Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception.

Science.gov (United States)

Kutschireiter, Anna; Surace, Simone Carlo; Sprekeler, Henning; Pfister, Jean-Pascal

2017-08-18

The robust estimation of dynamical hidden features, such as the position of prey, based on sensory inputs is one of the hallmarks of perception. This dynamical estimation can be rigorously formulated by nonlinear Bayesian filtering theory. Recent experimental and behavioral studies have shown that animals' performance in many tasks is consistent with such a Bayesian statistical interpretation. However, it is presently unclear how a nonlinear Bayesian filter can be efficiently implemented in a network of neurons that satisfies some minimum constraints of biological plausibility. Here, we propose the Neural Particle Filter (NPF), a sampling-based nonlinear Bayesian filter, which does not rely on importance weights. We show that this filter can be interpreted as the neuronal dynamics of a recurrently connected rate-based neural network receiving feed-forward input from sensory neurons. Further, it captures properties of temporal and multi-sensory integration that are crucial for perception, and it allows for online parameter learning with a maximum likelihood approach. The NPF holds the promise to avoid the 'curse of dimensionality', and we demonstrate numerically its capability to outperform weighted particle filters in higher dimensions and when the number of particles is limited.

The 2D Hotelling filter - a quantitative noise-reducing principal-component filter for dynamic PET data, with applications in patient dose reduction

International Nuclear Information System (INIS)

Axelsson, Jan; Sörensen, Jens

2013-01-01

In this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise from dynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. We furthermore show how preprocessing images with this filter improves parametric images created from such dynamic sequence. We use zero-mean unit variance normalization, prior to performing a Hotelling filter on the slices of a dynamic time-series. The Scree-plot technique was used to determine which principal components to be rejected in the filter process. This filter was applied to [ 11 C]-acetate on heart and head-neck tumors, [ 18 F]-FDG on liver tumors and brain, and [ 11 C]-Raclopride on brain. Simulations of blood and tissue regions with noise properties matched to real PET data, was used to analyze how quantitation and resolution is affected by the Hotelling filter. Summing varying parts of a 90-frame [ 18 F]-FDG brain scan, we created 9-frame dynamic scans with image statistics comparable to 20 MBq, 60 MBq and 200 MBq injected activity. Hotelling filter performed on slices (2D) and on volumes (3D) were compared. The 2D Hotelling filter reduces noise in the tissue uptake drastically, so that it becomes simple to manually pick out regions-of-interest from noisy data. 2D Hotelling filter introduces less bias than 3D Hotelling filter in focal Raclopride uptake. Simulations show that the Hotelling filter is sensitive to typical blood peak in PET prior to tissue uptake have commenced, introducing a negative bias in early tissue uptake. Quantitation on real dynamic data is reliable. Two examples clearly show that pre-filtering the dynamic sequence with the Hotelling filter prior to Patlak-slope calculations gives clearly improved parametric image quality. We also show that a dramatic dose reduction can be achieved for Patlak slope images without changing image quality or quantitation. The 2D Hotelling-filtering of dynamic PET data is a computer

NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM

Institute of Scientific and Technical Information of China (English)

ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi

2005-01-01

Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.

Delimiting Coefficient a from Internal Consistency and Unidimensionality

Science.gov (United States)

Sijtsma, Klaas

2015-01-01

I discuss the contribution by Davenport, Davison, Liou, & Love (2015) in which they relate reliability represented by coefficient a to formal definitions of internal consistency and unidimensionality, both proposed by Cronbach (1951). I argue that coefficient a is a lower bound to reliability and that concepts of internal consistency and…

Unidimensionality and reliability under Mokken scaling of the Dutch language version of the SF-36

NARCIS (Netherlands)

Heijden, P.G.M. van der; Buuren, S. van; Fekkes, M.; Radder, J.; Verrips, E.

2003-01-01

The sub-scales of the SF-36 in the Dutch National Study are investigated with respect to unidimensionality and reliability. It is argued that these properties deserve separate treatment. For unidimensionality we use a non-parametric model from item response theory, called the Mokken scaling model,

Nonlinear dynamical system identification using unscented Kalman filter

Science.gov (United States)

Rehman, M. Javvad ur; Dass, Sarat Chandra; Asirvadam, Vijanth Sagayan

2016-11-01

Kalman Filter is the most suitable choice for linear state space and Gaussian error distribution from decades. In general practical systems are not linear and Gaussian so these assumptions give inconsistent results. System Identification for nonlinear dynamical systems is a difficult task to perform. Usually, Extended Kalman Filter (EKF) is used to deal with non-linearity in which Jacobian method is used for linearizing the system dynamics, But it has been observed that in highly non-linear environment performance of EKF is poor. Unscented Kalman Filter (UKF) is proposed here as a better option because instead of analytical linearization of state space, UKF performs statistical linearization by using sigma point calculated from deterministic samples. Formation of the posterior distribution is based on the propagation of mean and covariance through sigma points.

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

Science.gov (United States)

Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

2013-05-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.

Filtering in Hybrid Dynamic Bayesian Networks

Science.gov (United States)

Andersen, Morten Nonboe; Andersen, Rasmus Orum; Wheeler, Kevin

2000-01-01

We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).

The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

Science.gov (United States)

Zhu, Yanqiu; Cohn, Stephen E.; Todling, Ricardo

1999-01-01

The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Dynamical noise filter and conditional entropy analysis in chaos synchronization.

Science.gov (United States)

Wang, Jiao; Lai, C-H

2006-06-01

It is shown that, in a chaotic synchronization system whose driving signal is exposed to channel noise, the estimation of the drive system states can be greatly improved by applying the dynamical noise filtering to the response system states. If the noise is bounded in a certain range, the estimation errors, i.e., the difference between the filtered responding states and the driving states, can be made arbitrarily small. This property can be used in designing an alternative digital communication scheme. An analysis based on the conditional entropy justifies the application of dynamical noise filtering in generating quality synchronization.

Unidimensional factor models imply weaker partial correlations than zero-order correlations.

Science.gov (United States)

van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J

2018-06-01

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.

Estimation of dynamic reactivity using an H∞ optimal filter with a nonlinear term

International Nuclear Information System (INIS)

Suzuki, Katsuo; Watanabe, Koiti

1996-01-01

A method of nonlinear filtering is applied to the problem of estimating the dynamic reactivity of a nonlinear reactor system. The nonlinear filtering algorithm developed is a simple modification of a linear H ∞ optimal filter with a nonlinear feedback loop added. The linear filter is designed on the basis of a linearized dynamical system model that consists of linearized point reactor kinetic equations and a reactivity state equation driven by a fictitious signal. The latter is artificially introduced to deal with the reactivity as a state variable. The results of the computer simulation show that the nonlinear filtering algorithm can be applied to estimate the dynamic reactivity of the nonlinear reactor system, even under relatively large reactivity disturbances

Performance of HEPA filters under hot dynamic conditions

International Nuclear Information System (INIS)

Frankum, D.P.; Costigan, G.

