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Parameter Design (parameter + design)

Distribution by Scientific Domains
Mathematics and Statistics60%
Engineering40%

Selected Abstracts

On Verification and Parameter Design in Hybrid Automaton Using Invariant

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 6 2009
LiLi Wang Non-member
Abstract Invariants for hybrid automata are determined from predicates that are constant for every reachable state in the automata. These invariants can be used to verify a given specification by exploiting their characteristics. In this paper, a switched system driven by discrete inputs is used as an example of a hybrid dynamical system. For the system, we propose a verification method for a given specification based on the concept of invariants and a design policy of parameters with which the given specification is satisfied. Some numerical and experimental results are provided to show the validity of the proposed method. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source]

A Comparative Study of Modal Parameter Identification Based on Wavelet and Hilbert,Huang Transforms

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 1 2006
Banfu Yan
Special attention is given to some implementation issues, such as the modal separation and end effect in the WT, the optimal parameter selection of the wavelet function, the new stopping criterion for the empirical mode decomposition (EMD) and the end effect in the HHT. The capabilities of these two techniques are compared and assessed by using three examples, namely a numerical simulation for a damped system with two very close modes, an impact test on an experimental model with three well-separated modes, and an ambient vibration test on the Z24-bridge benchmark problem. The results demonstrate that for the system with well-separated modes both methods are applicable when the time,frequency resolutions are sufficiently taken into account, whereas for the system with very close modes, the WT method seems to be more theoretical and effective than HHT from the viewpoint of parameter design. [source]

Comparison of multivariate methods for robust parameter design in sheet metal spinning

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 3 2004
Corinna Auer
Abstract Sheet metal spinning is a very complex forming process with a large number of quality characteristics. Within the scope of a joint project of the Department of Statistics and the Chair of Forming Technology the impact of process parameters (design factors) on important quality characteristics has been investigated both theoretically and experimentally. In the past, every response has been treated individually and uncontrollable disturbances (noise factors) have been neglected. Now this approach has been extended to robust multiresponse parameter design. For this, a review of common multivariate approaches for robust parameter design has been carried out, which also leads to the proposal of some new variants. In addition to the theoretical comparison, the methods were applied to data gained in the sheet metal spinning process. The obtained results were evaluated in terms of applicability, limitations and quality accuracy. Practical experiments confirmed the high degree of efficiency that the finally proposed method based on desirabilities promises. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Variances Are Not Always Nuisance Parameters

BIOMETRICS, Issue 2 2003
Raymond J. Carroll
Summary In classical problems, e.g., comparing two populations, fitting a regression surface, etc., variability is a nuisance parameter. The term "nuisance parameter" is meant here in both the technical and the practical sense. However, there are many instances where understanding the structure of variability is just as central as understanding the mean structure. The purpose of this article is to review a few of these problems. I focus in particular on two issues: (a) the determination of the validity of an assay; and (b) the issue of the power for detecting health effects from nutrient intakes when the latter are measured by food frequency questionnaires. I will also briefly mention the problems of variance structure in generalized linear mixed models, robust parameter design in quality technology, and the signal in microarrays. In these and other problems, treating variance structure as a nuisance instead of a central part of the modeling effort not only leads to inefficient estimation of means, but also to misleading conclusions. [source]