کلمات کلیدی مربوط به کتاب ریاضیات شبکه های عصبی. مدل ها، الگوریتم ها و کاربردها: علوم و مهندسی کامپیوتر، هوش مصنوعی، شبکه های عصبی
در صورت تبدیل فایل کتاب Mathematics of Neural Networks. Models, Algorithms and Applications به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب ریاضیات شبکه های عصبی. مدل ها، الگوریتم ها و کاربردها نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
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