**4. Multi-layered perceptron**

A multi-layered perceptron (MLP) network generally contains three or more layers of processing units [7, 8]. The topology of such a network is shown in **Figure 3**. Here, the network is containing three layers of nodes. The first layer defines the input layer. The middle layer or the "hidden" layer consists of "feature detectors"—units that respond to particular features that may appear in the input pattern. Usually, we may have more than one hidden layer. The output layer is the last layer. The activities of the output units are read as output from the network and define different categories of patterns.
