Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Weak signal extracting method based on self-adaptive stochastic resonance

A stochastic resonance, weak signal technology, applied in magnetic resonance measurement, material analysis through resonance, magnetic property measurement, etc., can solve the problems of weak signal detection and signal feature extraction can not meet

Inactive Publication Date: 2012-07-25
UNIV OF ELECTRONIC SCI & TECH OF CHINA
View PDF7 Cites 34 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to solve the problem that the detection of weak signals and the extraction of signal features cannot meet the needs of practical applications under extremely low SNR

Method used

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
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Weak signal extracting method based on self-adaptive stochastic resonance
  • Weak signal extracting method based on self-adaptive stochastic resonance
  • Weak signal extracting method based on self-adaptive stochastic resonance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] Combine below Figure 1 to Figure 8 The weak signal extraction method of the present invention is described, figure 1 It is a structural block diagram of the weak signal extraction method of the present invention, figure 2 It is a schematic diagram of the weak signal extraction process of the present invention, which specifically includes the following steps:

[0028] S1. Initialization parameters: The parameters specifically include, the resampling scale conversion factor R, the increase step size ΔR of the scale conversion factor; the inherent parameter a of stochastic resonance, and the reference frequency f for generating stochastic resonance ref , f ref The calculation offset Δf of the zero frequency calculation offset Δf 0 ; Spectral magnitude comparison coefficient m.

[0029] The following describes the values ​​of the initial parameters in detail:

[0030] f ref The value of is the frequency value at which the adaptive stochastic resonance system is easy...

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

PUM

No PUM Login to View More

Abstract

The invention discloses a weak signal extracting method based on self-adaptive stochastic resonance. Particularly, a frequency of a weak signal can be well adjusted to a frequency range easily generating the self-adaptive stochastic resonance through adjusting a scale changing factor which is secondarily sampled, so that the good performance of the self-adaptive stochastic resonance can be sufficiently utilized, the weak signal can be well extracted at a super-low signal to noise ratio, and the problem that the conventional weak signal processing method represents to be poor, even be invalid, at the super-low signal to noise ratio can be effectively solved; and meanwhile, a signal frequency of the weak signal which is secondarily sampled can be matched with a self-adaptive stochastic resonance system and can generate stochastic resonance through a fed-back automatic adjusting scale conversion factor under the condition of not knowing the frequency of the weak signal, so that the characteristic of the weak signal can be better extracted.

Description

technical field [0001] The invention belongs to the technical field of signal processing and communication, and in particular relates to the extraction of weak signals. Background technique [0002] Weak signal detection occupies an important position in the high-tech field, and is the premise and basis for the application of many technologies. Generally, the low-energy signal submerged in the strong background noise is called a weak signal. The processing of the weak signal generally uses modern signal processing methods and electronics to suppress the noise, and then extracts the weak signal from the strong background noise. However, there are certain limitations in the existing methods, mainly manifested in the relatively high signal-to-noise ratio (SNR) required for weak signals that can be detected. The extraction effect cannot meet the actual demand. [0003] The study found that applying the principle of Stochastic Resonance (SR) to the detection of weak signals has...

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

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G01R33/20
Inventor 张少文王军李少谦
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com