Adaptive fuzzy spiking neural P systems for fuzzy inference and learning

Spiking neural P systems (in short, SN P systems) and their variants, including fuzzy spiking neural P systems (in short, FSN P systems), generally lack learning ability so far. Aiming at this problem, a class of modified FSN P systems are proposed in this paper, called adaptive fuzzy spiking neural P systems (in short, AFSN P systems). The AFSN P systems not only can model weighted fuzzy production rules in fuzzy knowledge base but also can perform dynamically fuzzy reasoning. It is more important that the AFSN P systems have learning ability like neural networks. Based on neuron’s firing mechanisms, a fuzzy reasoning algorithm and a learning algorithm are developed. An example is included to illustrate the learning ability of the AFSN P systems.