Search results for "ESTIMATION"
showing 10 items of 924 documents
Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems
2015
Abstract A decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented in this paper. The overall system is split into a certain number of non-overlapping areas. Firstly, each area executes its own dynamic state estimation based on local measurements by using the UKF. Next, the consensus algorithm is required to perform only local communications between neighboring areas to diffuse local state information. Finally, according to the global state information obtained by the consensus algorithm, the UKF is run again for each area. Its performance is compared with the distributed UKF without consensus algori…
Towards human cell simulation
2019
The faithful reproduction and accurate prediction of the phe-notypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extr…
PCA Gaussianization for image processing
2009
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transforms are often quite restrictive to describe the PDF of natural images. In fact, additional non-linear processing is needed to overcome the limitations of the model. On the contrary, the class of techniques collectively known as projection pursuit, which solve the high-dimensional problem by sequential univariate solutions, may be applied to very general PDFs (e.g. iterative Gaussianization procedures). However, the associated computational cost has prevented their extensive use in image processing. In this work, w…
Finding essential features for tracking starfish in a video sequence
2004
The paper introduces a software system for detecting and tracking starfish in an underwater video sequence. The target of such a system is to help biologists in giving an estimate of the number of starfish present in a particular area of the sea-bottom. The nature of the input images is characterised by a low signal/noise ratio and by the presence of noisy background represented by pebbles; this makes the detection a non-trivial task. The procedure we use is a chain of several steps that starts from the extraction of the area of interest and ends with a classifier and a tracker providing the necessary information for counting the starfish present in the scene. © 2003 IEEE.
Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization
2008
The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…
A navigation and control algorithm for the position tracking of underwater vehicles
2014
In this paper we consider position control of underwater vehicles through inversion of differential kinematics based on uncalibrated, relative to the water, velocity sensors and unknown marine current. An estimation algorithm, based on the above measurements, estimates calibration parameters and marine current, assuring convergence of the estimated velocities to the true quantities. A kinematic control algorithm assures convergence to zero of the position tracking error. An extension of the basic estimation algorithm has been considered, in which position measurements are considered sampled at low rate and randomly spaced in time. Computer simulations are given of the proposed position trac…
Inference for the interclass correlation in familial data using small sample asymptotics
2012
Inference on the parent-offspring correlation coefficient is an important problem in the analysis of familial data, and point estimates and likelihood based inference are available in the literature. In this work, corrections for the signed log-likelihood ratio test statistics are proposed, based on small sample asymptotics, in order to achieve accurate small sample performance. The corrected statistic can be used for hypothesis testing as well as for interval estimation.
Monte Carlo estimation of transverse and longitudinal correlation functions in the model
2010
Abstract Monte Carlo simulations of the three-dimensional O ( 4 ) model in the ordered phase are performed to study the Goldstone mode effects. Our data show a distinct scaling region, where the Fourier-transformed transverse correlation function behaves as ∝ k − λ ⊥ with λ ⊥ 2 ( λ ≃ 1.95 ), in disagreement with the standard theoretical prediction λ ⊥ = 2 .
Morphostatistical characterization of the spatial galaxy distribution through Gibbs point processes
2021
This paper proposes a morpho-statistical characterisation of the galaxy distribution through spatial statistical modelling based on inhomogeneous Gibbs point processes. The galaxy distribution is supposed to exhibit two components. The first one is related to the major geometrical features exhibited by the observed galaxy field, here, its corresponding filamentary pattern. The second one is related to the interactions exhibited by the galaxies. Gibbs point processes are statistical models able to integrate these two aspects in a probability density, controlled by some parameters. Several such models are fitted to real observational data via the ABC Shadow algorithm. This algorithm provides …
Cost analysis of a vaccination strategy for respiratory syncytial virus (RSV) in a network model
2010
[EN] In this paper an age-structured mathematical model for respiratory syncytial virus (RSV) is proposed where children younger than one year old, who are the most affected by this illness, are specially considered. Real data of hospitalized children in the Spanish region of Valencia are used in order to determine some seasonal parameters of the model. Once the parameters are determined, we propose a complete stochastic network model to study the seasonal evolution of the respiratory syncytial virus (RSV) epidemics. In this model every susceptible individual can acquire the disease after a random encounter with any infected individual in the social network. The edges of a complete graph co…