Unlock instant, AI-driven research and patent intelligence for your innovation.

Robustness compressed sensing method based on Bayes

A compressed sensing and robust technology, applied in electrical components, code conversion, etc., can solve problems such as missing and abnormal measurement values, and achieve low time complexity and obvious advantages

Inactive Publication Date: 2017-05-10
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In response to this kind of problem, we consider a more general problem, that is, some of the measured values ​​are abnormal or missing

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
  • Robustness compressed sensing method based on Bayes
  • Robustness compressed sensing method based on Bayes
  • Robustness compressed sensing method based on Bayes

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The present invention will be further described in detail below in conjunction with specific embodiments.

[0046] A strong robust 1-bit compressed sensing method, the specific steps are as follows:

[0047] S1. Construct a perception matrix A with random sampling properties, sample the signal to obtain y, and set the error preset value ε;

[0048] S2. Construct the prior and posterior distributions of each parameter:

[0049] S3, target update function, corresponding variables at the same time,

[0050]

[0051]

[0052]

[0053]

[0054]

[0055] S4, each parameter a priori:

[0056]

[0057] S5. Utilize the Variational-EM algorithm to update each parameter, and the specific steps are as follows:

[0058] S51, update q x (x): because

[0059]

[0060]

[0061] Among them, D s = diag(s) and D α =diag(α),

[0062] Since x follows a Gaussian distribution, then

[0063] S52, update q α (α): because

[0064]

[0065]

[00...

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 belongs to the technical field of signal detection and estimation and communication and is applied to a scene that a DOA sensor is partially damaged or is abnormal. A realization method is robustness compressed sensing based on Bayes. The invention aims at providing robustness compressed sensing method based on Bayes. According to the method, the problem that abnormities occur in partial observation signals is taken into consideration, thereby carrying out effective recovery on sparse original signals. According to the method, the core thought is automatically detecting positions of abnormal values based on a Bayes frame through utilization of a pointer complying with bernoulli distribution and removing the positions of the abnormal values, thereby carrying out the effective recovery.

Description

technical field [0001] The invention belongs to the field of signal detection and estimation and communication technology, and is used in the scene where the sensor of DOA is partially damaged or abnormal, and the implementation method is robust compressed sensing based on Bayesian estimation. Background technique [0002] DOA (array signal angle of arrival) estimation is a key issue in the field of array signal processing. Correlative expansion has spatial spectrum estimation, and CS can overcome the problem of requiring a large amount of measurement data. To apply compressive sensing theory to the DOA estimation problem, it is necessary to establish a suitable sparse representation of angle estimation, that is, spatial sparsification. The following will be from the common compression scene to the DOA scene. The difference is that the measurement matrix A of the normal compression scene obeys the Gaussian distribution, while the measurement matrix A of the DOA scene obeys ...

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): H03M7/30
CPCH03M7/30
Inventor 方俊万千张丹
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA