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A Single Layer Network

A single layer network is a simple structure consisting of m neurons each having n inputs. The system performs a mapping from the n-dimensional input space to the m-dimensional output space. To train the network the same learning algorithms as for a single neuron can be used.

This type of network is widely used for linear separable problems, but like a neuron, single layer network are not capable of classifying non linear separable data sets. One way to tackle this problem is to use a multilayer network architecture.


next up previous contents
Next: Multilayer Neural Network Up: Multilayer Networks and Backpropagation Previous: An Artificial Neuron

Albrecht Schmidt
Mit Okt 4 16:45:34 CEST 2000