Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for detecting nanovolt-level weak sinusoidal signals by chaotic system based on principal component analysis

A principal component analysis and chaotic system technology, applied in the field of chaotic system detection of nanovolt-level weak sinusoidal signals, can solve the problems of large difference in magnitude of eigenvalues ​​and limited detection ability of weak signals, etc., to improve detection ability and simple operation Effect

Active Publication Date: 2020-05-22
LUOYANG NORMAL UNIV
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for the detection of nanovolt-level weak signals in the background of strong noise, due to the large difference in the magnitude of the eigenvalues ​​in the signal subspace and the noise subspace, limited by the calculation accuracy of the computer, the detection ability of the principal component analysis technology for weak signals is limited.

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
  • Method for detecting nanovolt-level weak sinusoidal signals by chaotic system based on principal component analysis
  • Method for detecting nanovolt-level weak sinusoidal signals by chaotic system based on principal component analysis
  • Method for detecting nanovolt-level weak sinusoidal signals by chaotic system based on principal component analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0068] Suppose the nanovolt level weak sinusoidal signal to be measured is s(t)=msin(10πt), where the amplitude m=10 -10 V, the frequency is 5Hz; the background noise is composed of three signal sources, that is, the amplitude is 10 -9 V, a periodic triangular wave signal with a frequency of 10Hz; the amplitude is 10 -8 V, a periodic square wave signal with a frequency of 5Hz; the power is 9×10 -19 Gaussian white noise for W. The three signal sources in the nanovolt-level sinusoidal signal to be tested and the background noise are all linearly superimposed and mixed. The mixed signal to be tested and its composition are as follows figure 1 shown.

[0069] To perform principal component analysis on the mixed signal to be tested, first zero-mean the mixed signal, and calculate the corresponding covariance matrix according to formula (2); sort the eigenvalues ​​of the covariance matrix from large to small, and use the formula Sub(3) extracts the principal component of the mi...

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 relates to a method for detecting nanovolt-level weak sinusoidal signals by a chaotic system based on principal component analysis, and a principal component analysis technology is introduced to overcome the limitation that an existing chaotic system detects the nanovolt-level weak sinusoidal signal in a mixed signal. The method comprises carrying out zero-mean preprocessing on the to-be-measured mixed signal, and solving a covariance matrix, a characteristic value and a corresponding characteristic vector of the to-be-measured signal; arranging the characteristic values of the covariance matrix from large to small, extracting a main component corresponding to a periodic signal in the mixed signal, and abandoning the main component; taking the mixed signal of the abandoned principal component as a built-in driving force of the chaotic system, and detecting the frequency of a weak sinusoidal signal according to the phase state change of a chaotic oscillator; and extractingthe amplitude of the nanovolt sinusoidal signal to be measured according to the jump of the chaotic oscillator from the critical periodic state to the large-scale periodic state. According to the method, influence of other periodic signals in the mixed signals on weak sinusoidal signal detection of the chaotic system is reduced, the detection capability of the chaotic system is improved, and theoperation is simple and feasible.

Description

technical field [0001] The invention belongs to the technical field of measurement, and relates to a method for detecting nanovolt-level weak sinusoidal signals by a chaotic system of principal component analysis. Background technique [0002] At present, weak signal detection technology is a comprehensive technology and frontier field in signal processing. Due to the universality of Fourier series, the detection of sinusoidal signals in the background of strong noise has attracted much attention. At present, the research on the theory and method of nanovolt-level weak sinusoidal signal detection not only has great theoretical significance, but also has urgent needs and important practical significance in the fields of remote sensing measurement, fault diagnosis, system identification, physics, and biomedicine. [0003] The sensitivity of chaotic system to periodic signal and immunity to noise make it play an important role in many weak signal detection techniques. The wea...

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): G01R23/02
CPCG01R23/02
Inventor 贺秋瑞李德光张永新贾世杰金彦龄周莉朱艺萍
Owner LUOYANG NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products