基于粗糙规则的脉冲神经膜系统计算能力的研究

Computing Ability of Spiking Neural P System Based on Rough Rules

脉冲神经膜系统是受到神经生物系统中神经元相互协作处理脉冲过程的启发而提出的一种新的计算模型。为了更进一步反映生物系统随机性的特点,文中首先提出一种新脉冲神经系统——粗糙规则脉冲神经膜系统,用上下近似概念来确立神经元的激活条件;然后证明了改进后脉冲神经膜系统的计算完备性;最后研究系统产生自动化语言能力来说明其具有很强的计算能力。

Spiking neural P system inspired neurons cooperation processing pulse process in biological systems and proposed new calculation model.In order to further reflect the randomness of biological system,this paper proposed a new neuronal activation system,rough rule based spiking neural P system,which uses the concept of upper and lower approximations to establish the activation conditions of neurons.Then,the computing completeness of the improved spiking neural P system was proved.Finally,the ability of the system to generate automatic language was studied to illustrate its computing ability.The result shows that the improved spiking neural P system has strong computing ability.