Nonlinear neural P systems for generating string languages

Nonlinear spiking neural P (NSNP) system is a distributed parallel computing model inspired from the mechanisms of spiking neurons. Computational completeness of NSNP systems as number generating/accepting devices and function computing devices has been already discussed. However, universality result of NSNP systems as language generating devices has not been established so far. This paper investigates computational power of NSNP systems as language generating devices. The relationships of languages generated by NSNP systems with regular languages are investigated. Moreover, we prove that recursively enumerable languages can be characterized by the projection of inverse-morphic images of languages generated by NSNP systems.

Authors

• Nan Zhou
• Qian Yang
• Hong Peng
• Jun Wang University College London
• Xiaohui Luo

Keywords

• Membrane computing
• Nonlinear neural P systems
• String language
• Language generating device