These error measurements were input to the Rosetta error model, which was used for subsequent analysis of statistical significance of differential gene expression.
A deterministic observer-based fault detection filter (FDF) is considered as residual generator and, based on this, the FDF is designed such that the l2-induced gain from unknown input to the estimation error between residual signal and weighted fault is less than a prescribed value in a probabilistic framework.
An upper bound to the H∞ norm of the transfer-function from the system input to the filtering error is used as performance criterion.
Robust performance is measured by the H2 and H∞ norms of the transfer function from the noisy input to the filtering error.
We propose a variation of the "regression-like" design introduced by Byrnes and Isidori (2004), showing how it is possible to move the internal model from the control input to the regulation error.
If sufficient conditions are satisfied, robustness in terms of the L2 gain from the disturbance input to the tracking error performance variable can be guaranteed and calculated a priori.
In the framework of linear matrix inequalities, the aperiodically intermittent H∞ synchronization controller is designed, which guarantees internally exponential stability as well as a prescribed L2-gain from the exogenous input to the regulated error output.
The purpose of the paper is to design a filter such that the error filtering system not only satisfies the prescribed circular pole constraints or D-stability constraint, but also meets the prescribed H∞ norm constraint on the transfer function from the disturbance input to the estimation error.
The goal is to design a dynamical observer such that the resulting dynamic estimation error is stable while the transfer function from the disturbance input to this error satisfies a prescribed H∞ norm level.
DOI: http://dx.doi.org/10.7554/eLife.02076.002 The cerebellum is thought to implement a supervised learning algorithm, with the climbing fiber input to the cerebellum providing error signals that induce learning.
According to the method in which the signals from the electrodes placed on the abdomen as desired and the signals from the electrodes placed on the limbs as input to the adaptive filter, the error signal can be obtained to represent the extracted FECG.
