Title :
Normal Forms of Spiking Neural P Systems With Anti-Spikes
Author :
Tao Song ; Linqiang Pan ; Jun Wang ; Venkat, I. ; Subramanian, K.G. ; Abdullah, R.
Author_Institution :
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
Spiking neural P systems with anti-spikes (ASN P systems, for short) are a variant of spiking neural P systems, which were inspired by inhibitory impulses/spikes or inhibitory synapses. In this work, we consider normal forms of ASN P systems. Specifically, we prove that ASN P systems with pure spiking rules of categories (a, a) and (a, a̅) without forgetting rules are universal as number generating devices. In an ASN P system with spiking rules of categories (a, a̅) and (a̅, a) without forgetting rules, the neurons change spikes to anti-spikes or change anti-spikes to spikes; such systems are proved to be universal. We also prove that ASN P systems with inhibitory synapses using pure spiking rules of category (a, a) and forgetting rules are universal. These results answer an open problem and improve a corresponding result from [IJCCC, IV(3), 2009, 273-282].
Keywords :
biocomputing; neurophysiology; ASN P systems; antispikes; inhibitory impulses; inhibitory spikes; inhibitory synapses; normal forms; number generating devices; pure spiking rules; spiking neural P systems; Computational modeling; Neurons; Registers; Turing machines; Anti-spike; Turing completeness; inhibitory synapse; normal form; spiking neural P system; Computer Simulation; Models, Neurological; Neural Networks (Computer); Neurons; Synapses;
Journal_Title :
NanoBioscience, IEEE Transactions on
DOI :
10.1109/TNB.2012.2208122