Implementation of Arithmetic Operations With Time-Free Spiking Neural P Systems

IEEE Transactions on Nanobioscience
Xiangrong LiuXiangxiang Zeng

Abstract

Spiking neural P systems (SN P systems) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In most applications of SN P systems, synchronization plays a key role which means the execution of a rule is completed in exactly one time unit (one step). However, such synchronization does not coincide with the biological fact: in biological nervous systems, the execution times of spiking rules cannot be known exactly. Therefore, a "realistic" system called time-free SN P systems were proposed, where the precise execution time of rules is removed. In this paper, we consider building arithmetical operation systems based on time-free SN P systems. Specifically, adder, subtracter, multiplier, and divider are constructed by using time-free SN P systems. The obtained systems always produce the same computation result independently from the execution time of the rules.

References

Feb 9, 2011·Neural Computation·Linqiang PanXingyi Zhang
Aug 16, 2012·IEEE Transactions on Nanobioscience·Xiangxiang ZengLinqiang Pan
Aug 26, 2014·Neural Computation·Xingyi ZhangLinqiang Pan
Nov 13, 2014·IEEE Transactions on Nanobioscience·Tao Song, Linqiang Pan
Feb 14, 2015·IEEE Transactions on Neural Networks and Learning Systems·Xingyi ZhangAndrei Paun

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Citations

May 27, 2016·Journal of Bioinformatics and Computational Biology·Tingfang WuYang Zhao
Jun 29, 2016·IEEE Transactions on Nanobioscience·Jun LiJiachang Xu
Apr 14, 2016·Scientific Reports·Zhuanlian DingBin Luo
Sep 18, 2020·International Journal of Neural Systems·Gexiang ZhangMario J Pérez-Jiménez
Feb 28, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Luis GarciaHector Perez

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