Nonlinear information data mining based on time series for fractional differential operators-Reference-Cited by-同舟云学术

Nonlinear information data mining based on time series for fractional differential operators

Published:2019-01 Issue:1 Volume:29 Page:013114
ISSN:1054-1500
Container-title:Chaos: An Interdisciplinary Journal of Nonlinear Science
language:en
Short-container-title:Chaos

Author:

Wu Shaofei¹^ORCID

Affiliation:

1. Hubei Province Key Laboratory of Intelligent Robots, Wuhan Institute of Technology, Wuhan 430000, People’s Republic of China and School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430000, People’s Republic of China

Funder

Natural Science Foundation of Hubei Province

Publisher

AIP Publishing

Subject

Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5085430

Reference20 articles.

1. An adaptive approach for texture enhancement based on a fractional differential operator with non-integer step and order

2. Nonlocal impulsive fractional differential inclusions with fractional sectorial operators on Banach spaces

3. Uniqueness of solution for boundary value problems for fractional differential equations

4. Adaptive fractional differential approach and its application to medical image enhancement

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