# Decay Neuron

This type of neuron decays towards a fixed base-line value. There are two ways the neuron can decay: either by an absolute amount, or a relative amount. At each iteration of the network, weighted inputs are added to the neuron's current activation value, and that sum then decays.

Relative/Absolute

If Relative is chosen, then at each iteration, the neuron's activation value is changed in the direction of the base-line value by a fixed proportion of its distance from that value. Since the amount the activation decays is a fraction of its current activation, this method is "relative."

If Absolute is chosen, then at each iteration, the neuron's activation value is changed in the direction of the base-line value by a fixed amount, or decay amount.

Base-line

The fixed value the neuron decays to.

Decay amount

The amount by which the activation is changed each iteration if absolute decay is chosen.

Decay fraction

The proportion of the distance between the current value and the base-line value, by which the activation is changed each iteration if relative decay is chosen.

Add Noise

If this is set to true, random values are added to the activation via a noise generator. The random values are added after the activation is decayed. For details how the noise generator works, click here.