Sentence examples for robustness estimation from inspiring English sources

We propose Quick Robustness Estimation (QRE), a new framework and implementation for estimating the robustness of a network in sub-quadratic time, i.e., significantly faster than betweenness centrality, based on the combination of cheap-to-compute network metrics.

Robustness estimation is critical for the design and maintenance of resilient networks.

Our work contributes towards scalable, yet accurate robustness estimation for large complex networks.

This paper presents an efficient platform for fault robustness estimation of digital circuits.

Existing studies on network robustness usually exploit a single network metric to generate attack strategies, which simulate intentional attacks on a network, and compute a metric-induced robustness estimation, called R. While some metrics are easy to compute, e.g. degree, others require considerable computation efforts, e.g. betweenness centrality.

Non-parametric bootstrapping is the most commonly used robustness estimation method in phylogenetics [ 2, 3].

In Section 3, we present the proposed method for robustness estimation and its implementation in BIOCHAM 2.8.

Finally we observed the robustness estimation of the p v a l u e by the resampling methods.

The experiments focused on three main aspects: robustness (successful estimation rate), accuracy (median estimation error), and efficiency (median estimation time), respectively.

However, we show that the robustness of estimation does depend on the control design for regulation and in fact, the robustness of estimation is described by the closed-loop sensitivity transfer function.

Applying L1/L2 framework the robustness and estimation accuracy with respect to model uncertainty are analyzed.