4.6 Article

Spiking Neural P Systems for Basic Arithmetic Operations

Journal

APPLIED SCIENCES-BASEL
Volume 13, Issue 14, Pages -

Publisher

MDPI
DOI: 10.3390/app13148556

Keywords

arithmetic operations; spiking neural p systems; membrane computing; numerical computing

Ask authors/readers for more resources

This paper studies four basic arithmetic operations and improves the parallelization of addition and multiplication methods. It designs more effective SNPS for natural number addition, multiplication, subtraction, and division based on multiple subtractions. The proposed SNPS is verified to be effective through examples. Compared with similar SNPS, our system reduces the number of neurons used and the time overhead for addition operation by 50% and 33% respectively, and reduces the number of neurons used for multiplication operation by 40%.
As a novel biological computing device, the Spiking Neural P system (SNPS) has powerful computing potential. The application of SNPS in the field of arithmetic operation has been a hot research topic in recent years. Researchers have proposed methods and systems for implementing basic arithmetic operations using SNPS. This paper studies four basic arithmetic operations, improves the parallelization of addition and multiplication methods, and designs more effective natural number addition and multiplication SNPS, as well as SNPS for subtraction and for division of natural numbers based on multiple subtractions. The effectiveness of the proposed SNPS is verified by example. Compared with the same kind of SNPS, for the addition operation the number of neurons used in our system is reduced by 50% and the time overhead is reduced by 33%, while for the multiplication operation the number of neurons is reduced by 40%.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available