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→Neural networks: doubled link

Most of the variety among neural network models comes from:

* ''Interpretation of units'': Units can be interpreted as neurons or groups of neurons.

* ''Definition of activation'': Activation can be defined in a variety of ways. For example, in a [[Boltzmann machine]], the activation is interpreted as the [[probability]] of generating an action potential spike, and is determined via a [[logistic function]] on the sum of the inputs to a unit.

* ''Learning algorithm'': Different networks modify their connections differently. In general, any mathematically defined change in connection weights over time is referred to as the "learning algorithm".

* ''Interpretation of units'': Units can be interpreted as neurons or groups of neurons.

* ''Definition of activation'': Activation can be defined in a variety of ways. For example, in a [[Boltzmann machine]], the activation is interpreted as the [[probability]] of generating an action potential spike, and is determined via a [[logistic function]] on the sum of the inputs to a unit.

* ''Learning algorithm'': Different networks modify their connections differently. In general, any mathematically defined change in connection weights over time is referred to as the "learning algorithm".

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