Stochastic resonance method based on multi-scale noise adjustment

A stochastic resonance, multi-scale technology, applied in the field of signal processing, to achieve the effect of less adjustment parameters, insensitive noise intensity, and high signal-to-noise ratio

CN103699513AActive Publication Date: 2014-04-02UNIV OF SCI & TECH OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2014-04-02

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Abstract

The invention provides a stochastic resonance method based on multi-scale noise adjustment. Relations among a nonlinear system, signals and noise are balanced only by adjusting multi-scale noise modes of the signals according to weak signal detection under a strong noise background, so that a stochastic resonance effect under the fixed nonlinear system and the fixed input noise is realized. By the method, the multi-scale noise modes of the signals to be processed are adjusted, so that the strength of the signals at the scale of signal characteristic frequency is the highest and then gradually reduced along with increase of the scale frequency, the nonlinear system, the signals and the noise are optimally matched by adjusting optimal parameters, so that the stochastic resonance effect under the fixed nonlinear system and the fixed input noise is realized. The method at least has the advantages that adjusting parameters are fewer, the method is insensitive to the noise strength of the signals, high frequency can be directly detected, higher signal-to-noise ratio can be obtained and the like.
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Description

technical field

[0001] The invention belongs to the technical field of signal processing, and in particular relates to a stochastic resonance method based on multi-scale noise adjustment, which can be used for weak signal detection under strong noise background. Background technique

[0002] In the fields of industry and medical treatment, due to the complex and changeable on-site conditions, the measured monitoring signals often contain a large degree of noise, making useful information appear very weak, which brings certain difficulties to signal analysis and feature extraction. Therefore, signal denoising is the most basic and important technique in measurement signal processing.

[0003] Traditional denoising methods usually use filtering technology, which regards the noise in the noisy signal as useless information and filters it out, thereby improving the signal-to-noise ratio. However, weak characteristic signals submerged in noise are still polluted by narrowband no...

Examples

Embodiment Construction

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0032] It can be seen from the background technology that the existing stochastic resonance technology needs to first convert the high-frequency signal to be detected to a low frequency, and also needs to adjust the parameters of the nonlinear stochastic resonance system and the noise intensity, so the implementation is relatively complicated, and the noise pattern has been determined. The signal under test does not perform well.

[0033] Therefore, the pre...