Neural Networks, Volume 6

Volume 6, Number 1, 1993

• Stephen Grossberg, John G. Taylor:
  The fifth anniversary of neural networks. 1
  

• Kurt Hornik, Maxwell B. Stinchcombe, Halbert White:
  Letters to the editor. 3
  
• Vladik Kreinovich:
  Letters to the editor. 3-4
  
• Terry Bossomaier, Natalina Isidoro, Adrian Loeff:
  Errors from grid approximation of IFS codes. 5-6
  

• Marc M. Van Hulle, Tom Tollenaere:
  A modular artificial neural network for texture processing. 7-32
  
• Kunihiko Fukushima, Taro Imagawa:
  Recognition and segmentation of connected characters with selective attention. 33-41
  
• Stephen Grossberg, Frank H. Guenther, Daniel Bullock, Douglas N. Greve:
  Neural representations for sensory-motor control, II: Learning a head-centered visuomotor representation of 3-D target position. 43-67
  
• Jeffrey Hoffman, Josef Skrzypek, Jacques J. Vidal:
  Cluster network for recognition of handwritten, cursive script characters. 69-78
  
• Andrew H. Gee, Sreeram V. B. Aiyer, Richard W. Prager:
  An analytical framework for optimizing neural networks. 79-97
  
• Sam-Kit Sin, Rui J. P. de Figueiredo:
  Efficient learning procedures for optimal interpolative nets. 99-113
  
• Masahiko Morita:
  Associative memory with nonmonotone dynamics. 115-126
  
• Friedrich Biegler-König, Frank Bärmann:
  A learning algorithm for multilayered neural networks based on linear least squares problems. 127-131
  
• Kevin N. Gurney:
  Training nets of stochastic units using system identification. 133-145
  

• Conferences on neural networks and related topics. 151-159
  

Volume 6, Number 2, 1993

• Shun-ichi Amari:
  A universal theorem on learning curves. 161-166
  
• Shuji Yoshizawa, Masahiko Morita, Shun-ichi Amari:
  Capacity of associative memory using a nonmonotonic neuron model. 167-176
  
• Rüdiger W. Brause:
  The error-bounded descriptional complexity of approximation networks. 177-187
  
• John J. Shynk, Neil J. Bershad:
  Stationary points of a single-layer perceptron for nonseparable data models. 189-202
  
• Kevin T. Judd, Kazuyuki Aihara:
  Pulse propagation networks: A neural network model that uses temporal coding by action potentials. 203-215
  
• Koji Nakajima, Yoshihiro Hayakawa:
  Correct reaction neural network. 217-222
  
• Albert Y. Zomaya, Tarek M. Nabhan:
  Centralized and decentralized neuro-adaptive robot controllers. 223-244
  
• Haluk Ögmen:
  A neural theory of retino-cortical dynamics. 245-273
  
• Michael Sabourin, Amar Mitiche:
  Modeling and classification of shape using a Kohonen associative memory with selective multiresolution. 275-283
  
• Christopher Ting, Keng-Chee Chuang:
  An adaptive algorithm for neocognitron to recognize analog images. 285-299
  

Volume 6, Number 3, 1993

• Mats Bengtsson:
  A neural system as a dynamical model for early vision. 313-325
  
• Haruo Kobayashi, Takashi Matsumoto, Tetsuya Yagi, Takuji Shimmi:
  Image processing regularization filters on layered architecture. 327-350
  
• Thierry Denoeux, Régis Lengellé:
  Initializing back propagation networks with prototypes. 351-363
  
• Alessandro Sperduti, Antonina Starita:
  Speed up learning and network optimization with extended back propagation. 365-383
  
• Charles W. Lee:
  Learning in neural networks by using tangent planes to constraint surfaces. 385-392
  
• Lars Kai Hansen:
  Stochastic linear learning: Exact test and training error averages. 393-396
  
• Mohamad T. Musavi, K. Kalantri, Wahid Ahmed, Khue Hiang Chan:
  A minimum error neural network (MNN). 397-407
  
• Jörgen M. Karlholm:
  Associative memories with short-range, higher order couplings. 409-421
  
• John G. Taylor, Stephen Coombes:
  Learning higher order correlations. 423-427
  
• Martin Brown, Chris J. Harris, Patrick C. Parks:
  The interpolation capabilities of the binary CMAC. 429-440
  
• Geoffrey J. Chappell, John G. Taylor:
  The temporal Kohönen map. 441-445
  

Volume 6, Number 4, 1993

• Stephen Grossberg:
  A solution of the figure-ground problem for biological vision. 463-483
  

• Hiroaki Gomi, Mitsuo Kawato:
  Recognition of manipulated objects by motor learning with modular architecture networks. 485-497
  
