• Familiar face recognition: A comparative study of a connectionist model and human performance
  Luckman, Adrian J., Allinson, Nigel M., Ellis, Andrew W. and Flude, Brenda M.
  page 3-27
• A recurrent network for modeling noisy temporal sequences
  Bulsari, Abhay B. and Saxen, Henrik
  page 29-40
• Diffusion-concentration neural system for separating figures from background
  Lei, Guo and Baolong, Guo
  page 41-59
• Combining Rough Sets Learning- and Neural Learning-method to deal with uncertain and imprecise information
  Yasdi, R.
  page 61-84
• How to solve the N-bit encoder problem with one hidden unit and polynomially increasing weights and thresholds
  Liang, Xun, Xia, Shaowei and Du, Jihong
  page 85-87

• Determining input features for multilayer perceptrons
  Belue, L.M. and Bauer, K.W. Jr.
  page 111-121
• A knowledge matrix representation for a rule-mapped neural network
  Yeung, D.S. and Fong, H.S.
  page 123-144
• Real-time neural computation of the eigenvector corresponding to the largest eigenvalue of positive matrix
  Luo, F. and Li, Y.
  page 145-157
• Image Recognition Neural Network: IRNN
  Cios, K.J. and Shin, I.
  page 159-185
• Competitive stochastic neural networks for Vector Quantization of images
  Grana, M., D'Anjou, A., Gonzalez, A.I., Albizuri, F.X. and Cottrell, M.
  page 187-195
• On the number and the distribution of RBF centers
  Sanchez A., V.D.
  page 197-202

• Scanning the issue
  Sanchez A., V.D.
  page 209-210
• A hybrid learning neural network architecture with locally activated hidden layer for fast and accurate mapping
  Oh, S., Choi, D. and Lee, I.
  page 211-224
• Optimal design of neural networks using the Taguchi method
  Khaw, J.F.C., Lim, B.S. and Lim, L.E.N.
  page 225-245
• Navigation satellite selection using neural networks
  Simon, D. and El-Sherief, H.
  page 247-258
• Neural network-based predictions of hand movements using simulated and real EEG data
  Masic, N., Pfurtscheller, G. and Flotzinger, D.
  page 259-274
• A new approach to the design of reinforcement schemes for learning automata: Stochastic estimator learning algorithm
  Vasilakos, A.V. and Papadimitriou, G.I.
  page 275-297
• The plasticity of feedforward neural networks in assimilating a training instance based on non-batch learning
  Chen, H. and Soo, V.
  page 299-309
• Second derivative dependent placement of RBF centers
  Sanchez A., V.D.
  page 311-317

• Clustering for vehicle routing with a competitive neural network
  Potvin, J. and Robillard, C.
  page 125-139
• Neural network parallel computing for multi-layer channel routing problems
  Suzuki, K., Amano, H. and Takefuji, Y.
  page 141-156
• Linear systems equivalent to artificial neural networks via Lie theory
  Pearson, D.W.
  page 157-170
• Circuit partitioning using mean field annealing
  Bultan, T. and Aykanat, C.
  page 171-194
• Fast computation of optimal paths using a parallel Dijkstra algorithm with embedded constraints
  Solka, J.L., Perry, J.C., Poellinger, B.R. and Rogers, G.W.
  page 195-212
• A principal component analysis algorithm with invariant norm
  Luo, F., Unbehauen, R. and Li, Y.
  page 213-221

• Scanning the issue
  Sanchez A., V.D.
  page 245-246
• Divide and conquer orthogonality principle for parallel optimizations in TSP
  Szu, H. and Foo, S.
  page 249-261
• The performance evaluation of a new neural network-based traffic management scheme for a satellite communication network
  Ansari, N. and Dequan, L.
  page 263-282
• Dual-mode dynamics neural network for combinatorial optimization
  Sukhan, L. and Park, J.
  page 283-304
• Hopfield networks and symmetry groups
  Pearson, D.W.
  page 305-314
• Design of neurocomputer architectures for large-scale constraint satisfaction problems
  Schaller, H.N.
  page 315-339
• Overfitting and generalization in learning discrete patterns
  Ling, C.X.
  page 341-347
• Inability of higher-order outer product learning to map random higher-order problems
  Kinser, J.M.
  page 349-357

• Efficient identification of RBF neural net models for nonlinear discrete-time multivariable dynamical systems
  Shaohua, T., Jianbin, H. and Vandewalle, J.
  page 11-26
• A successive learning neuro GA control system shooting an irregular moving object
  Hirota, K., Tsurumaru, T., Motegi, A., Yubazaki, N., Ohtani, M. and Miyajima, T.
  page 27-38
• Fuzzy-neural network controllers using mean-value-based functional reasoning
  Watanabe, K., Hara, K., Koga, S. and Tzafestas, S.G.
  page 39-61
• Neuroidentification of a biotechnological process: Issues and application
  Tsaptsinos, D., Tang, R. and Leigh, J.R.
  page 63-79
• Comments on _On the design of feedforward neural networks for binary mapping [1]"
  Tsong-Chih, H. and Sheng-De, W.
  page 81-84
• Robustization of a learning method for RBF networks
  David, V. and Sanchez, A.
  page 85-94

• Memory-based neural networks for robot learning
  Atkeson, C.G. and Schaal, S.
  page 243-269
• Direct associative reinforcement learning methods for dynamic systems control
  Gullapalli, V.
  page 271-292
• Space-frequency localized basis function networks for nonlinear system estimation and control
  Cannon, M. and Slotine, J.E.
  page 293-342
• Some notes on neural learning algorithm benchmarking
  Prechelt, L.
  page 343-347
• Fuzzy logic approach for removing noise
  Yih-Gong, L. and Yuang-Cheh, H.
  page 349-355

• Stabilization and speedup of convergence in training feedforward neural networks
  Looney, C.G.
  page 7-31
• Efficient training of Time Delay Neural Networks for sequential patterns
  Cancelliere, R. and Gemello, R.
  page 33-42
• Configuring interaction of memorized patterns with an asymmetric Hebbian rule for recurrent neural networks
  Ishii, T. and Kyuma, K.
  page 43-53
• Growing nonuniform feedforward networks for continuous mappings
  Vinod, V.V. and Ghose, S.
  page 55-69
• Self-organizing feature map with a momentum term
  Hagiwara, M.
  page 71-81
• Optimization techniques for the design of a neural predictive controller
  Yonghong, T. and Van Cauwenberghe, A.R.
  page 83-96

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