1995-01-01

Accidents in nuclear facilities involving fires may have implications upon the ventilation systems where high efficiency particulate air (HEPA) filters are used to minimise the airborne release of radioactive or toxic particles. The Filter Development Section at Harwell Laboratory has been investigating the effect of temperature on the performance of HEPA filters under hot dynamic conditions[ 1 ] for a number of years. The test rig is capable of delivering air flows of 10001/s (at ambient conditions) at temperatures up to 500 degrees C, where measurements of the penetration and pressure drop across the filter are obtained. This paper reports the experiments on different constructions of HEPA filters; rectangular and circular. The filters were tested at an air temperature of 200 degrees C for up to 48 hours at the rated airflow to assess their performance. The penetration measurements for rectangular filters were observed to be below 0.021% after prolonged operation. In a number of cases, holes appeared along the pleat creases of circular filters although the penetration remained below 1%. The sealing gasket for these filters was noted to deform with temperature, permitting a leakage path. A prototype high strength circular filter was evaluated at temperatures of up to 400 degrees C with a penetration less than 0.65%

Performance of HEPA filters under hot dynamic conditions

Energy Technology Data Exchange (ETDEWEB)

Frankum, D.P.; Costigan, G. [AEA Technology, Oxfordshire (United Kingdom)

1995-02-01

Accidents in nuclear facilities involving fires may have implications upon the ventilation systems where high efficiency particulate air (HEPA) filters are used to minimise the airborne release of radioactive or toxic particles. The Filter Development Section at Harwell Laboratory has been investigating the effect of temperature on the performance of HEPA filters under hot dynamic conditions[{sub 1}] for a number of years. The test rig is capable of delivering air flows of 10001/s (at ambient conditions) at temperatures up to 500{degrees}C, where measurements of the penetration and pressure drop across the filter are obtained. This paper reports the experiments on different constructions of HEPA filters; rectangular and circular. The filters were tested at an air temperature of 200{degrees}C for up to 48 hours at the rated airflow to assess their performance. The penetration measurements for rectangular filters were observed to be below 0.021% after prolonged operation. In a number of cases, holes appeared along the pleat creases of circular filters although the penetration remained below 1%. The sealing gasket for these filters was noted to deform with temperature, permitting a leakage path. A prototype high strength circular filter was evaluated at temperatures of up to 400{degrees}C with a penetration less than 0.65%.

Dynamic positron emission tomography image restoration via a kinetics-induced bilateral filter.

Directory of Open Access Journals (Sweden)

Zhaoying Bian

Full Text Available Dynamic positron emission tomography (PET imaging is a powerful tool that provides useful quantitative information on physiological and biochemical processes. However, low signal-to-noise ratio in short dynamic frames makes accurate kinetic parameter estimation from noisy voxel-wise time activity curves (TAC a challenging task. To address this problem, several spatial filters have been investigated to reduce the noise of each frame with noticeable gains. These filters include the Gaussian filter, bilateral filter, and wavelet-based filter. These filters usually consider only the local properties of each frame without exploring potential kinetic information from entire frames. Thus, in this work, to improve PET parametric imaging accuracy, we present a kinetics-induced bilateral filter (KIBF to reduce the noise of dynamic image frames by incorporating the similarity between the voxel-wise TACs using the framework of bilateral filter. The aim of the proposed KIBF algorithm is to reduce the noise in homogeneous areas while preserving the distinct kinetics of regions of interest. Experimental results on digital brain phantom and in vivo rat study with typical (18F-FDG kinetics have shown that the present KIBF algorithm can achieve notable gains over other existing algorithms in terms of quantitative accuracy measures and visual inspection.

Computational Fluid Dynamics of Choanoflagellate Filter-Feeding

Science.gov (United States)

Asadzadeh, Seyed Saeed; Walther, Jens; Nielsen, Lasse Tore; Kiorboe, Thomas; Dolger, Julia; Andersen, Anders

2017-11-01

Choanoflagellates are unicellular aquatic organisms with a single flagellum that drives a feeding current through a funnel-shaped collar filter on which bacteria-sized prey are caught. Using computational fluid dynamics (CFD) we model the beating flagellum and the complex filter flow of the choanoflagellate Diaphanoeca grandis. Our CFD simulations based on the current understanding of the morphology underestimate the experimentally observed clearance rate by more than an order of magnitude: The beating flagellum is simply unable to draw enough water through the fine filter. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), and addition of a wide vane in our CFD model allows us to correctly predict the observed clearance rate.

Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory

Science.gov (United States)

Bergner, Yoav; Droschler, Stefan; Kortemeyer, Gerd; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.

2012-01-01

We apply collaborative filtering (CF) to dichotomously scored student response data (right, wrong, or no interaction), finding optimal parameters for each student and item based on cross-validated prediction accuracy. The approach is naturally suited to comparing different models, both unidimensional and multidimensional in ability, including a…

Particle Filter Tracking without Dynamics

Directory of Open Access Journals (Sweden)

Jaime Ortegon-Aguilar

2007-01-01

Full Text Available People tracking is an interesting topic in computer vision. It has applications in industrial areas such as surveillance or human-machine interaction. Particle Filters is a common algorithm for people tracking; challenging situations occur when the target's motion is poorly modelled or with unexpected motions. In this paper, an alternative to address people tracking is presented. The proposed algorithm is based in particle filters, but instead of using a dynamical model, it uses background subtraction to predict future locations of particles. The algorithm is able to track people in omnidirectional sequences with a low frame rate (one or two frames per second. Our approach can tackle unexpected discontinuities and changes in the direction of the motion. The main goal of the paper is to track people from laboratories, but it has applications in surveillance, mainly in controlled environments.

Non-linear unidimensional Debye screening in plasmas

International Nuclear Information System (INIS)

Clemente, R.A.; Martin, P.

1992-01-01

An exact analytical solution for T e = T i and an approximate solution for T e ≠ T i have been obtained for the unidimensional non-linear Debye potential. The approximate expression is a solution of the Poisson equation obtained by expanding up to third order the Boltzmann's factors. The analysis shows that the effective Debye screening length can be quite different from the usual Debye length, when the potential to thermal energy ratio of the particles is not much smaller than unity. (author)

The optimal filtering of a class of dynamic multiscale systems

Institute of Scientific and Technical Information of China (English)

PAN Quan; ZHANG Lei; CUI Peiling; ZHANG Hongcai

2004-01-01

This paper discusses the optimal filtering of a class of dynamic multiscale systems (DMS), which are observed independently by several sensors distributed at different resolution spaces. The system is subject to known dynamic system model. The resolution and sampling frequencies of the sensors are supposed to decrease by a factor of two. By using the Haar wavelet transform to link the state nodes at each of the scales within a time block, a discrete-time model of this class of multiscale systems is given, and the conditions for applying Kalman filtering are proven. Based on the linear time-invariant system, the controllability and observability of the system and the stability of the Kalman filtering is studied, and a theorem is given. It is proved that the Kalman filter is stable if only the system is controllable and observable at the finest scale. Finally, a constant-velocity process is used to obtain insight into the efficiencies offered by our model and algorithm.

A Performance Comparison Between Extended Kalman Filter and Unscented Kalman Filter in Power System Dynamic State Estimation

DEFF Research Database (Denmark)

Khazraj, Hesam; Silva, Filipe Miguel Faria da; Bak, Claus Leth

2016-01-01

Dynamic State Estimation (DSE) is a critical tool for analysis, monitoring and planning of a power system. The concept of DSE involves designing state estimation with Extended Kalman Filter (EKF) or Unscented Kalman Filter (UKF) methods, which can be used by wide area monitoring to improve......-linear state estimator is developed in MatLab to solve states by applying the unscented Kalman filter (UKF) and Extended Kalman Filter (EKF) algorithm. Finally, a DSE model is built for a 14 bus power system network to evaluate the proposed algorithm for the networks.This article will focus on comparing...