• Gyöngyi Gaál:
  Population coding by simultaneous activities of neurons in intrinsic coordinate systems defined by their receptive field weighting functions. 499-515
  
• Wolfram Schiffmann, H. Willi Geffers:
  Adaptive control of dynamic systems by back propagation networks. 517-524
  
• Martin Fodslette Møller:
  A scaled conjugate gradient algorithm for fast supervised learning. 525-533
  
• Asim Roy, Lark Sang Kim, Somnath Mukhopadhyay:
  A polynomial time algorithm for the construction and training of a class of multilayer perceptrons. 535-545
  
• Ulrich Ramacher:
  Hamiltonian dynamics of neural networks. 547-557
  
• Giancarlo Parodi, Sandro Ridella, Rodolfo Zunino:
  Using chaos to generate keys for associative noise-like coding memories. 559-572
  
• Gregory Allen Kohring:
  On the Q-state neuron problem in attractor neural networks. 573-581
  
• Stevan V. Odri, Dusan P. Petrovacki, Gordana A. Krstonosic:
  Evolutional development of a multilevel neural network. 583-595
  
• Conferences on neural networks and related topics. 597-606
  

Volume 6, Number 5, 1993

• Dale A. Brown:
  Letters to the editor. 607-608
  
• Alexander Korn:
  Letters to the editor. 608
  
• David G. Stork:
  Letter to the editor. 609
  
• Nico Weymaere:
  Letter to the editor. 611
  
• Arjen van Ooyen, Bernard Nienhuis:
  Response to letter by N. Weymaere. 611-612
  

• Terry M. Caelli, David McG. Squire, Tom P. J. Wild:
  Model-based neural networks. 613-625
  
• Lei Xu:
  Least mean square error reconstruction principle for self-organizing neural-nets. 627-648
  
• Pascal Koiran:
  On the complexity of approximating mappings using feedforward networks. 649-653
  
• Michel Benaïm:
  The "off line learning approximation" in continuous time neural networks: An adiabatic theorem. 655-665
  
• Frank E. McFadden, Yun Peng, James A. Reggia:
  Local conditions for phase transitions in neural networks with variable connection strengths. 667-676
  
• Theodore A. Burton:
  Averaged neural networks. 677-680
  
• Harald Englisch, Yegao Xiao, Kailun Yao:
  Strongly diluted networks with selfinteraction. 681-688
  
• Haruhisa Takahashi, Etsuji Tomita, Tsutomu Kawabata:
  Separability of internal representations in multilayer perceptrons with application to learning. 689-703
  
• J. M. Minor:
  Parity with two layer feedforward nets. 705-707
  
• Katsunori Shimohara, Tadasu Uchiyama, Yukio Tokunaga:
  Subconnection neural network for event-driven temporal sequence processing. 709-718
  
• Youngjik Lee, Sang-Hoon Oh, Myung Won Kim:
  An analysis of premature saturation in back propagation learning. 719-728
  
• Shigeo Abe, Masahiro Kayama, Hiroshi Takenaga, Tadaaki Kitamura:
  Extracting algorithms from pattern classification neural networks. 729-735
  

• Conferences on neural networks and related topics. 741-752
  

Volume 6, Number 6, 1993

• Brendan L. Rogers:
  New conditioned stimulus trace circuit for the rabbit's nictitating membrane response. 753-769
  
• William Finnoff, Ferdinand Hergert, Hans-Georg Zimmermann:
  Improving model selection by nonconvergent methods. 771-783
  
• Hubertus M. A. Andree, Gerard T. Barkema, Wim Lourens, Arie Taal, Jos C. Vermeulen:
  A comparison study of binary feedforward neural networks and digital circuits. 785-790
  
• Faouzi Bouslama, Akira Ichikawa:
  Application of neural networks to fuzzy control. 791-799
  
• Ken-ichi Funahashi, Yuichi Nakamura:
  Approximation of dynamical systems by continuous time recurrent neural networks. 801-806
  
• Thierry Catfolis:
  A method for improving the real-time recurrent learning algorithm. 807-821
  
• Mark D. Plumbley:
  Efficient information transfer and anti-Hebbian neural networks. 823-833
  
• Pierre Courrieu:
  A convergent generator of neural networks. 835-844
  
• Ali A. Minai, Ronald D. Williams:
  On the derivatives of the sigmoid. 845-853
  
• Masahiko Arai:
  Bounds on the number of hidden units in binary-valued three-layer neural networks. 855-860
  
• Moshe Leshno, Vladimir Ya. Lin, Allan Pinkus, Shimon Schocken:
  Multilayer feedforward networks with a nonpolynomial activation function can approximate any function. 861-867
  
• Shashank K. Mehta, Laszlo Fulop:
  An analog neural network to solve the hamiltonian cycle problem. 869-881
  

• Conferences on neural networks and related topics. 883-893
  

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