English

Design of generalized fractional order gradient descent method

Signal Processing 2022-12-07 v2 Optimization and Control

Abstract

This paper focuses on the convergence problem of the emerging fractional order gradient descent method, and proposes three solutions to overcome the problem. In fact, the general fractional gradient method cannot converge to the real extreme point of the target function, which critically hampers the application of this method. Because of the long memory characteristics of fractional derivative, fixed memory principle is a prior choice. Apart from the truncation of memory length, two new methods are developed to reach the convergence. The one is the truncation of the infinite series, and the other is the modification of the constant fractional order. Finally, six illustrative examples are performed to illustrate the effectiveness and practicability of proposed methods.

Keywords

Cite

@article{arxiv.1901.05294,
  title  = {Design of generalized fractional order gradient descent method},
  author = {Yiheng Wei and Yu Kang and Weidi Yin and Yong Wang},
  journal= {arXiv preprint arXiv:1901.05294},
  year   = {2022}
}

Comments

8 pages, 16 figures

R2 v1 2026-06-23T07:13:23.324Z