Parameter wavelet threshold signal denoising method based on improved artificial bee colony algorithm

An artificial bee colony algorithm and wavelet threshold technology, applied in computing, artificial life, computing models, etc., can solve problems such as low convergence accuracy, easy to fall into local optimum, and slow convergence speed
CN110765834AActive Publication Date: 2020-02-07QINGDAO UNIV OF SCI & TECH +2
5 Cites 8 Cited by

Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
QINGDAO UNIV OF SCI & TECH
Publication Date
2020-02-07

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a parameter wavelet threshold signal denoising method based on an improved artificial bee colony algorithm. The parameter wavelet threshold signal denoising method comprises the steps: firstly obtaining a to-be-denoised signal, carrying out wavelet transformation, and obtaining a wavelet coefficient; designing a new threshold function on the basis of a traditional thresholdfunction, proving the property of the new threshold function through mathematical derivation, and determining threshold parameters to be optimized; improving an original artificial bee colony algorithm; taking a mean square error between the to-be-denoised signal and the denoised signal as a fitness function of the improved artificial bee colony algorithm in S3, and obtaining an optimal thresholdparameter under the condition of obtaining a minimum mean square error; and applying the optimal threshold parameter obtained in the step S4 to the new threshold function in the step S2, performing shrinkage processing on the wavelet coefficient to obtain a new wavelet coefficient, and performing inverse wavelet transform to obtain a denoised signal. According to the parameter wavelet threshold signal denoising method, a smaller mean square error, a higher output signal-to-noise ratio and a larger noise rejection ratio can be obtained.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention belongs to the field of wavelet threshold value signal denoising, and in particular relates to a parametric wavelet threshold signal denoising method based on an improved artificial bee colony algorithm. Background technique

[0002] Signals are often polluted by noise in the process of acquisition, transmission and processing, which will lead to the degradation of signal quality. The wavelet threshold denoising method can obtain the asymptotically optimal estimation of the original signal, and has been most widely used. The denoising performance of common wavelet threshold denoising methods depends on the accurate estimation of noise variance; however, in practical applications, it is difficult to know the exact noise variance. Another factor that determines the denoising performance of the wavelet threshold denoising method is the threshold function. The common threshold functions include hard threshold function, soft threshold functio...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More