Polynomial Complexity Classes in Spiking Neural P Systems
نویسندگان
چکیده
We study the computational potential of spiking neural (SN) P systems. Under various conditions, several intractable problems have been proven to be solvable by these systems in polynomial or even constant time. We study first their formal aspects such as the input encoding, halting versus spiking, and descriptional complexity. Then we establish a formal platform for complexity classes of uniform families of confluent recognizer SN P systems. Finally, we present results characterizing the computational power of several variants of confluent SN P systems, characterized by classes from P to PSPACE.
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تاریخ انتشار 2010