The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 23, 2021

Filed:

Jun. 14, 2018
Applicant:

C.r.f. SocietĂ  Consortile Per Azioni, Orbassano, IT;

Inventors:

Giuseppe D'Angelo, Orbassano, IT;

Gianmarco Genchi, Orbassano, IT;

Alessandro Cisi, Orbassano, IT;

Giorgio Pasquettaz, Orbassano, IT;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G01N 33/48 (2006.01); B23K 26/03 (2006.01); G05B 19/418 (2006.01); G06T 5/00 (2006.01); A61B 5/0402 (2006.01); A61B 5/0488 (2006.01); A61B 5/00 (2006.01); B23K 31/12 (2006.01); G01J 3/28 (2006.01); G01N 21/27 (2006.01); G01N 21/88 (2006.01); G06F 17/16 (2006.01);
U.S. Cl.
CPC ...
B23K 26/032 (2013.01); A61B 5/0402 (2013.01); A61B 5/0488 (2013.01); A61B 5/7203 (2013.01); B23K 26/034 (2013.01); B23K 31/125 (2013.01); G01J 3/2803 (2013.01); G01N 21/274 (2013.01); G01N 21/8851 (2013.01); G05B 19/418 (2013.01); G06F 17/16 (2013.01); G06T 5/002 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30152 (2013.01);
Abstract

A method for performing a noise removal operation includes decomposing an acquired signal considered as one dimensional series. A trajectory matrix is constructed, transforming the trajectory matrix in a form to which single value decomposition is applicable. A single value decomposition is done on the transformed matrix computing eigenvalues and eigenvectors of the matrix. A one dimensional series is reconstructed, corresponding to the denoised signal. After the single value decomposition operation is provided, a single value decomposition is applied sequentially starting from a given window value. For each iteration, the root mean square value is calculated between a current and previous eigenvalue, calculating a minimum and its position of said root mean square value. The iterations are halted if the minimum is lower than a determined threshold value, otherwise increasing the window value and returning to the operation of decomposition of the acquired signal.


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