Efficient Multi-Order Uncertainty Computation for Stochastic Subspace Identification

By Michael Döhler, Laurent Mevel. 2013

154 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6d1c875a3c523cfed383b79dcad8a2c78acdcd7c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Philippe Mellinger
2. Michael Döhler
3. Laurent Mevel

In Statistics and Probability

1. Philippe Mellinger
2. Michael Döhler
3. Laurent Mevel

Citations in the corpus

• Variance estimation of modal parameters from output-only and input/output subspace-based system identification (2016, methodology): “In the present paper, this covariance computation approach is generalized to a wider class of subspace algorithms in both outputonly and input/output frameworks, and for covariance-driven and data-driven methods, while keeping the advantages of the previously published method in [28] in terms of eff”