Hankel matrix structure optimization method and device, computing equipment and storage medium

Abstract

The invention discloses a Hankel matrix structure optimization method and a device, computing equipment and a storage medium, and the method comprises the steps: setting an initial value of an iteration parameter, and setting the effective order of matrix reconstruction as k = 1; constructing a Hankel matrix by taking different values of the matrix parameter L, reconstructing a signal through SVDand calculating a signal-to-noise ratio to obtain a relation curve of the signal-to-noise ratio and the matrix parameter L; detecting whether the relation curve is a characteristic signal-to-noise ratio curve; taking a first peak point coordinate of the characteristic signal-to-noise ratio curve as a value of a matrix parameter L, setting a matrix column number as L + 1, and setting a matrix row number as N-L; wherein N is the signal length, and N is greater than L. The method can effectively improve the signal denoising efficiency.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a Hankel matrix structure optimization method, device, computing device and storage medium. Background technique [0002] In the prior art, the SVD (Singular Value Decomposition) denoising algorithm has good stability and invariance, and is widely used in the field of signal processing, such as feature extraction of bearing vibration signals and biological signal processing. The main feature of SVD is that it can decompose the signal into a linear superposition of multiple component signals, and reconstruct the denoising signal by selecting useful components, while the SVD denoising effect is determined by the Hankel matrix structure (including the number of rows and columns) and the effective singular value ( or effective order) are jointly determined. At present, the common method to determine the structure of the Hankel matrix is ​​the maximum dimension method, that...

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Problems solved by technology

At present, the common method to determine the structure of the Hankel matrix is ​​the maximum dimension method, that is, to make the difference between the number of rows and the number of columns of the matrix as 1 as possible, and the constructed matrix is ​​square or very close to square. However, it is found in practical applications that if the The noise-to-signal-to-noise ratio is a reference index. The denoising effect of the square Hankel matrix is ​​not ideal. There are many singular values ​​to be calculated, and the calculation time is long, resulting in low calculation efficiency.

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