Earticle

초록

영어

In nature, the observed Chaos phenomenas were often mixed with noise, the existence of noise made the prediction of chaotic time series generate large errors. Chaotic time series had the characteristic of broadband, which liked noise. So there were some limitations with the traditional method of de-noising. But the wavelet threshold de-noising method had the characteristic of the multi-resolution analysis, and its computational quantity was smaller and the noise filtering effect was better. On the other hand, for different types of signals, with different wavelet base functions and threshold rules, it might have a different effect on the de-noising effect. In order to search for the optimal selection of those parameters, firstly this paper constructed a simulated Lorenz noisy signal, and used this signal to do the de-noising experiment, used the SNR and RMSE as the evaluating indicator, and finally obtained the matching combination of those parameters. At the end of this paper, the de-noising simulation was carried out using China's Shijiao station runoff time series data from 1960 to 1970 in China, and the final results showed the effectiveness of the proposed method in this paper.

목차

Abstract
 1. Introduction
 2. De-Noising Principle and Evaluation Rules
  2.1. The Principle of Wavelet Multi-Resolution Analysis and Threshold De-Noising Method
  2.2. De-Noising Effect Evaluation
 3. Simulation Experiment and Analysis
  3.1. The Original Signal and Noisy Signal of Lorenz System
  3.2. Basis Functions and Threshold Rules
  3.3. Simulation of Noisy Chaotic Signal De-Noising Process
 4. Real Chaotic Noisy Signal De-Noising
  4.1. Determining the Time Delay and Embedding Dimension of the Reconstructed Phase Space
  4.2. Prediction Effect Evaluation
 5. Conclusion
 References

키워드

저자

• Sun Hai [ Key Laboratory of marine environment and ecology, Ocean University of China, Qingdao, China ] corresponding Author
• Gao Huiwang [ Key Laboratory of marine environment and ecology, Ocean University of China, Qingdao, China ]
• Ruan Xuejing [ College of Architecture Engineering, Qingdao Agricultural University, Qingdao, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605