Spacecraft Dynamics Should be Considered in Kalman Filter Attitude Estimation

Science.gov (United States)

Yang, Yaguang; Zhou, Zhiqiang

2016-01-01

Kalman filter based spacecraft attitude estimation has been used in some high-profile missions and has been widely discussed in literature. While some models in spacecraft attitude estimation include spacecraft dynamics, most do not. To our best knowledge, there is no comparison on which model is a better choice. In this paper, we discuss the reasons why spacecraft dynamics should be considered in the Kalman filter based spacecraft attitude estimation problem. We also propose a reduced quaternion spacecraft dynamics model which admits additive noise. Geometry of the reduced quaternion model and the additive noise are discussed. This treatment is more elegant in mathematics and easier in computation. We use some simulation example to verify our claims.

Study of physical properties of the dynamic filter; Estudo das propriedades fisicas do filtro dinamico

Energy Technology Data Exchange (ETDEWEB)

Souza, Roberto Salomon

2004-02-15

This paper presents a characterization of the physical properties of the dynamic filter of Clinac 2300 CD linear accelerator of Varian Medical Systems, installed at the Cancer National Institute (INCA), Rio de Janeiro. The 'dynamic filter factors' were measured for the 6 and 15 MV photons, in squared and rectangular fields, and compared with factors furnished at the accelerator manual and used by the planning system, IN and OUT positions, at the maximum dose depths, 5 cm, 10 cm and 29 cm, for the 6 and 15 MV photons energies. The results demonstrated that the 'dynamic filter factors' does not changes with depth and the PDP for the opened field are the same for the fields with dynamic filters. Last but not least the dynamic filters were measured and compared with the nominal angles of the accelerator and the planning system, where some discrepancies were reported.

Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Directory of Open Access Journals (Sweden)

Przekop Rafał

2016-09-01

Full Text Available Deep bed filtration is an effective method of submicron and micron particle removal from the fluid stream. There is an extensive body of literature regarding particle deposition in filters, often using the classical continuum approach. However, the approach is not convenient for studying the influence of particle deposition on filter performance (filtration efficiency, pressure drop when non-steady state boundary conditions have to be introduced. For the purposes of this work the lattice-Boltzmann model describes fluid dynamics, while the solid particle motion is modeled by the Brownian dynamics. For aggregates the effect of their structure on displacement is taken into account. The possibility of particles rebound from the surface of collector or reentrainment of deposits to fluid stream is calculated by energy balanced oscillatory model derived from adhesion theory. The results show the evolution of filtration efficiency and pressure drop of filters with different internal structure described by the size of pores. The size of resuspended aggregates and volume distribution of deposits in filter were also analyzed. The model enables prediction of dynamic filter behavior. It can be a very useful tool for designing filter structures which optimize maximum lifetime with the acceptable values of filtration efficiency and pressure drop.

The role of model dynamics in ensemble Kalman filter performance for chaotic systems

Science.gov (United States)

Ng, G.-H.C.; McLaughlin, D.; Entekhabi, D.; Ahanin, A.

2011-01-01

The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.

The unidimensionality and overestimation of metacognitive awareness in children: validating the CATOM

Directory of Open Access Journals (Sweden)

Paula C. Ferreira

2015-10-01

Full Text Available Children often have difficulty in reporting their metacognitive functioning, which leads them to frequently overrating themselves under learning situations. Hence, this study presents a preliminary approach of how children's metacognitive awareness (MA can be measured. Essentially, this study aims to understand how children (n =1029 report their metacognitive functioning. In a first analysis, EFA revealed a unidimensional structure of the instrument (MK and MS. Item Response Theory was then used to analyse the unidimensionality of the dimension and the interactions between participants and items. Results revealed good item reliability (.87 and good person reliability (.87 with good Cronbach's a for MA (.95. These results show the potential of the instrument, as well as a tendency of children to overrate their metacognitive functioning. Implications for researchers and practitioners are discussed.

Distributed Dynamic State Estimation with Extended Kalman Filter

Energy Technology Data Exchange (ETDEWEB)

Du, Pengwei; Huang, Zhenyu; Sun, Yannan; Diao, Ruisheng; Kalsi, Karanjit; Anderson, Kevin K.; Li, Yulan; Lee, Barry

2011-08-04

Increasing complexity associated with large-scale renewable resources and novel smart-grid technologies necessitates real-time monitoring and control. Our previous work applied the extended Kalman filter (EKF) with the use of phasor measurement data (PMU) for dynamic state estimation. However, high computation complexity creates significant challenges for real-time applications. In this paper, the problem of distributed dynamic state estimation is investigated. One domain decomposition method is proposed to utilize decentralized computing resources. The performance of distributed dynamic state estimation is tested on a 16-machine, 68-bus test system.

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

Science.gov (United States)

Rabinowitz, Matthew (Inventor)

2002-01-01

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

Frequency-scanning interferometry using a time-varying Kalman filter for dynamic tracking measurements.

Science.gov (United States)

Jia, Xingyu; Liu, Zhigang; Tao, Long; Deng, Zhongwen

2017-10-16

Frequency scanning interferometry (FSI) with a single external cavity diode laser (ECDL) and time-invariant Kalman filtering is an effective technique for measuring the distance of a dynamic target. However, due to the hysteresis of the piezoelectric ceramic transducer (PZT) actuator in the ECDL, the optical frequency sweeps of the ECDL exhibit different behaviors, depending on whether the frequency is increasing or decreasing. Consequently, the model parameters of Kalman filter appear time varying in each iteration, which produces state estimation errors with time-invariant filtering. To address this, in this paper, a time-varying Kalman filter is proposed to model the instantaneous movement of a target relative to the different optical frequency tuning durations of the ECDL. The combination of the FSI method with the time-varying Kalman filter was theoretically analyzed, and the simulation and experimental results show the proposed method greatly improves the performance of dynamic FSI measurements.

Estudio unidimensional del síndrome de burnout en estudiantes de medicina de Holguín

OpenAIRE

Rosales Ricardo, Yury

2012-01-01

Se realizó un estudio descriptivo transversal entre octubre y noviembre de 2010. Objetivos: Determinar la presencia del Síndrome de Burnout en su enfoque unidimensional en estudiantes de primer año de medicina de la Universidad de Ciencias Médicas de Holguín (UCMH). Métodos: Se escogieron aleatoriamente 70 estudiantes de primer año, 35 de cada sexo (85 % de la población), a los que se les aplicó el instrumento Escala Unidimensional de Burnout Estudiantil. Resultados: El sexo femenino (sin Bur...

