| Preface | |
| N-Tuple Neural Networks | p. 3 |
| Information Geometry of Neural Networks - An Overview | p. 15 |
| Q-Learning: A Tutorial and Extensions | p. 24 |
| Are There Universal Principles of Brain Computation? | p. 34 |
| On-line Training of Memory-Driven Attractor Networks | p. 41 |
| Mathematical Problems Arising from Constructing an Artificial Brain | p. 47 |
| The Successful Use of Probability Data in Connectionist Models | p. 61 |
| Weighted Mixture of Models for On-Line Learning | p. 67 |
| Local Modifications to Radial Basis Networks | p. 73 |
| A Statistical Analysis of the Modified NLMS Rules | p. 78 |
| Finite Size Effects in On-Line Learning of Multi-Layer Neural Networks | p. 84 |
| Constant Fan-In Digital Neural Networks are VLSI-Optimal | p. 89 |
| The Application of Binary Encoded 2nd Differential Spectrometry in Preprocessing of UV-VIS Absorption Spectral Data | p. 95 |
| A Non-Equidistant Elastic Net Algorithm | p. 101 |
| Unimodal Loading Problems | p. 107 |
| On the Use of Simple Classifiers for the Initialisation of One-Hidden-Layer Neural Nets | p. 113 |
| Modelling Conditional Probability Distributions for Periodic Variables | p. 118 |
| Integro-Differential Equations in Compartmental Model Neurodynamics | p. 123 |
| Nonlinear Models for Neural Networks | p. 129 |
| A Neural Network for the Travelling Salesman Problem with a Well Behaved Energy Function | p. 134 |
| Semiparametric Artificial Neural Networks | p. 140 |
| An Event-Space Feedforward Network Using Maximum Entropy Partitioning with Application to Low Level Speech Data | p. 146 |
| Approximating the Bayesian Decision Boundary for Channel Equalisation Using Subset Radial Basis Function Network | p. 151 |
| Applications of Graph Theory to the Design of Neural Networks for Automated Fingerprint Identification | p. 156 |
| Zero Dynamics and Relative Degree of Dynamic Recurrent Neural Networks | p. 161 |
| Irregular Sampling Approach to Neurocontrol: The Band- and Space-Limited Functions Questions | p. 166 |
| Unsupervised Learning of Temporal Constancies by Pyramidal-Type Neurons | p. 171 |
| Numerical Aspects of Machine Learning in Artificial Neural Networks | p. 176 |
| Learning Algorithms for Ram-Based Neural Networks | p. 181 |
| Analysis of Correlation Matrix Memory and Partial Match-Implications for Cognitive Psychology | p. 186 |
| Regularization and Realizability in Radial Basis Function Networks | p. 192 |
| A Universal Approximator Network for Learning Conditional Probability Densities | p. 198 |
| Convergence of a Class of Neural Networks | p. 204 |
| Applications of the Compartmental Model Neuron to Time Series Analysis | p. 209 |
| Information Theoretic Neural Networks for Contextually Guided Unsupervised Learning | p. 215 |
| Convergence in Noisy Training | p. 220 |
| Non-Linear Learning Dynamics with a Diffusing Messenger | p. 225 |
| A Variational Approach to Associative Memory | p. 230 |
| Transformation of Nonlinear Programming Problems into Separable Ones Using Multilayer Neural Networks | p. 235 |
| A Theory of Self-Organising Neural Networks | p. 240 |
| Neural Network Supervised Training Based on a Dimension Reducing Method | p. 245 |
| A Training Method for Discrete Multilayer Neural Networks | p. 250 |
| Local Minimal Realisations of Trained Hopfield Networks | p. 255 |
| Data Dependent Hyperparameter Assignment | p. 259 |
| Training Radial Basis Function Networks by Using Separable and Orthogonalized Gaussians | p. 265 |
| Error Bounds for Density Estimation by Mixtures | p. 270 |
| On Smooth Activation Functions | p. 275 |
| Generalisation and Regularisation by Gaussian Filter Convolution of Radial Basis Function Networks | p. 280 |
| Dynamical System Prediction: A Lie Algebraic Approach for a Novel Neural Architecture | p. 285 |
| Stochastic Neurodynamics and the System Size Expansion | p. 290 |
| An Upper Bound on the Bayesian Error Bars for Generalized Linear Regression | p. 295 |
| Capacity Bounds for Structured Neural Network Architectures | p. 300 |
| On-Line Learning in Multilayer Neural Networks | p. 306 |
| Spontaneous Dynamics and Associative Learning in an Assymetric Recurrent Random Neural Network | p. 312 |
| A Statistical Mechanics Analysis of Genetic Algorithms for Search and Learning | p. 318 |
| Volumes of Attraction Basins in Randomly Connected Boolean Networks | p. 323 |
| Evidential Rejection Strategy for Neural Network Classifiers | p. 328 |
| Dynamics Approximation and Change Point Retrieval from a Neural Network Model | p. 333 |
| Query Learning for Maximum Information Gain in a Multi-Layer Neural Network | p. 339 |
| Shift, Rotation and Scale Invariant Signatures for Two-Dimensional Contours, in a Neural Network Architecture | p. 344 |
| Function Approximation by Three-Layer Artificial Neural Networks | p. 349 |
| Neural Network Versus Statistical Clustering Techniques: A Pilot Study in a Phoneme Recognition Task | p. 355 |
| Multispectral Image Analysis Using Pulsed Coupled Neural Networks | p. 361 |
| Reasoning Neural Networks | p. 366 |
| Capacity of the Upstart Algorithm | p. 372 |
| Regression with Gaussian Processes | p. 378 |
| Stochastic Forward-Perturbation, Error Surface and Progressive Learning in Neural Networks | p. 383 |
| Dynamical Stability of a High-Dimensional Self-Organizing Map | p. 389 |
| Measurements of Generalisation Based on Information Geometry | p. 394 |
| Towards an Algebraic Theory of Neural Networks: Sequential Composition | p. 399 |
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