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In this section, we propose a channel estimation in order to estimate the CIRs in Table 1.
This paper proposes an analytical hybrid approach for fundamental phasor estimation in order to remove the decaying DC components using Hilbert Transform (HT) and Discrete Fourier Transform (DFT).
Using NIALM algorithms, the transient sensor allows us to determine event detection (On/off operation), while the second one is dedicated to signature analysis and power consumption estimation in order to classify appliances.
The aim of the industrial survey is to promote a discussion on the needs and the expectations regarding cost estimation in order to obtain feedbacks to be addresses in the implementation of a software tool.
Here we present an overview of the steps necessary for effective outlier removal, error propagation and estimation in order to provide reliable confidence limits for the stress value obtained.
Several approaches for robustification of model-based methodologies for the design of optimal experiments have been presented in the past, mainly in the context of maximum-likelihood estimation in order to account for the effect of the nominal values of parameters being far from the true values.
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It is desirable to have an explicit, robust and accurate models for battery states estimation in-order to ensure its proper reliability and safety.
The simulation results provide a good basis for several parameter estimations in order to optimize the synchronization precision for different network topologies.
These estimators use channel estimation models in order to counteract the effect of multipath.
Then, the obtained vectors are lengthened to the frames I t-3 and I t+3 through a motion estimation criterion in order to estimate the trajectory of each block among the frames.
In this paper, we develop an explicit closed-form expression for the Ziv Zakai bound on the mean square estimation error in order to quantify the degradation in estimation performance due to the sidelobe ambiguities.
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