Adaptive spiking neural P systems

Spiking neural P systems (SN P systems, in short) are a class of new computing models inspired by the neurophysiological behavior of biological spiking neurons, and have many attractive features for a number of application areas. However, SN P systems lacks learning ability so far. In this paper, we will extend SN P systems and propose a new class of extended spiking neural P systems, called adaptive spiking neural P systems (ASN P systems, in short). The ASN P systems not only retain the advantages of SN P systems, and but also hold learning ability like neural networks. Furthermore, a weight learning algorithm is developed. A linear adaptive filtering example is included as an illustration.