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Neuronal Networks
Andreas Mielke
Neural networks are a useful tool for simulations in various areas like medicine or economy. For a successful application one has to consider several points. In this document we answer the following questions: How does one plan a project in which neural networks are used? How does one construct a neural network? How can errors be analyzed, and how can one minimize them? Which techniques can be used to derive rules using neural networks? How can one optimize and control a neural network? At the end, we present an example of an application of neural networks in medicine.
1. Possibilities and limitations of neural networks
2. Planning
- 2.1 Introduction
- 2.2 The problem
- 2.3 The aim
- 2.4 Resources
- 2.5 Project personnel
- 2.6 Costs
- 2.7 Documentation
3. Data
4. The network
5. Errors
- 5.1 Basic remarks
- 5.2 Sources of errors
- 5.3 Errors in classifications
- 5.4 Errors of continuous output data
- 5.5 Estimating errors of continuous data
- 5.6 Interpretation of errors
- 5.7 Special cases
6. Rules
7. Optimization and control
- 7.1 Introduction
- 7.2 Refinement of a neural network
- 7.3 Optimization and control of the software
- 7.4 Optimization of the Hardware
8. Application
9. Links to other sites providing information on neural networks
This document has been generated automatically out of an XML-source and has been processed to various formats. It can be obtained as postscript or as pdf file. It will be updated regularly.
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