A fuzzy hyperbolic secant function clustering algorithm

Jinxuan Zhuo; Xusheng Zhuo; Erfu Wu; Xueliang Pang; Jietao Chen; Tong Li

doi:10.1117/12.3005288

7 March 2024 A fuzzy hyperbolic secant function clustering algorithm

Jinxuan Zhuo, Xusheng Zhuo, Erfu Wu, Xueliang Pang, Jietao Chen, Tong Li

Proceedings Volume 13086, MIPPR 2023: Pattern Recognition and Computer Vision; 130860O (2024) https://doi.org/10.1117/12.3005288
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China

Abstract

In the paper, a new fuzzy hyperbolic secant function clustering algorithm was presented to improve the cluster center positional accuracy and robustness of cluster. The core of this algorithm is to utilize the high recognition attribute of bell curve of hyperbolic secant function for obtaining the cluster centers and its number. By compared, the provided hyperbolic secant function clustering algorithm prior to the Gaussian function clustering algorithm in the location accuracy of cluster center, and is better than the FCM cluster algorithm both in the location accuracy of cluster center and the cluster robustness.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinxuan Zhuo, Xusheng Zhuo, Erfu Wu, Xueliang Pang, Jietao Chen, and Tong Li "A fuzzy hyperbolic secant function clustering algorithm", Proc. SPIE 13086, MIPPR 2023: Pattern Recognition and Computer Vision, 130860O (7 March 2024); https://doi.org/10.1117/12.3005288

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