Neural Network Engineering in Dynamic Control Systems
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
London
Springer London
1995, 1995
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| Edition: | 1st ed. 1995 |
| Series: | Advances in Industrial Control
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1 Neural Approximation: A Control Perspective
- 2 Dynamic Systems in Neural Networks
- 3 Adaptive Neurocontrol of a Certain Class of MIMO Discrete-time Processes Based on Stability Theory
- 4 Local Model Architectures for Nonlinear Modelling and Control
- 5 On ASMOD — An Algorithm for Empirical Modelling using Spline Functions
- 6 Semi-Empirical Modeling of Non-linear Dynamic Systems through Identification of Operating Regimes and Local Models
- 7 On Interpolating Memories for Learning Control
- 8 Construction and Design of Parsimonious Neurofuzzy Systems
- 9 Fast Gradient Based Off-line Training of Multilayer Perceptrons
- 10 Kohonen Network as a Classifier and Predictor for the Qualification of Metal-Oxide Surfaces
- 11 Analysis and Classification of Energy Requirement Situations Using Kohonen Feature Maps within a Forecasting System
- 12 A Radial Basis Function Network Model for Adaptive Control of Drying Oven Temperature
- 13 Hierarchical Competitive Net Architecture