脉冲神经P系统的计算复杂性
On the computational complexity of spiking neural P systems
摘要：
它表明，没有标准的脉冲神经P系统，模拟图灵机小于指数的时间和空间开销。这里考虑的尖峰神经P系统具有与输入长度无关的恒定数量的神经元。在此基础上，我们构造了一个通用的脉冲神经P系统，该系统在线性时间内模拟图灵机，并且只有10个神经元。
英文摘要：
It is shown that there is no standard spiking neural P system that simulates Turing machines with less than exponential time and space overheads. The spiking neural P systems considered here have a constant number of neurons that is independent of the input length. Following this we construct a universal spiking neural P system with exhaustive use of rules that simulates Turing machines in linear time and has only 10 neurons.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
