Inspired from spiking and dynamic mechanisms of neurons, dynamic threshold neural P systems (DTNP systems) have been developed and their computational completeness as number-generating/accepting devices and function computing devices has been investigated. However, a universality result of DTNP systems as language generators has not been established so far. This paper discusses computational power of DTNP systems as language generators. We first discuss the relationship between the languages generated by DTNP systems and finite languages, and then prove that regular languages can be generated by finite DTNP systems. Moreover, we prove that recursively enumerable languages can be characterized by projections of inverse-morphic images of the languages generated by DTNP systems.

受神经元突增和动态机制的启发，已经开发了动态阈值神经P系统（DTNP系统），并研究了其作为数生成/接受设备和功能计算设备的计算完整性。但是，迄今为止尚未确定DTNP系统作为语言生成器的普遍性结果。本文讨论了DTNP系统作为语言生成器的计算能力。我们首先讨论了DTNP系统生成的语言与有限语言之间的关系，然后证明了有限DTNP系统可以生成常规语言。此外，我们证明了递归可枚举的语言可以通过DTNP系统生成的语言的反形态图像的投影来表征。