Basic Structure
For a given artificial neuron, let there be m + 1 inputs with signals x0 through xm and weights w0 through wm. Usually, the x0 input is assigned the value +1, which makes it a bias input with wk0 = bk. This leaves only m actual inputs to the neuron: from x1 to xm.
The output of kth neuron is:
Where (phi) is the transfer function.
The output is analogous to the axon of a biological neuron, and its value propagates to input of the next layer, through a synapse. It may also exit the system, possibly as part of an output vector.
It has no learning process as such. Its transfer function, weights are calculated and threshold value are predetermined.
Read more about this topic: Artificial Neuron
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