Sentence examples for fragile estimation from inspiring English sources

Here we show that this claim is the result of a fragile estimation framework capable of producing nearly any result from the reported data, including values tens of orders of magnitude larger or smaller than the one originally reported in (Bushdid et al., 2014).

In this paper, the non-fragile state estimation problem is investigated for a class of continuous neural networks with time-delays and nonlinear perturbations.

In this paper, the non-fragile state estimation problem is investigated for a class of discrete-time neural networks subject to Markovian jumping parameters and time delays.

This paper is concerned with the problem of finite-time l2−l∞ non-fragile state estimation for discrete-time Markov jump neural networks with unreliable communication links.

In addition, some sufficient criteria are given to ensure that the estimation error system is stochastically finite-time stable and stochastically finite-time bounded, and the gains of non-fragile estimator are then derived based on these results.

However, system GMM is a fragile and complicated estimation method, and future work should continue to critically assess its applicability to this issue.

This paper is concerned with the non-fragile H∞ state estimation problem for a class of discrete-time networked system with probabilistic diverging disturbance and multiple missing measurements.

This paper addresses the problem of robust non-fragile H∞ state estimation for discrete-time genetic regulatory networks (GRNs) with exogenous disturbances, parameter uncertainties, and time delays.

The aim of the addressed problem is to design a state estimator such that the estimation performance is non-fragile against the gain variations and also robust against the parameter uncertainties.

We aim to estimate the true concentrations of mRNAs and proteins by designing a non-fragile H∞ estimator such that the estimation error dynamics is stochastically stable while achieving the prescribed H∞ disturbance attenuation level.

The aim of this paper is to estimate the networked system by designing a non-fragile H∞ estimator such that the augmented estimation error system is asymptotically mean square stable with a prescribed H∞ disturbance attention level γ.