Robust filtering for dynamic compensation of self-powered neutron detectors

International Nuclear Information System (INIS)

Peng, Xingjie; Li, Qing; Zhao, Wenbo; Gong, Helin; Wang, Kan

2014-01-01

Highlights: • Three dynamic compensation methods based on robust filtering theory are proposed. • Filter design problems are converted into linear matrix inequality problems. • Rhodium and Vanadium self-powered neutron detectors are used to validate the use of these three dynamic compensation methods. • The numerical simulation results show that all three methods can provide a reasonable balance between response speed and noise suppression. - Abstract: Self-powered neutron detectors (SPNDs), which are widely used in nuclear reactors to obtain core neutron flux distribution, are accurate at steady state but respond slowly to changes in neutron flux. Dynamic compensation methods are required to improve the response speed of the SPNDs and make it possible to apply the SPNDs for core monitoring and surveillance. In this paper, three digital dynamic compensation methods are proposed. All the three methods are based on the convex optimization framework using linear matrix inequalities (LMIs). The simulation results show that all three methods can provide a reasonable balance between response speed and noise suppression

Modeling the system dynamics for nutrient removal in an innovative septic tank media filter.

Science.gov (United States)

Xuan, Zhemin; Chang, Ni-Bin; Wanielista, Martin

2012-05-01

A next generation septic tank media filter to replace or enhance the current on-site wastewater treatment drainfields was proposed in this study. Unit operation with known treatment efficiencies, flow pattern identification, and system dynamics modeling was cohesively concatenated in order to prove the concept of a newly developed media filter. A multicompartmental model addressing system dynamics and feedbacks based on our assumed microbiological processes accounting for aerobic, anoxic, and anaerobic conditions in the media filter was constructed and calibrated with the aid of in situ measurements and the understanding of the flow patterns. Such a calibrated system dynamics model was then applied for a sensitivity analysis under changing inflow conditions based on the rates of nitrification and denitrification characterized through the field-scale testing. This advancement may contribute to design such a drainfield media filter in household septic tank systems in the future.

Dynamic data filtering system and method

Science.gov (United States)

Bickford, Randall L; Palnitkar, Rahul M

2014-04-29

A computer-implemented dynamic data filtering system and method for selectively choosing operating data of a monitored asset that modifies or expands a learned scope of an empirical model of normal operation of the monitored asset while simultaneously rejecting operating data of the monitored asset that is indicative of excessive degradation or impending failure of the monitored asset, and utilizing the selectively chosen data for adaptively recalibrating the empirical model to more accurately monitor asset aging changes or operating condition changes of the monitored asset.

Tunable and reconfigurable multi-tap microwave photonic filter based on dynamic Brillouin gratings in fibers.

Science.gov (United States)

Sancho, J; Primerov, N; Chin, S; Antman, Y; Zadok, A; Sales, S; Thévenaz, L

2012-03-12

We propose and experimentally demonstrate new architectures to realize multi-tap microwave photonic filters, based on the generation of a single or multiple dynamic Brillouin gratings in polarization maintaining fibers. The spectral range and selectivity of the proposed periodic filters is extensively tunable, simply by reconfiguring the positions and the number of dynamic gratings along the fiber respectively. In this paper, we present a complete analysis of three different configurations comprising a microwave photonic filter implementation: a simple notch-type Mach-Zehnder approach with a single movable dynamic grating, a multi-tap performance based on multiple dynamic gratings and finally a stationary grating configuration based on the phase modulation of two counter-propagating optical waves by a common pseudo-random bit sequence (PRBS).

High-Order Model and Dynamic Filtering for Frame Rate Up-Conversion.

Science.gov (United States)

Bao, Wenbo; Zhang, Xiaoyun; Chen, Li; Ding, Lianghui; Gao, Zhiyong

2018-08-01

This paper proposes a novel frame rate up-conversion method through high-order model and dynamic filtering (HOMDF) for video pixels. Unlike the constant brightness and linear motion assumptions in traditional methods, the intensity and position of the video pixels are both modeled with high-order polynomials in terms of time. Then, the key problem of our method is to estimate the polynomial coefficients that represent the pixel's intensity variation, velocity, and acceleration. We propose to solve it with two energy objectives: one minimizes the auto-regressive prediction error of intensity variation by its past samples, and the other minimizes video frame's reconstruction error along the motion trajectory. To efficiently address the optimization problem for these coefficients, we propose the dynamic filtering solution inspired by video's temporal coherence. The optimal estimation of these coefficients is reformulated into a dynamic fusion of the prior estimate from pixel's temporal predecessor and the maximum likelihood estimate from current new observation. Finally, frame rate up-conversion is implemented using motion-compensated interpolation by pixel-wise intensity variation and motion trajectory. Benefited from the advanced model and dynamic filtering, the interpolated frame has much better visual quality. Extensive experiments on the natural and synthesized videos demonstrate the superiority of HOMDF over the state-of-the-art methods in both subjective and objective comparisons.

Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications

Science.gov (United States)

2016-06-01

Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications Executive Summary The Global Positioning system ( GPS ) is the primary...software that may need to be developed for performance prediction of current or future systems that incorporate GPS . The ultimate aim is to help inform...Defence Science and Technology Organisation in 1986. His major areas of work were adaptive tracking , sig- nal processing, and radar systems engineering

A programação por restrições aplicada à um problema de corte unidimensional

OpenAIRE

Preissler Junior, Sigmundo

2009-01-01

Esta dissertação apresenta um estudo sobre o problema de corte unidimensional. Como resultado deste estudo, é proposta e desenvolvida uma aplicação da programação por restrições na solução do problema em uma aplicação industrial. O problema consiste em encontrar uma solução do factível para o problema de corte unidimensional de bobinas de aço, em uma situação real, considerando o tempo de preparação. O algoritmo gera planos de corte para um determinado período. Além da abordagem PSR (Programa...

A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics

Directory of Open Access Journals (Sweden)

Joaquín Míguez

2004-11-01

Full Text Available In recent years, particle filtering has become a powerful tool for tracking signals and time-varying parameters of random dynamic systems. These methods require a mathematical representation of the dynamics of the system evolution, together with assumptions of probabilistic models. In this paper, we present a new class of particle filtering methods that do not assume explicit mathematical forms of the probability distributions of the noise in the system. As a consequence, the proposed techniques are simpler, more robust, and more flexible than standard particle filters. Apart from the theoretical development of specific methods in the new class, we provide computer simulation results that demonstrate the performance of the algorithms in the problem of autonomous positioning of a vehicle in a 2-dimensional space.

Dynamic Optimization of Feedforward Automatic Gauge Control Based on Extended Kalman Filter

Institute of Scientific and Technical Information of China (English)

YANG Bin-hu; YANG Wei-dong; CHEN Lian-gui; QU Lei

2008-01-01

Automatic gauge control is an essentially nonlinear process varying with time delay, and stochastically varying input and process noise always influence the target gauge control accuracy. To improve the control capability of feedforward automatic gauge control, Kalman filter was employed to filter the noise signal transferred from one stand to another. The linearized matrix that the Kalman filter algorithm needed was concluded; thus, the feedforward automatic gauge control architecture was dynamically optimized. The theoretical analyses and simulation show that the proposed algorithm is reasonable and effective.

Modeling of HVDC in Dynamic State Estimation Using Unscented Kalman Filter Method

DEFF Research Database (Denmark)

Khazraj, Hesam; Silva, Filipe Miguel Faria da; Bak, Claus Leth

2016-01-01

HVDC transmission is an integral part of various power system networks. This article presents an Unscented Kalman Filter dynamic state estimator algorithm that considers the presence of HVDC links. The AC - DC power flow analysis, which is implemented as power flow solver for Dynamic State...

Exact solutions for a discrete unidimensional Boltzmann model satisfying all conservation laws

International Nuclear Information System (INIS)

Cornille, H.

