##
__A Simple Artificial Neuron__

Our
basic computational element (model neuron) is often called a node or unit. It
receives input from some other units, or perhaps from an external source. Each
input has an associated weight w, which can be modified so as to model synaptic
learning. The unit computes some function f of the weighted sum of its inputs:

Its output, in turn, can serve
as input to other units

The weighted sum is called the net
input to unit i, often written neti.

- Note that wij refers to the weight from unit
j to unit i (not the other way around).
- The function f is the unit's activation
function. In the simplest case, f is the identity function, and the unit's
output is just its net input. This is called a linear unit.

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