  The space-time (s-t) algebra provides a mathematical model for communication
and computation using values encoded as events in discretized linear
(Newtonian) time. Consequently, the input-output behavior of s-t algebra and
implemented functions are consistent with the flow of time. The s-t algebra and
functions are formally defined. A network design framework for s-t functions is
described, and the design of temporal neural networks, a form of spiking neural
networks, is discussed as an extended case study. Finally, the relationship
with Allen's interval algebra is briefly discussed.
