A note on small universal spiking neural p systems

Authors:
Linqiang Pan;Xiangxiang Zeng
Affiliations:
Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Hubei, People's Republic of China;Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Hubei, People's Republic of China
Venue:
WMC'09 Proceedings of the 10th international conference on Membrane Computing
Year:
2009

Citing 8
Cited 2

Small universal Turing machines

Theoretical Computer Science - Special issue on universal machines and computations
Small universal register machines

Theoretical Computer Science - Special issue on universal machines and computations
Handbook of formal languages, vol. 3: beyond words

Handbook of formal languages, vol. 3: beyond words
Membrane Computing: An Introduction

Membrane Computing: An Introduction
Computation: finite and infinite machines

Computation: finite and infinite machines
Spiking Neural P Systems

Fundamenta Informaticae
Smaller Universal Spiking Neural P Systems

Fundamenta Informaticae
Extended spiking neural p systems

WMC'06 Proceedings of the 7th international conference on Membrane Computing

A boundary between universality and non-universality in extended spiking neural p systems

LATA'10 Proceedings of the 4th international conference on Language and Automata Theory and Applications
Spiking neural P systems with rules on synapses

Theoretical Computer Science

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the “standard” way of simulating register machines by spiking neural P systems (in short, SN P systems), one neuron is associated with each instruction of the register machine that we want to simulate. In this note, a new way is introduced for simulating register machines by SN P systems, where only one neuron is used for all instructions of a register machine; in this way, we can use less neurons to construct universal SN P systems. Specifically, a universal system with extended rules (without delay) having 10 neurons is constructed.