Other models exist to model more complex binary systems [7].

The network architecture and signal process used to model nervous systems can roughly be divided into three categories, each based on a different philosophy.

Thermodynamic cycles may be used to model real devices and systems, typically by making a series of assumptions.

Simulation is an approach which can be used to model large, complex stochastic systems for forecasting or performance measurement purposes.

While real world communications are often inherently asynchronous it is more practical and useful to model synchronous systems.

There is great interest in modelling biological systems.

They are sometimes allegorical and often serious attempts to model possible future societies, political institutions and systems.

To model systems that do not obey the assumptions of constant temperature and a single reaction, additional dependent variables must be considered.

To model nervous systems accurately, in real-time, alternative hardware is required.

While some sciences are more cut-and-dried, it is beyond challenging to model biological systems.