Artificial Neural Networks

An Introduction to ANN Theory and Practice
1995
ISBN: 978-3-540-59488-8
Verlag: Springer Berlin Heidelberg

Buch, Englisch, Band 931, 299 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 470 g

Reihe: Lecture Notes in Computer Science

This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium.
The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Braspenning, P. J.

Weijters, A. J. M. M.

Thuijsman, F.

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Algebra Elementare Algebra
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme
• Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Grafikprogrammierung
• Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker

Inhaltsverzeichnis

Introduction: Neural networks as associative devices.- Backpropagation networks for Grapheme-Phoneme conversion: A non-technical introduction.- Back Propagation.- Perceptrons.- Kohonen network.- Adaptive Resonance Theory.- Boltzmann Machines.- Representation issues in Boltzmann machines.- Optimisation networks.- Local search in combinatorial optimization.- Process identification and control.- Learning controllers using neural networks.- Key issues for successful industrial neural-network applications: An application in geology.- Neural cognodynamics.- Choosing and using a neural net.