1989-01-01

We consider a four-velocity discrete and unidimensional Boltzmann model. The mass, momentum and energy conservation laws being satisfied we can define a temperature. We report the exact positive solutions which have been found: periodic in the space and propagating or not when the time is growing, shock waves similarity solutions and (1 + 1)-dimensional solutions [fr

Multidimensional student skills with collaborative filtering

Science.gov (United States)

Bergner, Yoav; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.

2013-01-01

Despite the fact that a physics course typically culminates in one final grade for the student, many instructors and researchers believe that there are multiple skills that students acquire to achieve mastery. Assessment validation and data analysis in general may thus benefit from extension to multidimensional ability. This paper introduces an approach for model determination and dimensionality analysis using collaborative filtering (CF), which is related to factor analysis and item response theory (IRT). Model selection is guided by machine learning perspectives, seeking to maximize the accuracy in predicting which students will answer which items correctly. We apply the CF to response data for the Mechanics Baseline Test and combine the results with prior analysis using unidimensional IRT.

Static and Dynamic Characteristics of DC-DC Converter Using a Digital Filter

Science.gov (United States)

Kurokawa, Fujio; Okamatsu, Masashi

This paper presents the regulation and dynamic characteristics of the dc-dc converter with digital PID control, the minimum phase FIR filter or the IIR filter, and then the design criterion to improve the dynamic characteristics is discussed. As a result, it is clarified that the DC-DC converter using the IIR filter method has superior performance characteristics. The regulation range is within 1.3%, the undershoot against the step change of the load is less than 2% and the transient time is less than 0.4ms with the IIR filter method. In this case, the switching frequency is 100kHz and the step change of the load R is from 50 Ω to 10 Ω. Further, the superior characteristics are obtained when the first gain, the second gain and the second cut-off frequency are relatively large, and the first cut-off frequency and the passing frequency are relatively low. Moreover, it is important that the gain strongly decreases at the second cut-off frequency because the upper band pass frequency range must be always less than half of the sampling frequency based on the sampling theory.

Coupling of unidimensional neutron kinetics to thermal hydraulics in parallel channels; Acoplamiento de cinetica neutronica unidimensional a canales termohidraulicos en paralelo

Energy Technology Data Exchange (ETDEWEB)

Cecenas F, M.; Campos G, R.M. [IIE, Av. Reforma 113, Col. Palmira, Cuernavaca, Morelos (Mexico)]. e-mail: mcf@iie.org.mx

2003-07-01

In this work the dynamic behavior of a consistent system in fifteen channels in parallel that represent the reactor core of a BWR type, coupled of a kinetic neutronic model in one dimension is studied by means of time series. The arrangement of channels is obtained collapsing the assemblies that it consists the core to an arrangement of channels prepared in straight lines, and it is coupled to the unidimensional solution of the neutron diffusion equation. This solution represents the radial power distribution, and initially the static solution is obtained to verify that the one modeling core is critic. The coupled set nuclear-thermal hydraulics it is solved numerically by means of a net of CPUs working in the outline teacher-slave by means of Parallel Virtual Machine (PVM), subject to the restriction that the pressure drop is equal for each channel, which is executed iterating on the refrigerant distribution. The channels are dimensioned according to the one Stability Benchmark of the Ringhals swedish plant, organized by the Nuclear Energy Agency in 1994. From the information of this benchmark it is obtained the axial power profile for each channel, which is assumed as invariant in the time. To obtain the time series, the system gets excited with white noise (sequence that statistically obeys to a normal distribution with zero media), so that the power generated in each channel it possesses the same ones characteristics of a typical signal obtained by means of the acquisition of those signals of neutron flux in a BWR reactor. (Author)

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

International Nuclear Information System (INIS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-01-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters. (paper)

A MATLAB Package for Markov Chain Monte Carlo with a Multi-Unidimensional IRT Model

Directory of Open Access Journals (Sweden)

Yanyan Sheng

2008-11-01

Full Text Available Unidimensional item response theory (IRT models are useful when each item is designed to measure some facet of a unified latent trait. In practical applications, items are not necessarily measuring the same underlying trait, and hence the more general multi-unidimensional model should be considered. This paper provides the requisite information and description of software that implements the Gibbs sampler for such models with two item parameters and a normal ogive form. The software developed is written in the MATLAB package IRTmu2no. The package is flexible enough to allow a user the choice to simulate binary response data with multiple dimensions, set the number of total or burn-in iterations, specify starting values or prior distributions for model parameters, check convergence of the Markov chain, as well as obtain Bayesian fit statistics. Illustrative examples are provided to demonstrate and validate the use of the software package.

Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters

Directory of Open Access Journals (Sweden)

Wen Xu

2016-10-01

Full Text Available Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackwellized particle filters. Monte Carlo studies reveal the good and stable performance of our particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic volatility exists, our approach can be better than the maximum likelihood estimator which neglects stochastic volatility and generalized method of moments (GMM estimators.

Change detection in the dynamics of an intracellular protein synthesis model using nonlinear Kalman filtering.

Science.gov (United States)

Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel

2015-10-01

A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).

Coalescence of silver unidimensional structures by molecular dynamics simulation

International Nuclear Information System (INIS)

Perez A, M.; Gutierrez W, C.E.; Mondragon, G.; Arenas, J.

2007-01-01

The study of nanoparticles coalescence and silver nano rods phenomena by means of molecular dynamics simulation under the thermodynamic laws is reported. In this work we focus ourselves to see the conditions under which the one can be given one dimension growth of silver nano rods for the coalescence phenomenon among two nano rods or one nano rod and one particle; what allows us to study those structural, dynamic and morphological properties of the silver nano rods to different thermodynamic conditions. The simulations are carried out using the Sutton-Chen potentials of interaction of many bodies that allow to obtain appropriate results with the real physical systems. (Author)

AN EFFECTIVE SPAM FILTERING FOR DYNAMIC MAIL MANAGEMENT SYSTEM

Directory of Open Access Journals (Sweden)

S. Arun Mozhi Selvi

2012-04-01

Full Text Available Spam is commonly defined as unsolicited email messages and the goal of spam categorization is to distinguish between spam and legitimate email messages. The economics of spam details that the spammer has to target several recipients with identical and similar email messages. As a result a dynamic knowledge sharing effective defense against a substantial fraction of spam has to be designed which can alternate the burdens of frequent training stand alone spam filter. A weighted email attribute based classification is proposed to mainly focus to encounter the issues in normal email system. These type of classification helps to formulate an effective utilization of our email system by combining the concepts of Bayesian Spam Filtering Algorithm, Iterative Dichotmiser 3(ID3 Algorithm and Bloom Filter. The details captured by the system are processed to track the original sender causing disturbances and prefer them to block further mails from them. We have tested the effectiveness of our scheme by collecting offline data from Yahoo mail & Gmail dumps. This proposal is implemented using .net and sample user-Id for knowledge base.

Robust filtering and prediction for systems with embedded finite-state Markov-Chain dynamics

International Nuclear Information System (INIS)

Pate, E.B.

