The distances between neurons are calculated using a distance function.

The positive real numbers with distance function is a complete metric space.

The model makes extensive use of gravity or interaction decaying with distance functions.

The distance function on is most readily understood from this point of view.

All it needs is the distance function that satisfies the properties of the metric space.

On the positive real numbers, the metric (distance function) can be defined.

Such a distance function is known as a metric.

The general approach is to use a special distance function together with a regular clustering algorithm.

Signed distance functions are applied for example in computer vision.

Points with no upstream segments in the distance function.