Chapter 2 Introduction to Neural network

Example:
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Many signal processing problems can be transformed to the approximation
problem. We will deal with arbitrary number of input
and output for any nonlinear function.
2.1.2 Association
The ideas is to put a finite number of items in memory (e.g. the
Latin characters) and by presenting distorted versions, we want the
item to be restored.
Example:
Input
Output
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□
2.1.3 Pattern classification
A number of inputs should be classified into categories.
o
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90 C OK
o
100 C
Error
□
2.1.4 Prediction
Given information up to present time predict the behavior in the
future.
2.1.5 Automatic control (Reglerteknik)
We want to simulate the behavior of a process so that we can control
it to fit our purposes.
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