On the convergence of the sparse possibilistic c-means algorithm
Computer Vision and Pattern Recognition
2017-04-20 v2
Abstract
In this paper, a convergence proof for the recently proposed sparse possibilistic c-means (SPCM) algorithm is provided, utilizing the celebrated Zangwill convergence theorem. It is shown that the iterative sequence generated by SPCM converges to a stationary point or there exists a subsequence of it that converges to a stationary point of the cost function of the algorithm.
Keywords
Cite
@article{arxiv.1508.01057,
title = {On the convergence of the sparse possibilistic c-means algorithm},
author = {Spyridoula D. Xenaki and Konstantinos D. Koutroumbas and Athanasios A. Rontogiannis},
journal= {arXiv preprint arXiv:1508.01057},
year = {2017}
}