Feature extracting method based on improved HHT transformation

A feature extraction and component technology, applied in the field of feature extraction based on improved HHT transformation, can solve the problems of nonlinear and non-stationary signal extraction feature inaccuracy, etc., to achieve efficient extraction, improve efficiency, and improve accuracy

Inactive Publication Date: 2018-07-27
TIANJIN UNIV
View PDF0 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] The current existing problem of inaccurate feat

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
  • Feature extracting method based on improved HHT transformation
  • Feature extracting method based on improved HHT transformation
  • Feature extracting method based on improved HHT transformation

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0033] The feature extraction method based on the improved HHT transform of the present invention will be described in detail below in conjunction with embodiments and drawings.

[0034] Such as figure 1 As shown, the feature extraction method based on improved HHT transformation of the present invention includes the following steps:

[0035] 1) Use wavelet packet to decompose and reconstruct the measured signal x(t) to obtain narrowband signals of different frequency bands; specifically, use db4 or db6 or db7 or db8 in Daubechies wavelet to perform the input measured signal x(t) N-layer wavelet packet decomposition and reconstruction, 2 N For narrowband signals of different frequency bands, the three-layer wavelet packet decomposition diagram is shown as figure 2 As shown in the figure, S represents the measured signal x(t), A represents low frequency, D represents high frequency, and the sequence number at the end represents the number of layers of wavelet packet decomposition. ...

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 feature extracting method based on improved HHT transformation. A wavelet packet is adopted to decompose and reconstruct measured signals to obtain narrow-band signals with different frequent bands; all the narrow-band signals are subjected to empirical-mode decomposition to obtain IMF components of all the narrow-band signals; sifting the IMF components of all the narrow-band signals to obtain final IMF components of the whole measured signals; the final IMF components are subjected to Hilbert transformation respectively to obtain instant attributes of the measured signals; according to the instant attributes of the measured signals, time-frequency statistical characteristics which can reflect the time-frequency characteristics of the measured signals are extracted, wherein the time-frequency statistical characteristics comprise the mean value of the instant amplitude of each IMF component, and the bandwidths, peak values and variances of marginal spectrums of all the IMF components. By means of the feature extracting method based on the improved HHT transformation, the precision of the time-frequency analysis of the signals is improved based on the improved HHT method for wavelet packet decomposition and virtual IMF component removal. The features for reflecting the signal properties can be more efficiently extracted, and finally, the efficiency of data mining and pattern recognition is improved.

Description

technical field [0001] The invention relates to a feature extraction method. In particular, it relates to a feature extraction method based on improved HHT transform for time-frequency analysis of nonlinear and non-stationary time-varying signals. Background technique [0002] 1. Feature extraction [0003] Feature extraction refers to obtaining one or more parameters from the original signal through mathematical transformation or statistical analysis, and these parameters can represent the characteristics of the signal in a certain aspect. These parameters are called the features of the signal, and the process of obtaining these features is feature extraction. Feature extraction is used in the fields of data mining and pattern recognition, and feature extraction is one of the key technologies. Through feature extraction, parameters that can reflect the characteristics of the data in the signal can be obtained, and the quality of the extracted features determines the perf...

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): G06K9/00G06F17/14
CPCG06F17/14G06F2218/08
Inventor 张涛丁碧云赵鑫
Owner TIANJIN UNIV
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap