Skip to main navigation
Skip to search
Skip to main content
Universidad de los Andes Home
English
Español
Search content at Universidad de los Andes
Home
Profiles
Research units
Research output
Projects
Press/Media
Activities
Equipment
Student theses
Prizes
Courses
Impacts
Adaptive Kalman filters for nonlinear finite element model updating
Mingming Song
,
Rodrigo Astroza
, Hamed Ebrahimian
, Babak Moaveni
*
, Costas Papadimitriou
*
Corresponding author for this work
Doctorado en Ciencias de la Ingeniería
Línea de investigación en Sistemas de Ingeniería Civil
Ingeniería Civil en Obras Civiles
Claustro Doctorado en Ciencias de la Ingeniería
Facultad de Ingeniería y Ciencias Aplicadas
Universidad de los Andes
Research output
:
Contribution to journal
›
Article
›
peer-review
156
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Adaptive Kalman filters for nonlinear finite element model updating'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Nonlinear Finite Element Model Updating
100%
Adaptive Kalman Filter
100%
Adaptive Approach
100%
Adaptive Filter
75%
Non-adaptive
75%
Noise Measurement
50%
Covariance Matrix
50%
Numerical Application
50%
Nonlinear Model Updating
50%
Forgetting Factor
50%
Adaptive Method
50%
Dual-adaptive
50%
Unscented Kalman Filter
25%
Parameter Estimation
25%
Extended Kalman Filter
25%
Response Prediction
25%
Steel Frame Structure
25%
Covariance Matching Technique
25%
Nonlinear Parameter
25%
Kalman Filter Algorithm
25%
Measurement Simulation
25%
Unscented
25%
First Application
25%
Ensemble Kalman Filter (EnKF)
25%
Steel pier
25%
Nonlinear Material Properties
25%
Acceptable Accuracy
25%
Robust Parameter Estimation
25%
Sliding Window Method
25%
Tuning Process
25%
Nonlinear Kalman Filter
25%
Modeling Error
25%
Accuracy in Parameter Estimation
25%
Physics
Covariance
100%
Adaptive Filter
100%
Finite Element Modeling
100%
Noise Measurement
66%
Parameter Estimation
66%
Mathematics
Numerical Method
28%