TAILIEUCHUNG - RECURRENT NEURAL NETWORKS FOR TEMPORAL DATA PROCESSING

The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems. | RECURRENT NEURAL NETWORKS FOR TEMPORAL DATA PROCESSING Edited by Hubert Cardot and Romuald Boné Recurrent Neural Networks for Temporal Data Processing Edited by Hubert Cardot and Romuald Boné Published by InTech Janeza Trdine 9 51000 Rijeka Croatia Copyright 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution license which permits to copy distribute transmit and adapt the work in any medium so long as the original work is properly cited. After this work has been published by InTech authors have the right to republish it in whole or part in any publication of which they are the author and to make other personal use of the work. Any republication referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials instructions methods or ideas contained in the book. Publishing Process Manager Katarina Lovrecic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright Sybille Yates 2010. Used under license from First published Februry 2011 Printed in India A free online edition of this book is available at Additional hard copies can be obtained from orders@ Recurrent Neural Networks for Temporal Data Processing Edited by Hubert Cardot and Romuald Boné p. cm. ISBN 978-953-307-685-0 I kfTC LI OPEN ACCESS INI Evn PUBLISHER INTECH open free online editions of InTech Books and Journals can be found at .

• Kỹ thuật lập trình
• Neural Networks
• Coordination Dynamics
• Dynamic Environments
• Tunnel Syndrome
• Double Seasonal
• Recurrent Neural
• Neural Networks Representation
• Appropriate problems for Neural Network Learning
• Multilayer Networks
• Remarks on the Backpropagation algorithm
• Neural network application development
• Finding Minimal Neural Networks
• Neural Networks for Business Intelligence Applications
• Feed forward neural networks
• Rule extraction
• Business intelligence applications
• Neural network training
• Fundamentals of neural networks
• Simple neural nets
• Pattern classification
• Pattern asociation
• Neural networks based
• Neural network and deep learning
• Neural network and deep learning: A textbook
• Multilayer neural networks
• Common neural architectures
• Training deep neural networks
• Radial basis function networks
• Adaptive resonance theory
• Backpropagation neural net
• Other neural nets
• Hệ thống GSM
• Ứng dụng Neural Networks
• Lý thuyết Neural Networks
• Thông tin di động GSM
• Mô phỏng Neural Networks
• Luận văn viễn thông
• Bayesian neural networks and its application in obstacle avoidance methods
• Bayesian neural networks
• The most suitable autonomous task
• The optimal neural network structure
• Previously reported shared control methods
• Aided Diagnosis
• Biomedical Applications
• Biological Research
• Cell Responses
• Numerical Forecasting
• Risk Analysis
• Oxidative Process
• Potential Mapping
• Programming Neural
• Networks in Java
• Neural Networks in Java
• Java program
• IS programmers
• Artificial neural networks
• ANN representations
• Perceptron Training
• Rule Extraction from Artificial Neural Networks
• Feedforward neural networks for classification
• Rulle exttractition ffrom neurall nettworkks Examples
• Different types of classification rules
• RegressionRegression rulesrules
• Wavelet neural networks
• Identifying undamaged
• Singular spectrum analysis
• Frequency based filter
• Identifying structure
• The artificial neural networks
• Well log data
• The lithology physical parameters
• Cuu Long basin
• Quantum neural networks
• Cryptographic algorithm
• Key agreement protocol
• Quantum computing
• Bridge deck condition rating based on artificial neural networks
• The Design Load and Main Structure Design
• Neglectable effects on the ANN’s performance
• Accordingly the maintenance need
• Summary of engineering doctoral thesis
• Building regionallinked hydroelectric turbine speed control systems
• The basis of fuzzy logic and artificial neural networks
• Regional linked hydropower turbine
• Artificial Intelligence
• Lecture Artificial Intelligence
• Trí tuệ nhân tạo
• Multilayer perceptrons
• Lecture note Artificial Intelligence
• Bài giảng trí tuệ nhân tạo
• Khoa học máy tính
• RELAP5 simulation program
• VVER 1000 reactor technology
• ANN based model
• Autonomous walking machines
• Behavior control
• Biologically inspired perception
• action systems
• Embedded systems Ethology
• Evolutionary robotics
• Neural control
• Neuroethology
• Reactive behavior
• Reactive control
• Recurrent neural networks
• Sensor fusion
• clinical
• health
• health care
• The Handbook of Brain Theory and Neural Networks
• biomedical
• industrial
• physics
• financial applications
• Neutron Spectrometry
• Transplantation Outcome
• Machine learning
• Lecture Machine learning
• Machine learning algorithms
• Data analysis methods