Results 61 to 70 of about 2,193 (205)
A Stochastic Framework for Subspace Identification of a Strongly Nonlinear Aerospace Structure [PDF]
The present study exploits the maximum likelihood identification framework for deriving statistically-optimal models of nonlinear mechanical systems. The identification problem is formulated in the frequency domain, and model parameters are calculated by minimising a weighted least-squares cost function.
Noël, Jean-Philippe +2 more
openaire +2 more sources
Survey on differential estimators for 3d point clouds
Computer Graphics Forum, EarlyView.Abstract Recent advancements in 3D scanning technologies, including LiDAR and photogrammetry, have enabled the precise digital replication of real‐world objects. These methods are widely used in fields such as GIS, robotics, and cultural heritage. However, the point clouds generated by such scans are often noisy and unstructured, posing challenges for ...
Léo Arnal–Anger +4 more
wiley +1 more source
LQ decomposition based subspace identification under deterministic type disturbance
Systems Science & Control Engineering, 2017 To overcome the influence from deterministic type load disturbance with unknown dynamics, a bias-eliminated subspace identification method is proposed for consistent estimation.
Shengnan Zhang +3 more
doaj +1 more source
Establishing Shape Correspondences: A Survey
Computer Graphics Forum, EarlyView.Abstract Shape correspondence between surfaces in 3D is a central problem in geometry processing, concerned with establishing meaningful relations between surfaces. While all correspondence problems share this goal, specific formulations can differ significantly: Downstream applications require certain properties that correspondences must satisfy ...
A. Heuschling, H. Meinhold, L. Kobbelt
wiley +1 more source
Understanding Stochastic Subspace Identification
, 2006 The data driven Stochastic Subspace Identification techniques is considered to be the most powerful class of the known identification techniques for natural input modal analysis in the time domain. However, the techniques involves several steps of "mysterious mathematics" that is difficult to follow and to understand for people with a classical ...
Brincker, Rune, Andersen, Palle
openaire +1 more source
Computer Graphics Forum, EarlyView.We present an interactive visual analysis tool to study how patient‐specific tissue properties influence radiofrequency ablation outcomes. Using a deep‐learning surrogate model, we predict ablation volumes for unseen parameter settings with accuracy superior to interpolation, supporting improved treatment planning. Abstract Radiofrequency (RF) ablation
R. Sabbagh Gol +7 more
wiley +1 more source
To Grandmother's House We Go: Informal Childcare and Female Labor Mobility
International Economic Review, EarlyView.ABSTRACT We document how childcare costs and the location of extended family influence the labor supply and mobility of US women. Women return to their home locations immediately before fertility events, suggesting that informal childcare needs may motivate home migration. Women who live near their parents have lower child earnings penalties.
Garrett Anstreicher, Joanna Venator
wiley +1 more source
Automated Modal Analysis Using Stochastic Subspace Identification and Field Monitoring Data
Applied SciencesThe accurate identification of modal parameters is essential for structural health monitoring (SHM), as it provides critical insights into the presence of damage or degradation within the structure.
Shieh-Kung Huang +3 more
doaj +1 more source
The combined deterministic stochastic subspace based system identification in buildings
Structural Engineering and Mechanics, 2011 The Combined Deterministic Stochastic Subspace based System Identification Technique (CDSSSIT) is a powerful input-output system identification technique which is known to be always convergent and numerically stable. The technique determines a Kalman state sequence from the projection of the output-input data.
openaire +2 more sources
On Metric Choice in Dimension Reduction for Fréchet Regression
International Statistical Review, EarlyView.Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale +3 more
wiley +1 more source