Title: Multidimensional distribution data association algorithm based on DNAzyme

Authors: Yingying Liu; Xixi Li; Shaofeng Rong; Shimin Guan; Baoguo Cai; Shuo Zhang

Addresses: College of Perfumery and Flavor Technology and Engineering, Shanghai University of Applied Sciences, Shanghai 201418, China ' College of Perfumery and Flavor Technology and Engineering, Shanghai University of Applied Sciences, Shanghai 201418, China ' College of Perfumery and Flavor Technology and Engineering, Shanghai University of Applied Sciences, Shanghai 201418, China ' College of Perfumery and Flavor Technology and Engineering, Shanghai University of Applied Sciences, Shanghai 201418, China ' College of Perfumery and Flavor Technology and Engineering, Shanghai University of Applied Sciences, Shanghai 201418, China ' College of Perfumery and Flavor Technology and Engineering, Shanghai University of Applied Sciences, Shanghai 201418, China

Abstract: The distribution function of the current multidimensional distribution data association algorithm does not have timeliness, which causes the data to generate interference signals during the distribution process, and correlation trajectory errors. Based on DNAzyme, a multidimensional distribution data association algorithm is proposed. The classification characteristics of mostly distributed data is adopted to extract the characteristic parameters of the data. At the same time, the internal storage structure of different data is strengthened to ensure the safe storage of data and connect the signal between the sensor and the data in time, and as a result, establishes good data communication relationship.

Keywords: DNAzyme; multidimensional distribution data; data association; association algorithm.

DOI: 10.1504/IJBM.2022.121811

International Journal of Biometrics, 2022 Vol.14 No.2, pp.208 - 222

Received: 23 Sep 2020
Accepted: 09 Dec 2020
Published online: 07 Apr 2022 *

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