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Title:
FUZZY ENTROPY BASED NOISY SIGNAL PROCESSING METHOD AND ITERATIVE SINGULAR SPECTRUM SOFT THRESHOLDING DENOISING METHOD
Document Type and Number:
WIPO Patent Application WO/2018/090467
Kind Code:
A1
Abstract:
The present invention discloses fuzzy entropy based noisy signal processing method and iterative singular spectrum (SSA) soft thresholding denoising method. The method is suitable for noisy signals. Assuming a noisy signal having a length N, and xin = {x1, x2, …, xN}, in which an additive white noise and a signal thereof are not correlated, an original signal xin is used to construct a d-dimensional vector Xd e = {xd e, xd e+1, …, xd e+d-1}, and a similarity Sd r(e) and a fuzzy probability Sd r are defined. The same method is used to construct a (d+1)-dimensional vector Xd+1 e, a corresponding similarity Sd+1 r(e), and a corresponding fuzzy probability Sd+1 r. Fuzzy entropy is defined as FuzzyEn(d, r, N) = -ln(Sd+1 r / Sd r). The singular spectrum distribution of all components obtained by using known signal decomposition methods is defined as a fuzzy entropy spectrum. The invention utilizes fuzzy entropy of quantized system complexity under chaos theory to represent a noise plane, providing a more effective path for noisy signal processing. The fuzzy entropy spectrum-based iterative singular spectrum (SSA-IST) soft thresholding denoising method thereof has a better denoising capability than conventional truncated singular spectrum methods and wavelet transform and empirical mode decomposition denoising methods.

Inventors:
XIE HONGBO (CN)
JI YI (CN)
Application Number:
PCT/CN2016/113611
Publication Date:
May 24, 2018
Filing Date:
December 30, 2016
Export Citation:
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Assignee:
DANYANG HUASHEN ELECTRIC APPLIANCE CO LTD (CN)
International Classes:
H04B15/00; G06F19/00
Foreign References:
CN104615877A2015-05-13
CN102903083A2013-01-30
Other References:
"Denoising Nonlinear Time Series Using Singular Spectrum Analysis and Fuzzy Entropy", CHINESE PHYSICS LETTERS, 31 October 2016 (2016-10-31)
Attorney, Agent or Firm:
CHOFN INTELLECTUAL PROPERTY (CN)
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