Spiking Neural Membrane Computing Models

As third-generation neural network models, spiking P systems (SNP) have distributed parallel computing capabilities with good performance. In recent years, artificial networks received widespread attention due to their powerful information processing capabilities, which is an effective combination of a class biological and mathematical models. However, SNP some shortcomings in numerical calculations. order improve the incompletion current dealing certain real data technology this paper, we use structure methods for reference. Combining them membrane computing, models (SNMC models) are proposed. SNMC state each neuron number, contains input unit threshold unit. Additionally, there new style rules neurons time delay. The way consuming spikes controlled by nonlinear production function, produced spike determined based on comparison between value calculated function critical value. addition, Turing universality model as number generator acceptor proved.