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Mathematics of Neural Networks

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Cover of 'Mathematics of Neural Networks'

Table of Contents

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    Book Overview
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    Chapter 1 N-Tuple Neural Networks
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    Chapter 2 Information Geometry of Neural Networks — An Overview —
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    Chapter 3 Q-Learning: A Tutorial and Extensions
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    Chapter 4 Are There Universal Principles of Brain Computation?
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    Chapter 5 On-Line Training of Memory-Driven Attractor Networks
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    Chapter 6 Mathematical Problems Arising from Constructing an Artificial Brain
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    Chapter 7 The Successful Use of Probability Data in Connectionist Models
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    Chapter 8 Weighted Mixture of Models For On-Line Learning
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    Chapter 9 Local Modifications to Radial Basis Networks
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    Chapter 10 A Statistical Analysis of the Modified NLMS Rules
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    Chapter 11 Finite Size Effects in On-Line Learning of Multi-Layer Neural Networks
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    Chapter 12 Constant Fan-in Digital Neural Networks are VLSI-Optimal
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    Chapter 13 The Application of Binary Encoded 2nd Differential Spectrometry in Preprocessing of UV-Vis Absorption Spectral Data
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    Chapter 14 A Non-Equidistant Elastic Net Algorithm
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    Chapter 15 Unimodal Loading Problems
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    Chapter 16 On the Use of Simple Classifiers for the Initialisation of One-Hidden-Layer Neural Nets
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    Chapter 17 Modelling Conditional Probability Distributions for Periodic Variables
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    Chapter 18 Integro-Differential Equations in Compartmental Model Neurodynamics
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    Chapter 19 Nonlinear Models for Neural Networks
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    Chapter 20 A Neural Network for the Travelling Salesman Problem with a Well Behaved Energy Function
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    Chapter 21 Semiparametric Artificial Neural Networks
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    Chapter 22 An Event-Space Feedforward Network Using Maximum Entropy Partitioning with Application to Low Level Speech Data
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    Chapter 23 Approximating the Bayesian Decision Boundary for Channel Equalisation Using Subset Radial Basis Function Network
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    Chapter 24 Applications of Graph Theory to the Design of Neural Networks for Automated Fingerprint Identification
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    Chapter 25 Zero Dynamics and Relative Degree of Dynamic Recurrent Neural Networks
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    Chapter 26 Irregular Sampling Approach to Neurocontrol: The Band-And Space-Limited Functions Questions
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    Chapter 27 Unsupervised Learning of Temporal Constancies by Pyramidal-Type Neurons.
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    Chapter 28 Numerical Aspects of Machine Learning in Artificial Neural Networks
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    Chapter 29 Learning Algorithms for Ram-Based Neural Networks
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    Chapter 30 Analysis of Correlation Matrix Memory and Partial Match-Implications for Cognitive Psychology
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    Chapter 31 Regularization and Realizability in Radial Basis Function Networks
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    Chapter 32 A Universal Approximator Network for Learning Conditional Probability Densities
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    Chapter 33 Convergence of a Class of Neural Networks
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    Chapter 34 Applications of the Compartmental Model Neuron to Time Series Analysis
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    Chapter 35 Information Theoretic Neural Networks for Contextually Guided Unsupervised Learning
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    Chapter 36 Convergence in Noisy Training
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    Chapter 37 Non-Linear Learning Dynamics with a Diffusing Messenger
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    Chapter 38 A Variational Approach to Associative Memory
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    Chapter 39 Transformation of Nonlinear Programming Problems into Separable ones Using Multilayer Neural Networks
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    Chapter 40 A Theory of Self-Organising Neural Networks
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    Chapter 41 Neural Network Supervised Training Based on a Dimension Reducing Method
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    Chapter 42 A Training Method for Discrete Multilayer Neural Networks
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    Chapter 43 Local Minimal Realisations of Trained Hopfield Networks
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    Chapter 44 Data Dependent Hyperparameter Assignment
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    Chapter 45 Training Radial Basis Function Networks by Using Separable and Orthogonalized Gaussians
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    Chapter 46 Error Bounds for Density Estimation by Mixtures
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    Chapter 47 On Smooth Activation Functions
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    Chapter 48 Generalisation and Regularisation by Gaussian Filter Convolution of Radial Basis Function Networks
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    Chapter 49 Dynamical System Prediction: A Lie Algebraic Approach for a Novel Neural Architecture
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    Chapter 50 Stochastic Neurodynamics and the System Size Expansion
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    Chapter 51 Mathematics of Neural Networks
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    Chapter 52 Capacity Bounds for Structured Neural Network Architectures
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    Chapter 53 On-Line Learning in Multilayer Neural Networks
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    Chapter 54 Spontaneous Dynamics and Associative Learning in an Assymetric Recurrent Random Neural Network
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    Chapter 55 A Statistical Mechanics Analysis of Genetic Algorithms for Search and Learning
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    Chapter 56 Volumes of Attraction Basins in Randomly Connected Boolean Networks
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    Chapter 57 Evidential Rejection Strategy for Neural Network Classifiers
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    Chapter 58 Dynamics Approximation and Change Point Retrieval from a Neural Network Model
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    Chapter 59 Query Learning for Maximum Information Gain in a Multi-Layer Neural Network
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    Chapter 60 Shift, Rotation and Scale Invariant Signatures for Two-Dimensional Contours, in a Neural Network Architecture
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    Chapter 61 Function Approximation by Three-Layer Artificial Neural Networks
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    Chapter 62 Neural Network Versus Statistical Clustering Techniques: A Pilot Study in a Phoneme Recognition Task
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    Chapter 63 Multispectral Image Analysis Using Pulsed Coupled Neural Networks
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    Chapter 64 Reasoning Neural Networks
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    Chapter 65 Capacity of the Upstart Algorithm
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    Chapter 66 Regression with Gaussian Processes
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    Chapter 67 Stochastic Forward-Perturbation, Error Surface and Progressive Learning in Neural Networks
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    Chapter 68 Dynamical Stability of a High-Dimensional Self-Organizing Map
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    Chapter 69 Measurements of Generalisation Based on Information Geometry
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    Chapter 70 Towards an Algebraic Theory of Neural Networks: Sequential Composition
Overall attention for this book and its chapters
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Title
Mathematics of Neural Networks
Published by
Springer US, December 2012
DOI 10.1007/978-1-4615-6099-9
ISBNs
978-1-4613-7794-8, 978-1-4615-6099-9
Editors

Ellacott, Stephen W., Mason, John C., Anderson, Iain J.

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 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 2%
United States 1 2%
Brazil 1 2%
Unknown 38 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 24%
Researcher 7 17%
Student > Ph. D. Student 7 17%
Lecturer 2 5%
Other 2 5%
Other 7 17%
Unknown 6 15%
Readers by discipline Count As %
Computer Science 17 41%
Engineering 7 17%
Mathematics 4 10%
Physics and Astronomy 4 10%
Economics, Econometrics and Finance 2 5%
Other 1 2%
Unknown 6 15%

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