Neural Networks Methodology and Applications /

• Main Author: Dreyfus, G. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
• Subjects: Physics.; Artificial intelligence.; Information theory.; Statistical physics.; Dynamical systems.; Engineering.; Electrical engineering.; Statistical Physics, Dynamical Systems and Complexity.; Theoretical, Mathematical and Computational Physics.; Engineering, general.; Information and Communication, Circuits.; Communications Engineering, Networks.; Artificial Intelligence (incl. Robotics).

Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, m...

Table of Contents:

• Neural Networks: An Overview
• Modeling with Neural Networks: Principles and Model Design Methodology
• Modeling Metholodgy: Dimension Reduction and Resampling Methods
• Neural Identification of Controlled Dynamical Systems and Recurrent Networks
• Closed-Loop Control Learning
• Discrimination
• Self-Organizing Maps and Unsupervised Classification
• Neural Networks without Training for Optimization.