Chapter 2 Introduction to Neural network
Chapter 2 Introduction to Neural network
Chapter 2 Introduction to Neural network
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Not linear separable!<br />
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Example: Classification problem<br />
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4.1 Perceptron training<br />
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Assume we have sampled the sensors when the process is OK (P)<br />
as well as when its broken (N). We have a number of input vec<strong>to</strong>rs<br />
in each class.<br />
Start: Choose w 0 randomly, t = 0<br />
test: Select a vec<strong>to</strong>r x ∈ P ∪ N<br />
If all x correct, s<strong>to</strong>p!<br />
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