Neural computing is the study of cellular networks that have a natural property for storing experimental knowledge. Such systems bear a resemblance to the brain in the sense that knowledge is acquired through training rather than programming and is retained due to changes in node functions. The knowledge takes the form of stable states or cycles of states in the operation of the et. A central property of such nets is to recall these states or cycles in response to the presentation of cues.

Aleksander & Morton (1989) Neural computing architectures: the design of brain-like machines. p.2 as cited in: M.A. Lovell et al. (1997) Developments in petrophysics. p.169