Blind source separation method based on mixed signal local peak value variance detection

A local peak, blind source separation technology, applied in speech analysis, instruments, etc., can solve the problems of inaccurate parameter estimation of mixing matrix, low source signal estimation accuracy, and inability to effectively detect local peaks of signal attenuation.

Inactive Publication Date: 2010-06-09
HARBIN INST OF TECH
View PDF0 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0027] In order to solve the problem that the current DUET blind source separation method cannot effectively detect local peaks in the signal attenuation-delay histogram and estimate the parameters of the mixing matrix inaccurately, resulting in low accuracy of source signal estimation, a method based on local peak variance of mixed signals is proposed Blind source separation method for detection (Sub-area variance peak detection, SV-peakdet)

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
  • Blind source separation method based on mixed signal local peak value variance detection
  • Blind source separation method based on mixed signal local peak value variance detection
  • Blind source separation method based on mixed signal local peak value variance detection

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0046] Specific implementation mode one: combine figure 1 In this embodiment, the blind source separation method based on the local peak variance detection of the mixed signal is realized based on the following system: the blind source separation system is composed of a mixing system and an unmixing system, and the source signal s j (t) and the noise signal v i (t) mixed in the hybrid system, the observed signal through the hybrid system is x i (t), observed signal x i (t) The estimated signal of the source signal separated by the unmixing system is

[0047] The specific steps of the blind source separation method based on local peak variance detection of mixed signals are as follows:

[0048] Step A, by observing the signal x i The relative attenuation and delay parameters of (t) draw the signal attenuation-delay histogram;

[0049] Step B. Traverse the x-axis and y-axis in the signal attenuation-delay histogram plane area Ω obtained in step A, and find all sub-areas Ω...

specific Embodiment approach 2

[0066] Specific embodiment 2: This embodiment further defines step C in specific embodiment 1. In step C, a threshold value threshold δ is set, and the peak sub-region Further screening, select the value a of the center point (i,j) Peak sub-regions greater than the threshold threshold δ Participate in subsequent calculations, that is, satisfy a (i,j) ≥δ peak subregion Participate in subsequent calculations.

[0067] In this embodiment, the threshold δ of the maximum value is manually adjusted and set by technicians according to the actual demand of the signal. Generally, the threshold δ is proportional to the maximum amplitude M in the signal attenuation-delay histogram. For example, the threshold δ of the maximum value in this embodiment can be selected

[0068] In this embodiment, according to the set threshold threshold δ, the peak sub-region After further screening, only the value a of the center point (i,j) It is the maximum value in this sub-region and the su...

specific Embodiment approach 3

[0069] Specific implementation mode three: this implementation mode is a further limitation of step E in specific implementation mode one, in step E, all peak sub-regions The variance of VAR k The method of sorting adopts the "bubble method".

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 blind source separation method based on mixed signal local peak value variance detection, relating to the improvement on a DUET method and solving the problem that the peak value can not be effectively detected in the prior DUET blind source separation method, in particularly comprising the following steps: finding out all N*N grid subregions on a signal source attenuation-delay column diagram; selecting out the subregion of which the value of the central point is maximum in all subregions as the peak value subregion; respectively calculating the average value of the three-dimensional coordinates of all data points in the selected peak value subregion, sequentially solving the distances from each data point to the average value point and calculating variances; sequencing all variances, and extracting the first P larger variances; and transferring the horizontal coordinates and vertical coordinates corresponding to the P peak values to an attenuation-delay array, extracting the peak value by binary time-frequency masks, separating signal sources on the time-frequency domain, and transforming to time domain to obtain the final separation source signals. The method is applicable to general peak value detection, in particular applicable to the peak value detection of the DUET blind source separation method.

Description

technical field [0001] The invention relates to the technical field of blind source separation, in particular to the improvement of the local signal peak detection method of the DUET blind source separation method in time-frequency component analysis. Background technique [0002] Blind Source Separation (BSS) refers to recovering or separating out only the aliasing signal observed by the sensor according to the statistical characteristics of the input source signal without knowing the prior information of the source signal and the transmission channel. process of the source signal. Due to its special properties, it has broad practical application prospects in many fields such as wireless communication, array signal processing, biomedical signal processing, voice signal processing and image signal processing. [0003] At present, the independent component analysis (Independent Component Analysis, ICA) method is applied to most blind source separation problems, but this meth...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G10L21/02G10L21/0272
Inventor 付宁乔立岩彭喜元曹离然
Owner HARBIN INST OF TECH
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
Try Eureka
PatSnap group products