1986-01-01

This research developed new methodologies for the design of robust near-optimal filters/predictors for a class of system models that exhibit embedded finite-state Markov-chain dynamics. These methodologies are developed through the concepts and methods of stochastic model building (including time-series analysis), game theory, decision theory, and filtering/prediction for linear dynamic systems. The methodology is based on the relationship between the robustness of a class of time-series models and quantization which is applied to the time series as part of the model identification process. This relationship is exploited by utilizing the concept of an equivalence, through invariance of spectra, between the class of Markov-chain models and the class of autoregressive moving average (ARMA) models. This spectral equivalence permits a straightforward implementation of the desirable robust properties of the Markov-chain approximation in a class of models which may be applied in linear-recursive form in a linear Kalman filter/predictor structure. The linear filter/predictor structure is shown to provide asymptotically optimal estimates of states which represent one or more integrations of the Markov-chain state. The development of a new saddle-point theorem for a game based on the Markov-chain model structure gives rise to a technique for determining a worst case Markov-chain process, upon which a robust filter/predictor design if based

Tuning the Solar Dynamics Observatory Onboard Kalman Filter

Science.gov (United States)

Halverson, Julie Kay; Harman, Rick; Carpenter, Russell; Poland, Devin

2017-01-01

The Solar Dynamics Observatory (SDO) was launched in 2010. SDO is a sun pointing semi-autonomous spacecraft in a geosynchronous orbit that allows nearly continuous observations of the sun. SDO is equipped with coarse sun sensors, two star trackers, a digital sun sensor, and three two-axis inertial reference units (IRU). The IRUs are temperature sensitive and were designed to operate in a stable thermal environment. Due to battery degradation concerns the IRU heaters were not used on SDO and the onboard filter was tuned to accommodate the noisier IRU data. Since launch currents have increased on two IRUs, one had to eventually be powered off. Recent ground tests on a battery similar to SDO indicated the heaters would have negligible impact on battery degradation, so in 2016 a decision was made to turn the heaters on. This paper presents the analysis and results of updating the filter tuning parameters onboard SDO with the IRUs now operating in their intended thermal environment.

Filter-design perspective applied to dynamical decoupling of a multi-qubit system

International Nuclear Information System (INIS)

Su Zhikun; Jiang Shaoji

2012-01-01

We employ the filter-design perspective and derive the filter functions according to nested Uhrig dynamical decoupling (NUDD) and symmetric dynamical decoupling (SDD) in the pure-dephasing spin-boson model with N qubits. The performances of NUDD and SDD are discussed in detail for a two-qubit system. The analysis shows that (i) SDD outperforms NUDD for the bath with a soft cutoff while NUDD approaches SDD as the cutoff becomes harder; (ii) if the qubits are coupled to a common reservoir, SDD helps to protect the decoherence-free subspace while NUDD destroys it; (iii) when the imperfect control pulses with finite width are considered, NUDD is affected in both the high-fidelity regime and coherence time regime while SDD is affected in the coherence time regime only. (paper)

Decentralized control and filtering in interconnected dynamical systems

CERN Document Server

Mahmoud, Magdi S

2011-01-01

Based on the many approaches available for dealing with large-scale systems (LSS), Decentralized Control and Filtering in Interconnected Dynamical Systems supplies a rigorous framework for studying the analysis, stability, and control problems of LSS. Providing an overall assessment of LSS theories, it addresses model order reduction, parametric uncertainties, time delays, and control estimator gain perturbations. Taking readers on a guided tour through LSS, the book examines recent trends and approaches and reviews past methods and results from a contemporary perspective. It traces the progre

Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

Science.gov (United States)

Kelly, David; Majda, Andrew J; Tong, Xin T

2015-08-25

The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.

Dynamics of ions in the selectivity filter of the KcsA channel: Towards a coupled Brownian particle description

OpenAIRE

Cosseddu, Salvatore M.; Khovanov, Igor A.; Allen, Michael P.; Rodger, P. M.; Luchinsky, Dmitry G.; McClintock, Peter V. E.

2013-01-01

The statistical and dynamical properties of ions in the selectivity filter of the KcsA ion channel are considered on the basis of molecular dynamics (MD) simulations of the KcsA protein embedded in a lipid membrane surrounded by an ionic solution. A new approach to the derivation of a Brownian dynamics (BD) model of ion permeation through the filter is discussed, based on unbiased MD simulations. It is shown that depending on additional assumptions, ion’s dynamics can be described either by u...

Analysis of Dynamic Performance of a Kalman Filter for Combining Multiple MEMS Gyroscopes

Directory of Open Access Journals (Sweden)

Liang Xue

2014-11-01

Full Text Available In this paper, the dynamic performance of a Kalman filter (KF was analyzed, which is used to combine multiple measurements of a gyroscopes array to reduce the noise and improve the accuracy of the individual sensors. A principle for accuracy improvement by the KF was briefly presented to obtain an optimal estimate of input rate signal. In particular, the influences of some crucial factors on the KF dynamic performance were analyzed by simulations such as the factors input signal frequency, signal sampling, and KF filtering rate. Finally, a system that was comprised of a six-gyroscope array was designed and implemented to test the dynamic performance. Experimental results indicated that the 1σ error for the combined rate signal was reduced to about 0.2°/s in the constant rate test, which was a reduction by a factor of more than eight compared to the single gyroscope. The 1σ error was also reduced from 1.6°/s to 0.48°/s in the swing test. It showed that the estimated angular rate signal could well reflect the dynamic characteristic of the input signal in dynamic conditions.

On using the dynamic snap-through motion of MEMS initially curved microbeams for filtering applications

KAUST Repository

Ouakad, Hassen M.; Younis, Mohammad I.

2014-01-01

Numerical and experimental investigations of the dynamics of micromachined shallow arches (initially curved microbeams) and the possibility of using their dynamic snap-through motion for filtering purposes are presented. The considered MEMS arches are actuated by a DC electrostatic load along with an AC harmonic load. Their dynamics is examined numerically using a Galerkin-based reduced-order model when excited near both their first and third natural frequencies. Several simulation results are presented demonstrating interesting jumps and dynamic snap-through behavior of the MEMS arches and their attractive features for uses as band-pass filters, such as their sharp roll-off from pass-bands to stop-bands and their flat response. Experimental work is conducted to test arches realized of curved polysilicon microbeams when excited by DC and AC loads. Experimental data of the micromachined curved beams are shown for the softening and hardening behavior near the first and third natural frequencies, respectively, as well as dynamic snap-through motion. © 2013 Elsevier Ltd.

Dynamic spin filtering at the Co/Alq3 interface mediated by weakly coupled second layer molecules

Science.gov (United States)

Droghetti, Andrea; Thielen, Philip; Rungger, Ivan; Haag, Norman; Großmann, Nicolas; Stöckl, Johannes; Stadtmüller, Benjamin; Aeschlimann, Martin; Sanvito, Stefano; Cinchetti, Mirko

2016-08-01

Spin filtering at organic-metal interfaces is often determined by the details of the interaction between the organic molecules and the inorganic magnets used as electrodes. Here we demonstrate a spin-filtering mechanism based on the dynamical spin relaxation of the long-living interface states formed by the magnet and weakly physisorbed molecules. We investigate the case of Alq3 on Co and, by combining two-photon photoemission experiments with electronic structure theory, show that the observed long-time spin-dependent electron dynamics is driven by molecules in the second organic layer. The interface states formed by physisorbed molecules are not spin-split, but acquire a spin-dependent lifetime, that is the result of dynamical spin-relaxation driven by the interaction with the Co substrate. Such spin-filtering mechanism has an important role in the injection of spin-polarized carriers across the interface and their successive hopping diffusion into successive molecular layers of molecular spintronics devices.

