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Recommended Citation

Cruse H (2009). Neural Networks as Cybernetic Systems (3rd and revised edition) - Part I. Brains, Minds & Media, Vol. 3, bmm1988. (urn:nbn:de:0009-3-19884)

BibTeX

@Article{Cruse:2009,
  author  = "Holk Cruse", 
  title   = "Neural Networks as Cybernetic Systems  (3rd and revised edition) - Part I",
  journal = "Brains, Minds & Media",
  number  = "3",
  year    = "2009"
}

Full Metadata

Bibliographic Citation Brains, Minds & Media, Volume 3, Number 3 (2009-06-26)
Title Neural Networks as Cybernetic Systems (3rd and revised edition) - Part I (eng)
Author Holk Cruse
Language eng
Abstract Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.
Subject cybernetics, neurosciences, models, simulation, systems theory, ANN, neural networks
Classified Subjects ddc: Neurobiology (N3983) ddc: Neuroinformatics (N3985) ddc: System Theory (Sy873) ddc: Cybernetics (C9921) mesh: Neuroscience (D009488) mesh: Models, Theoretical (D008962) mesh: Computer Simulation (D003198)
DDC 500 570 004 150
Rights DPPL
URN urn:nbn:de:0009-3-19884
DOI
Contents
show floating TOC
1 Introduction
1.1 Symbols
1.2 Linear Systems
1.3 The Tasks of Systems Theory Investigations
2 The Most Important Input Functions
2.1 The Step Function
2.2 The Impulse Function
2.3 The Sine Function
2.4 The Statistical Function
2.5 The Ramp Function
3 The Fourier Analysis
4 The Properties of the Most Important Filters
4.1 First Order Low-Pass Filter
4.2 First Order High-Pass Filter
4.3 N-th Order Low-Pass Filter
4.4 N-th Order High-Pass Filters
4.5 Band-Pass filter
4.6 Lead-Lag System
4.7 Pure Time Delay
Box 1
4.8 Integrator and Differentiator
4.9 Oscillating Systems
4.10 Combination of Different Filters
5 The Characteristics
5.1 General Remarks
5.2 The Static Characteristic
5.3 The Dynamic Characteristic
6 Combination of Linear and Nonlinear Elements
6.1 The Sequence Linear Element - Nonlinear Element
6.2 The Sequence Nonlinear Element - Linear Element
6.3 Unidirectional Rate Sensitive (URS) Element
7 The Study of Nonlinear Systems
Box 2
8 Feedback Systems
8.1 Open Loop Control - Closed Loop Control
8.2 The Most Important Terms
8.3 A Simple Feedback System
8.4 The Study of a Feedback System
8.5 Feedback Control Systems with Dynamic Properties
8.6 The Stability of Feedback Systems
Box 3
8.7 Further Types of Feedback Control Systems
8.8 An Example
8.9 Reafference Principle
8.10 The Dynamic Properties of a Simplified Neuron
Appendix I – Laplace Transformation
Appendix II – Simulation of Dynamic Systems
Appendix III – Exercises
References (for Part 1 and Part 2)
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