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The Diffusion Kernel Filter
(SPRINGER, 2009)
A particle filter method is presented for the discrete-time filtering problem with nonlinear ItA ` stochastic ordinary differential equations (SODE) with additive noise supposed to be analytically integrable as a function ...
State-of-charge estimation to improve energy conservation and extend battery life of wireless sensor network nodes
(2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN)2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 07/27/2017)
Wireless sensor networks are pervasive systems that continuously demonstrate increase in growth by branching into diverse applications. The state of charge is an indicator that conveys the amount of energy available in the ...
An approach to real-coded quantum inspired evolutionary algorithm using particles filter
(Institute of Electrical and Electronics Engineers Inc., 2016)
This work proposes, implements and evaluates the FP-QIEA-R model as a new quantum inspired evolutionary algorithm based on the concept of quantum superposition that allows the optimization process to be carried on with a ...
State estimation in bioheat transfer: a comparison of particle filter algorithms
(Emerald Group Publishing Limited, 2017-12)
Purpose The purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle ...
Real-time monitoring and diagnosis in dynamic systems using particle filtering methods-Edición Única
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2003-05-01)
Fault diagnosis is a critical task for many real-world processes. The diagnosis problem is that of estimating the
most probable state of a process over time given noisy observations. For many applications, the complex ...
Combined parameter and state estimation in the radio frequency hyperthermia treatment of cancer
(Taylor & Francis, 2016-08-18)
Particle filters are general methods for the solution of state estimation problems, which can be applied to nonlinear models with non-Gaussian uncertainties. In this paper, an algorithm of the particle filter is used for ...
The analog data assimilation
(American Meteorological Society, 2017-10)
In light of growing interest in data-driven methods for oceanic, atmospheric, and climate sciences, this work focuses on the field of data assimilation and presents the analog data assimilation (AnDA). The proposed framework ...
An overview of methods of fine and ultrafine particle collection for physicochemical characterisation and toxicity assessments
Particulate matter (PM) is a crucial health risk factor for respiratory and cardiovascular diseases.
The smaller size fractions, ≤2.5μm (PM2.5; fine particles) and ≤0.1μm (PM0.1; ultrafine particles),
show the highest ...
Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods
(Taylor & Francis, 2018-01)
For modelling geophysical systems, large-scale processes are described through a set of coarse-grained dynamical equations while small-scale processes are represented via parameterizations. This work proposes a method for ...
Influence of particle mass fraction over the turbulent behaviour of an incompressible particle-laden flow
(MDPI, 2021-10-21)
The presence of spherical solid particles immersed in an incompressible turbulent flow was
numerically investigated from the perspective of the particle mass fraction (PMF or φm), a measure
of the particle-to-fluid mass ...