A new method for regularization parameter determination in the inverse problem of electrocardiography

1997 ◽  
Vol 44 (1) ◽  
pp. 19-39 ◽  
Author(s):  
P.R. Johnston ◽  
R.M. Gulrajani
Keyword(s):  
Inverse Problem ◽  
Regularization Parameter ◽  
New Method ◽  
Parameter Determination ◽  
Inverse Problem Of Electrocardiography

scholarly journals A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Wei Gao ◽  
Kaiping Yu ◽  
Ying Wu
Keyword(s):  
Inverse Problem ◽  
Regularization Method ◽  
Cross Validation ◽  
Regularization Parameter ◽  
New Method ◽  
Parameter Determination ◽  
Load Identification ◽  
Noise Levels ◽  
Regularization Parameters ◽  
Curve Method

According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM) is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV) method and theL-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.

A new method for phemt noise-parameter determination based on 50-Ω noise measurement system

2003 ◽  
Vol 51 (10) ◽  
pp. 2079-2089 ◽  
Author(s):  
Jianjun Gao ◽  
Choi Look Law ◽  
Hong Wang ◽  
S. Aditya ◽  
G. Boeck
Keyword(s):  
Measurement System ◽  
Noise Measurement ◽  
New Method ◽  
Parameter Determination ◽  
Noise Parameter

scholarly journals IPG as a new method to improve the agility of the initial analysis of the inventive design

2021 ◽  
Vol 49 (3) ◽  
pp. 549-562
Author(s):  
Masih Hanifi ◽  
Hicham Chibane ◽  
Rémy Houssin ◽  
Denis Cavallucci
Keyword(s):  
Inverse Problem ◽  
Design Method ◽  
New Method ◽  
Significant Progress ◽  
Initial Analysis ◽  
The Subject ◽  
Time Required

TRIZ method has long proven its value without appearing to the industrial world as inevitable. Design researchers have therefore addressed the limitations of the TRIZ method and have overcome them with more systematic approaches. Among these, the Inventive Design Method (IDM) has been the subject of several articles and put into practice in the industry. It is considered an improvement over TRIZ but still suffers from some drawbacks in terms of the time-consuming nature of its implementation. We focused on the IDM process by trying to both identify its areas of inefficiencies while attempting to preserve the quality of its deliverables. Our approach consists of applying the precepts of Lean to IDM. The result is the Inverse Problem Graph (IPG) method, inspired by IDM, but offering significant progress in reducing the time required to mobilize experts while preserving its inventive outcomes. This article outlines our approach for the construction of this new method.

Compact discrepancy and chi-squared principles for over-determined inverse problems

2017 ◽  
Vol 25 (3) ◽  
Author(s):  
Maxim Pisarenco ◽  
Irwan D. Setija
Keyword(s):  
Inverse Problem ◽  
Inverse Problems ◽  
Regularization Parameter ◽  
Discrepancy Principle ◽  
Chi Squared

AbstractWe discuss and analyze the classical discrepancy principle and the recently proposed and closely related chi-squared principle for selecting the regularization parameter of an inverse problem. Some properties that deteriorate the performance of these methods for over-determined inverse problems are highlighted. We propose a so-called

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