Title: An online noise reduction method for sequential data based on Bernstein-Bezier curve formulation

Authors: Weimin Gao; Xiaoyong Fang; Jingguo Zhao; Qingyun Luo; Jun Hong

Addresses: Department of Computer and Information Science, Hunan Institute of Technology, Hengyang, Hunan 421002, China ' Department of Computer and Information Science, Hunan Institute of Technology, Hengyang, Hunan 421002, China ' Department of Computer and Information Science, Hunan Institute of Technology, Hengyang, Hunan 421002, China ' Department of Computer and Information Science, Hunan Institute of Technology, Hengyang, Hunan 421002, China ' Department of Computer and Information Science, Hunan Institute of Technology, Hengyang, Hunan 421002, China

Abstract: Noise reduction is an important research issue for computer data processing, especially for sequential data. In recent years, owing to the fast development of computer application, the online noise reduction for the sequential data has become an increasingly important research focus. On the basis of Bernstein-Bezier curve formulation, the paper distilled its feature model and proposed a novel online curve (online Bernstein-Bezier curve, OBB curve)-based noise reduction method. OBB curve is a novel curve with online construction characteristics, which is easy, flexible, effective and highly extendable (can be easily extended to reduce noise for n-dimensional sequential data). Experiments prove that OBB curve is a novel online curve, and the online noise reduction with the OBB curve is feasible and effective.

Keywords: noise reduction; online curves; sequential data; Bernstein-Bezier curves; data processing.

DOI: 10.1504/IJCAT.2015.068399

International Journal of Computer Applications in Technology, 2015 Vol.51 No.1, pp.49 - 53

Published online: 01 Apr 2015 *

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