Search results for "Optimal estimation"

Selection of time windows in the horizontal-to-vertical noise spectral ratio by means of cluster analysis

2016

The selection of the elementary analysis windows in continuous noise recordings for optimal estimation of the mean horizontal‐to‐vertical spectral ratio (HVSR) curve is generally performed by visual inspection of HVSR curves considered as functions of time. Starting from full‐length records, HVSR curves are determined in consecutive time windows of appropriate lengths. Time windows with HVSR curves that are anomalous on the basis of a simple visual inspection are generally ignored in the computation of the average HVSR curve. It is often very difficult to optimize the selection of time windows to be used for the calculation of the HVSR curve representative of a site. The use of nonobjective…

ROTOR FLUX OPTIMAL ESTIMATION FOR INDUCTION MOTOR CONTROL

2005

Abstract The aim of this paper is to analyze and design reduced order observers of the rotor flux of induction motors. The design requirements are: a) the convergence rate of the rotor flux estimation error; b) a low sensitivity to stator and rotor resistance variations; c) a low sensitivity to errors due to the implementation of the observers on microprocessor-based systems. It is shown that, in order to satisfy the requirements a)-c), it is sufficient to solve a constrained optimization problem according to a criterion in which these requirements appear explicitly. The implementation of the observer is discussed. The observer is tested by simulation and experiments.

Optimal estimation of losses at the ultimate quantum limit with non-Gaussian states

2009

We address the estimation of the loss parameter of a bosonic channel probed by arbitrary signals. Unlike the optimal Gaussian probes, which can attain the ultimate bound on precision asymptotically either for very small or very large losses, we prove that Fock states at any fixed photon number saturate the bound unconditionally for any value of the loss. In the relevant regime of low-energy probes, we demonstrate that superpositions of the first low-lying Fock states yield an absolute improvement over any Gaussian probe. Such few-photon states can be recast quite generally as truncations of de-Gaussified photon-subtracted states.

Measurement of damping and temperature: Precision bounds in Gaussian dissipative channels

2011

We present a comprehensive analysis of the performance of different classes of Gaussian states in the estimation of Gaussian phase-insensitive dissipative channels. In particular, we investigate the optimal estimation of the damping constant and reservoir temperature. We show that, for two-mode squeezed vacuum probe states, the quantum-limited accuracy of both parameters can be achieved simultaneously. Moreover, we show that for both parameters two-mode squeezed vacuum states are more efficient than either coherent, thermal or single-mode squeezed states. This suggests that at high energy regimes two-mode squeezed vacuum states are optimal within the Gaussian setup. This optimality result i…

static optimal estimation of joint accelerations for inverse dynamics problem solution

2002

In inverse dynamics computations, the accuracy of the solution strongly depends on the accuracy of the input data. In particular, estimated joint moments are highly sensitive to uncertainties in acceleration data. The aim of the present work was to improve classical inverse dynamics computations by providing an accurate estimation of accelerations. Accelerations are usually calculated from noise-polluted position data using numerical double differentiation, which amplifies measurement noise. The objective of the present paper is to use all available imperfect position and force measurements to extract optimum acceleration estimations. A weighted least-squares optimisation approach is used t…

Use of functionals in linearization and composite estimation with application to two-sample survey data

2009

An important problem associated with two-sample surveys is the estimation of nonlinear functions of finite population totals such as ratios, correlation coefficients or measures of income inequality. Computation and estimation of the variance of such complex statistics are made more difficult by the existence of overlapping units. In one-sample surveys, the linearization method based on the influence function approach is a powerful tool for variance estimation. We introduce a two-sample linearization technique that can be viewed as a generalization of the one-sample influence function approach. Our technique is based on expressing the parameters of interest as multivariate functionals of fi…

2013

Abstract. It has become possible to retrieve the global, long-term trends of trace gases that are important to atmospheric chemistry, climate, and air quality from satellite data records that span more than a decade. However, many of the satellite remote sensing techniques produce measurements that have variable sensitivity to the vertical profiles of atmospheric gases. In the case of constrained retrievals like optimal estimation, this leads to a varying amount of a priori information in the retrieval and is represented by an averaging kernel (AK). In this study, we investigate to what extent the estimation of trends from retrieved data can be biased by temporal changes of averaging kernel…