论文标题
（牛顿）时空代数
(Newtonian) Space-Time Algebra
论文作者
论文摘要
时空（S-T）代数提供了一个数学模型，用于使用以离散的线性（牛顿）时间为事件编码为事件的值进行通信和计算。因此，S-T代数和实现功能的投入输出行为与时间流程一致。 S-T代数和函数正式定义。描述了用于S-T功能的网络设计框架，并将时间神经网络的设计（一种尖峰神经网络形式）讨论为一种扩展案例研究。最后，简要讨论了与艾伦间隔代数的关系。
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.
