensional Kohonen network with quantized weights and inputs.**1427-1439

- Bernd Fritzke:
**Growing cell structures--A self-organizing network for unsupervised and supervised learning.**1441-1460

- Bernard Ans, Yves Coiton, Jean-Claude Gilhodes, Jean-Luc Velay:
**A neural network model for temporal sequence learning and motor programming.**1461-1476

- Yan Qiu Chen, David W. Thomas, Mark S. Nixon:
**Generating-shrinking algorithm for learning arbitrary classification.**1471-1489