Towards denoising XMCD movies of fast magnetization dynamics using extended Kalman filter.

Science.gov (United States)

Kopp, M; Harmeling, S; Schütz, G; Schölkopf, B; Fähnle, M

2015-01-01

The Kalman filter is a well-established approach to get information on the time-dependent state of a system from noisy observations. It was developed in the context of the Apollo project to see the deviation of the true trajectory of a rocket from the desired trajectory. Afterwards it was applied to many different systems with small numbers of components of the respective state vector (typically about 10). In all cases the equation of motion for the state vector was known exactly. The fast dissipative magnetization dynamics is often investigated by x-ray magnetic circular dichroism movies (XMCD movies), which are often very noisy. In this situation the number of components of the state vector is extremely large (about 10(5)), and the equation of motion for the dissipative magnetization dynamics (especially the values of the material parameters of this equation) is not well known. In the present paper it is shown by theoretical considerations that - nevertheless - there is no principle problem for the use of the Kalman filter to denoise XMCD movies of fast dissipative magnetization dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

Science.gov (United States)

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

Optimized chaotic Brillouin dynamic grating with filtered optical feedback.

Science.gov (United States)

Zhang, Jianzhong; Li, Zhuping; Wu, Yuan; Zhang, Mingjiang; Liu, Yi; Li, Mengwen

2018-01-16

Chaotic Brillouin dynamic gratings (BDGs) have special advantages such as the creation of single, permanent and localized BDG. However, the periodic signals induced by conventional optical feedback (COF) in chaotic semiconductor lasers can lead to the generation of spurious BDGs, which will limit the application of chaotic BDGs. In this paper, filtered optical feedback (FOF) is proposed to eliminate spurious BDGs. By controlling the spectral width of the optical filter and its detuning from the laser frequency, semiconductor lasers with FOF operate in the suppression region of the time-delay signature, and chaotic outputs serving as pump waves are then utilized to generate the chaotic BDG in a polarization maintaining fiber. Through comparative analysis of the COF and FOF schemes, it has been demonstrated that spurious BDGs are effectively eliminated and that the reflection characterization of the chaotic BDG is improved. The influence of FOF on the reflection and gain spectra of the chaotic BDG is analyzed as well.

Adaptive wave filtering for dynamic positioning of marine vessels using maximum likelihood identification: Theory and experiments

Digital Repository Service at National Institute of Oceanography (India)

Hassani, V.; Sorensen, A.J.; Pascoal, A.M.

This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. The dynamic model of the vessel captures explicitly the sea state as an uncertain...

Operating regimes of signaling cycles: statics, dynamics, and noise filtering.

Directory of Open Access Journals (Sweden)

Carlos Gomez-Uribe

2007-12-01

Full Text Available A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades. Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive input-output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input-output characteristics. These results are obtained using the total quasi-steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act--in all four regimes--as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways.

A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer.

Science.gov (United States)

Ligorio, Gabriele; Sabatini, Angelo M

2015-08-01

Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in this study. A significant accuracy improvement was achieved over state-of-the-art approaches, due to a filter design that better matched the basic optimality assumptions of Kalman filtering. Human motion tracking is the main application field of the proposed method. Accurately discriminating the two components present in the triaxial accelerometer signal is well suited for studying both the rotational and the linear body kinematics.

H{infinity} Filtering for Dynamic Compensation of Self-Powered Neutron Detectors - A Linear Matrix Inequality Based Method -

Energy Technology Data Exchange (ETDEWEB)

Park, M.G.; Kim, Y.H.; Cha, K.H.; Kim, M.K. [Korea Electric Power Research Institute, Taejon (Korea)

1999-07-01

A method is described to develop and H{infinity} filtering method for the dynamic compensation of self-powered neutron detectors normally used for fixed incore instruments. An H{infinity} norm of the filter transfer matrix is used as the optimization criteria in the worst-case estimation error sense. Filter modeling is performed for both continuous- and discrete-time models. The filter gains are optimized in the sense of noise attenuation level of H{infinity} setting. By introducing Bounded Real Lemma, the conventional algebraic Riccati inequalities are converted into Linear Matrix Inequalities (LMIs). Finally, the filter design problem is solved via the convex optimization framework using LMIs. The simulation results show that remarkable improvements are achieved in view of the filter response time and the filter design efficiency. (author). 15 refs., 4 figs., 3 tabs.

Arte em Herbert Marcuse: formação e resistência à sociedade unidimensional

Directory of Open Access Journals (Sweden)

Juliana Castro Chaves

2014-04-01

Full Text Available Este trabalho é resultado de uma pesquisa teórica que teve como objetivo analisar a contribuição de Herbert Marcuse, autor da teoria crítica da sociedade, para pensar a relação entre arte, sujeito e formação para a resistência à sociedade unidimensional. Foram estudados os seguintes textos escritos entre 1941 e 1977: Razão e revolução (1941/1978, Eros e civilização (1955/1969, Ideologia da sociedade industrial: o homem unidimensional (1964/1973, Ideias sobre uma teoria crítica da sociedade (1969/1981 e A dimensão estética (1977/1999. Para Marcuse, a arte é política, apresenta universalidade, alteridade, transcendência, forma estética e negação e confirmação da realidade. A arte é objetivação e não trabalho alienado, ela realiza a sublimação e provoca sensibilidade, diferenciando-se da mercadoria que se apropria da cultura, fazendo-a esvaziar-se em seu sentido. Ao analisar a arte, esse autor contribuiu para uma psicologia social crítica que revela a arte como mediação psicossocial para um sujeito não adaptado.

Structural Dynamic Response Compressing Technique in Bridges using a Cochlea-inspired Artificial Filter Bank (CAFB)

International Nuclear Information System (INIS)

Heo, G; Jeon, J; Son, B; Kim, C; Jeon, S; Lee, C

2016-01-01

In this study, a cochlea-inspired artificial filter bank (CAFB) was developed to efficiently obtain dynamic response of a structure, and a dynamic response measurement of a cable-stayed bridge model was also carried out to evaluate the performance of the developed CAFB. The developed CAFB used a band-pass filter optimizing algorithm (BOA) and peakpicking algorithm (PPA) to select and compress dynamic response signal containing the modal information which was significant enough. The CAFB was then optimized about the El-Centro earthquake wave which was often used in the construction research, and the software implementation of CAFB was finally embedded in the unified structural management system (USMS). For the evaluation of the developed CAFB, a real time dynamic response experiment was performed on a cable-stayed bridge model, and the response of the cable-stayed bridge model was measured using both the traditional wired system and the developed CAFB-based USMS. The experiment results showed that the compressed dynamic response acquired by the CAFB-based USMS matched significantly with that of the traditional wired system while still carrying sufficient modal information of the cable-stayed bridge. (paper)

Effects of dynamic operating conditions on nitrification in biological rapid sand filters for drinking water treatment

DEFF Research Database (Denmark)

Lee, Carson Odell; Boe-Hansen, Rasmus; Musovic, Sanin

2014-01-01

Biological rapid sand filters are often used to remove ammonium from groundwater for drinking water supply. They often operate under dynamic substrate and hydraulic loading conditions, which can lead to increased levels of ammonium and nitrite in the effluent. To determine the maximum nitrification...... operating conditions. The ammonium removal rate of the filter was determined by the ammonium loading rate, but was independent of both the flow and influent ammonium concentration individually. Ammonia-oxidizing bacteria and archaea were almost equally abundant in the filter. Both ammonium removal...... rates and safe operating windows of rapid sand filters, a pilot scale rapid sand filter was used to test short-term increased ammonium loads, set by varying either influent ammonium concentrations or hydraulic loading rates. Ammonium and iron (flock) removal were consistent between the pilot...

