Ebook: Mathematics of Neural Networks. Models, Algorithms and Applications

Springer, 1997. — 423 p. — ISBN 978-1-4613-7794-8.This volume of research papers comprises the proceedings of the first International Conference on Mathematics of Neural Networks and Applications (MANNA), which was held at Lady Margaret Hall, Oxford from July 3rd to 7th, 1995 and attended by 116 people. The meeting was strongly supported and, in addition to a stimulating academic programme, it featured a delightful venue, excellent food and accommodation, a full social programme and fine weather - all of which made for a very enjoyable week.Preface
Invited papers
N. M. Allinson and A. R. Kolcz N-tuple neural networks
Shun-ichi Amari Information geometry of neural networks -an overview15
George Cybenko, Robert Gray and Katsuhiro Moizumi Q-learning: A tutorial and extensions
Stephen Grossberg Are there universal principles of brain computation?
Morris W. Hirsch On-line training of memory-driven attractor networks
J. G. Taylor Mathematical problems arising from constructing an artificial brain
Submitted papers
J. R. Alexander Jr. and J. P. Coughlin the successful use of probability data in connectionist models
P. Edgar An Weighted mixture of models for on-line learning
I. J. Anderson Local modifications to radial basis networks
E.D. Aved'yan, M. Brown and C.J. Harris A statistical analysis of the modified nlms rules
David Barber, Peter Sollich and David Saad Finite size effects in on-line learning of multi-layer neural networks
V. Beiu Constant fan-in digital neural networks are vlsi-optimal
N. Benjathapanun, W. J. O. Boyle and K. T. V. Grattan The application of binary encoded 2nd differential spectrometry in preprocessing of uv -vis absorption spectral data
Jan van den Berg and Jock H. Geselschap A non-equidistant elastic net algorithm
Monica Bianchini, Stefano Fanelli, Marco Gori and Marco Protasi Unimodal loading problems
Jan C. Bioch, Robert Carsouw and Rob Potharst On the use of simple classifiers for the initialisation of one-hiddenlayer neural nets
Christopher M Bishop and Ian T Nabney Modelling conditional probability distributions for periodic variables
Paul C. Bressloff Integro-differential equations in compartmental model neurodynamics
Susan Brittain and Linda M. Haines Nonlinear models for neural networks
Marco Budinich and Barbara Rosario A Neural network for the travelling salesman problem with a well behaved energy function
Enrico Capobianco Semiparametric artificial neural networks
D.K. Y. Chiu, D. Bockus and J. Bradford An event-space feedforward network using maximum entropy partitioning with application to low level speech data
E.S. Chng, B. Mulgrew, S. Chen and G. Gibson Approximating the bayesian decision boundary for channel equalisation using subset radial basis function network
Carol G. Crawford Applications of graph theory to the design of neural networks for automated fingerprint identification
A. Delgado, C. Kambhampati and K. Warwick Zero dynamics and relative degree of dynamic recurrent neural networks
Andrzej Dzielinski and Rafal Zbikowski Irregular sampling approach to neurocontrol: the band-and space-limited functions questions
Michael Eisele Unsupervised learning of temporal constancies by pyramidal-type neurons
S. W. Ellacott and A. Easdown Numerical aspects of machine learning in artificial neural networks
Alistair Ferguson, Laurence C Dixon and Hamid Bolouri Learning algorithms for ram-based neural networks
Richard Filer and James Austin Analysis of correlation matrix memory and partial matchimplications for cognitive psychology
Jason A.S. Freeman and David Saad Regularization and realizability in radial basis function networks
D. Husmeier, D. Allen and J. G. Taylor A universal approximator network for learning conditional probability densities
Mark P. Joy Convergence of a class of neural networks
S. K. Asderidis and J. G. Taylor Applications of the compartmental model neuron to time series analysis
Jim Kay Information theoretic neural networks for contextually guided unsupervised learning
Petri K. Oistinen Convergence in noisy training
Barl Krekelberg and John G. Taylor Non-linear learning dynamics with a diffusing messenger
Abderrahim Labbi A Variational approach to associative memory
Bao-Liang Lu and Koji Ito Transformation of nonlinear programming problems into separable ones using multilayer neural networks
S. P. Luttrell A theory of self-organising neural networks
G.D. Magoulas, M.N. Vrahatis, T.N. Grapsa and G.S. Androulakis Neural network supervised training based on a dimension reducing method
G.D. Magoulas, M.N. Vrahatis, T.N. Grapsa and G.S. Androulakis A training method for discrete multilayer neural networks
S. Manchanda and G.G.R. Green Local minimal realisations of trained hopfield networks
Glenn Marion and David Saad Data dependent hyperparameter assignment
J. C. Mason, 1. J. Anderson, G. Rodriguez and S. Seatzu Training radial basis function networks by using separable and orthogonalized gaussians
Ronny Meir and Assaf J. Zeevi Error bounds for density estimation by mixtures
H. N. Mhaskar On smooth activation functions
Christophe Molina and Mahesan Niranjan Generalisation and regularisation by gaussian filter convolution of radial basis function networks
Yves Moreau and Joos Vandewalle Dynamical system prediction: a lie algebraic approach for a novel neural architecture
Toru Ohira and Jack D. Cowan Stochastic neurodynamics and the system size expansion
Cazhaow S. Qazaz, Christopher K. I. Williams and Christopher M. Bishop An upper bound on the bayesian error bars for generalized linear regression
Peter Rieper, Sabine Kroner and Reinhard Moratz Capacity bounds for structured neural network architectures
David Saad and Sara A. Solla On-line learning in multilayer neural networks
M. Samuelides, B. Doyon, B. Cessac and M. Quoy Spontaneous dynamics and associative learning in an assymetric recurrent random neural network
Jonathan L. Shapiro, Adam Prugel-Bennett and Magnus Rattray A statistical mechanics analysis of genetic algorithms for search and learning
Sergey A. Shumsky Volumes of attraction basins in randomly connected boolean networks
A. Shustorovich Evidential rejection strategy for neural network classifiers
J. Smid and P. Volf Dynamics approximation and change point retrieval from a neural network model
Peter Sollich Query learning for maximum information gain in a multi-layer neural network
David McG. Squire and Terry M. Caelli Shift, rotation and scale invariant signatures for two-dimensional contours, in a neural network architecture
Shin Suzuki Function approximation by threelayer artificial neural networks
G. Tambouratzis, T. Tambouratzis and D. Tambouratzis Neural network versus statistical clustering techniques: A pilot study in a phoneme recognition task
G. L. Tarr, X. Clastres, L. Freyss, M. Samuelides, C. Dehainaut and W. Burckel Multispectral image analysis using pulsed coupled neural networks
Rua-Huan R. Tsaih Reasoning neural networks
Ansgar H. L. West and David Saad Capacity of the upstart algorithm
Christopher K. 1. Williams Regression with gaussian processes
Li-Qun Xu Stochastic forward-perturbation, error surface and progressive learning in neural networks
Howard Hua Yang Dynamical stability of a highdimensional self-organizing map
Huaiyu Zhu and Richard Rohwer Measurements of generalisation based on information geometry
R. Zimmer Towards an algebraic theory of neural networks: Sequential composition