Plant Electrical signals based on wavelet transform and self similarity feature detection

DOI

10.2991/amcce-15.2015.76How to use a DOI?

Keywords

Continuous wavelet transform; Plant electrical signals; self similarity; feature detection

Abstract

According to the self similarity of plant electrical signal (fractal feature), changes of plant electrical signal amplitude a moment with the physical environment and mutation, causing plant electrical signal is not continuous. Electrical signal fractal characteristics of plant changes along with the time development, but at some point, it does not change with time change. This paper adopts the wavelet coefficient and self similarity relationship, through the index of self similarity calculation between plant electrical signal and wavelet to obtain the wavelet decomposition. Self similarity index is large, and plant electrical of the self similar degree are high. The simulation experiment results show that the self similarity index diagram after wavelet decomposition display can be found in many scales, the wavelet coefficients are very similar looking, providing a new idea for the detection of plant electrical signal characteristics of the physical environment.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Changcheng Li
AU  - Laiwu Yin
AU  - Shuyun Cai
PY  - 2015/04
DA  - 2015/04
TI  - Plant Electrical signals based on wavelet transform and self similarity feature detection
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 394
EP  - 399
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.76
DO  - 10.2991/amcce-15.2015.76
ID  - Li2015/04
ER  -