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All output measurements from the various machine vision methodologies were analyzed with custom software in Matlab.
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Several cases of surfaces manufactured by various levels of fabrication errors and also different types of metrology systems are studied and the convergence of the employed methodologies are analyzed.
The errors that may be induced by this type of methodology were analyzed in some studies (Park and Gil 2004; Park and Kang 2003).
Assumptions and errors of the methodology are analyzed.
Can the significance of Dedekind's methodology be analyzed further, or can it be articulated in other terms?
The convergence of the proposed methodology was analyzed using Lyapunov stability theory.
The results obtained from one study case applying the methodology are analyzed.
Finally the accuracy of each methodology is analyzed and the pros and cons of each one are shown.
The convergence aspects of the proposed methodology are analyzed and a numerical validation is explored through three applications of increasing complexity.
The advantages and disadvantages of this methodology are analyzed in terms of numerical convergence and positive definiteness of the estimated T-copula correlation matrix.
Proposed methodology is analyzed and tested for the following criteria: Bijective property, nonlinearity, strict avalanche criterion, output bits independence criterion and equiprobable input/output XOR distribution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com