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Artificial Neural Networks

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Cover of 'Artificial Neural Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Recurrent Neural Networks and Super-Turing Interactive Computation
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    Chapter 2 Image Classification with Nonnegative Matrix Factorization Based on Spectral Projected Gradient
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    Chapter 3 Energy-Time Tradeoff in Recurrent Neural Nets
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    Chapter 4 An Introduction to Delay-Coupled Reservoir Computing
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    Chapter 5 Double-Layer Vector Perceptron for Binary Patterns Recognition
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    Chapter 6 Local Detection of Communities by Attractor Neural-Network Dynamics
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    Chapter 7 Learning Gestalt Formations for Oscillator Networks
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    Chapter 8 Analysing the Multiple Timescale Recurrent Neural Network for Embodied Language Understanding
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    Chapter 9 Learning to Look and Looking to Remember: A Neural-Dynamic Embodied Model for Generation of Saccadic Gaze Shifts and Memory Formation
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    Chapter 10 How to Pretrain Deep Boltzmann Machines in Two Stages
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    Chapter 11 Training Dynamic Neural Networks Using the Extended Kalman Filter for Multi-Step-Ahead Predictions
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    Chapter 12 Learning as Constraint Reactions
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    Chapter 13 Baseline-Free Sampling in Parameter Exploring Policy Gradients: Super Symmetric PGPE
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    Chapter 14 Sparse Approximations to Value Functions in Reinforcement Learning
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    Chapter 15 Neural Networks Solution of Optimal Control Problems with Discrete Time Delays and Time-Dependent Learning of Infinitesimal Dynamic System
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    Chapter 16 Applying Prototype Selection and Abstraction Algorithms for Efficient Time-Series Classification
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    Chapter 17 Enforcing Group Structure through the Group Fused Lasso
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    Chapter 18 Incremental Anomaly Identification in Flight Data Analysis by Adapted One-Class SVM Method
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    Chapter 19 Inertial Gesture Recognition with BLSTM-RNN
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    Chapter 20 Online Recognition of Fixations, Saccades, and Smooth Pursuits for Automated Analysis of Traffic Hazard Perception
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    Chapter 21 Input Transformation and Output Combination for Improved Handwritten Digit Recognition
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    Chapter 22 Feature Selection for Interval Forecasting of Electricity Demand Time Series Data
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    Chapter 23 Stacked Denoising Auto-Encoders for Short-Term Time Series Forecasting
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Artificial Neural Networks
Published by
Springer, Cham, January 2015
DOI 10.1007/978-3-319-09903-3
978-3-31-909902-6, 978-3-31-909903-3

Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Student > Postgraduate 1 25%
Unknown 2 50%
Readers by discipline Count As %
Mathematics 1 25%
Physics and Astronomy 1 25%
Unknown 2 50%