feed-forward neural network in artificial intelligence
Feedforward Neural Network:
A feed-forward neural network is a biologically inspired
classification algorithm. I consist of a (possibly large number of simple
neuron-like processing units, organized in layers. Every unit in a layer is
connected with all the units in the previous layer. These connections are not
all equal: each connection may have a different strengthen weight on these connections encode the knowledge of a network.
Often the units in a neural network are also called modes. Data enters at the inputs and passes through the network, layer by layer until it arrives at the outputs. During normal operation, that is when it acts as a classifier, there is no feedback between layers. This is why they are called feedforward neural networks.
In the following figure, we see an example of a 2-layered
network with, from top to bottom: an output layer with 5 units, a hidden layer
with 4 units, respectively. The network has 3 input units.
The 3 inputs are shown as circles and these
do not belong to any layer of the network (although the inputs sometimes are
considered as a virtual layer with layer number 0). Any layer that is not an
output layer is a hidden layer. This network, therefore, has 1
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