Linear versus Nonlinear Filtering with Scale-Selective Corrections for Balanced Dynamics in a Simple Atmospheric Model

KAUST Repository

Subramanian, Aneesh C.

2012-11-01

This paper investigates the role of the linear analysis step of the ensemble Kalman filters (EnKF) in disrupting the balanced dynamics in a simple atmospheric model and compares it to a fully nonlinear particle-based filter (PF). The filters have a very similar forecast step but the analysis step of the PF solves the full Bayesian filtering problem while the EnKF analysis only applies to Gaussian distributions. The EnKF is compared to two flavors of the particle filter with different sampling strategies, the sequential importance resampling filter (SIRF) and the sequential kernel resampling filter (SKRF). The model admits a chaotic vortical mode coupled to a comparatively fast gravity wave mode. It can also be configured either to evolve on a so-called slow manifold, where the fast motion is suppressed, or such that the fast-varying variables are diagnosed from the slow-varying variables as slaved modes. Identical twin experiments show that EnKF and PF capture the variables on the slow manifold well as the dynamics is very stable. PFs, especially the SKRF, capture slaved modes better than the EnKF, implying that a full Bayesian analysis estimates the nonlinear model variables better. The PFs perform significantly better in the fully coupled nonlinear model where fast and slow variables modulate each other. This suggests that the analysis step in the PFs maintains the balance in both variables much better than the EnKF. It is also shown that increasing the ensemble size generally improves the performance of the PFs but has less impact on the EnKF after a sufficient number of members have been used.

Linear versus Nonlinear Filtering with Scale-Selective Corrections for Balanced Dynamics in a Simple Atmospheric Model

KAUST Repository

Subramanian, Aneesh C.; Hoteit, Ibrahim; Cornuelle, Bruce; Miller, Arthur J.; Song, Hajoon

2012-01-01

This paper investigates the role of the linear analysis step of the ensemble Kalman filters (EnKF) in disrupting the balanced dynamics in a simple atmospheric model and compares it to a fully nonlinear particle-based filter (PF). The filters have a very similar forecast step but the analysis step of the PF solves the full Bayesian filtering problem while the EnKF analysis only applies to Gaussian distributions. The EnKF is compared to two flavors of the particle filter with different sampling strategies, the sequential importance resampling filter (SIRF) and the sequential kernel resampling filter (SKRF). The model admits a chaotic vortical mode coupled to a comparatively fast gravity wave mode. It can also be configured either to evolve on a so-called slow manifold, where the fast motion is suppressed, or such that the fast-varying variables are diagnosed from the slow-varying variables as slaved modes. Identical twin experiments show that EnKF and PF capture the variables on the slow manifold well as the dynamics is very stable. PFs, especially the SKRF, capture slaved modes better than the EnKF, implying that a full Bayesian analysis estimates the nonlinear model variables better. The PFs perform significantly better in the fully coupled nonlinear model where fast and slow variables modulate each other. This suggests that the analysis step in the PFs maintains the balance in both variables much better than the EnKF. It is also shown that increasing the ensemble size generally improves the performance of the PFs but has less impact on the EnKF after a sufficient number of members have been used.

Coupling of unidimensional neutron kinetics to thermal hydraulics in parallel channels

International Nuclear Information System (INIS)

Cecenas F, M.; Campos G, R.M.

2003-01-01

In this work the dynamic behavior of a consistent system in fifteen channels in parallel that represent the reactor core of a BWR type, coupled of a kinetic neutronic model in one dimension is studied by means of time series. The arrangement of channels is obtained collapsing the assemblies that it consists the core to an arrangement of channels prepared in straight lines, and it is coupled to the unidimensional solution of the neutron diffusion equation. This solution represents the radial power distribution, and initially the static solution is obtained to verify that the one modeling core is critic. The coupled set nuclear-thermal hydraulics it is solved numerically by means of a net of CPUs working in the outline teacher-slave by means of Parallel Virtual Machine (PVM), subject to the restriction that the pressure drop is equal for each channel, which is executed iterating on the refrigerant distribution. The channels are dimensioned according to the one Stability Benchmark of the Ringhals swedish plant, organized by the Nuclear Energy Agency in 1994. From the information of this benchmark it is obtained the axial power profile for each channel, which is assumed as invariant in the time. To obtain the time series, the system gets excited with white noise (sequence that statistically obeys to a normal distribution with zero media), so that the power generated in each channel it possesses the same ones characteristics of a typical signal obtained by means of the acquisition of those signals of neutron flux in a BWR reactor. (Author)

daptive Filter Used as a Dynamic Compensator in Automatic Gauge Control of Strip Rolling Processes

Directory of Open Access Journals (Sweden)

N. ROMAN

2010-12-01

Full Text Available The paper deals with a control structure of the strip thickness in a rolling mill of quarto type (AGC – Automatic Gauge Control. It performs two functions: the compensation of errors induced by unideal dynamics of the tracking systems lead by AGC system and the control adaptation to the change of dynamic properties of the tracking systems. The compensation of dynamical errors is achieved through inverse models of the tracking system, implemented as adaptive filters.

Differential Neural Networks for Identification and Filtering in Nonlinear Dynamic Games

Directory of Open Access Journals (Sweden)

Emmanuel García

2014-01-01

Full Text Available This paper deals with the problem of identifying and filtering a class of continuous-time nonlinear dynamic games (nonlinear differential games subject to additive and undesired deterministic perturbations. Moreover, the mathematical model of this class is completely unknown with the exception of the control actions of each player, and even though the deterministic noises are known, their power (or their effect is not. Therefore, two differential neural networks are designed in order to obtain a feedback (perfect state information pattern for the mentioned class of games. In this way, the stability conditions for two state identification errors and for a filtering error are established, the upper bounds of these errors are obtained, and two new learning laws for each neural network are suggested. Finally, an illustrating example shows the applicability of this approach.

Estimation of the Dynamic States of Synchronous Machines Using an Extended Particle Filter

Energy Technology Data Exchange (ETDEWEB)

Zhou, Ning; Meng, Da; Lu, Shuai

2013-11-11

In this paper, an extended particle filter (PF) is proposed to estimate the dynamic states of a synchronous machine using phasor measurement unit (PMU) data. A PF propagates the mean and covariance of states via Monte Carlo simulation, is easy to implement, and can be directly applied to a non-linear system with non-Gaussian noise. The extended PF modifies a basic PF to improve robustness. Using Monte Carlo simulations with practical noise and model uncertainty considerations, the extended PF’s performance is evaluated and compared with the basic PF and an extended Kalman filter (EKF). The extended PF results showed high accuracy and robustness against measurement and model noise.

Lattice Boltzmann simulations for wall-flow dynamics in porous ceramic diesel particulate filters

Science.gov (United States)

Lee, Da Young; Lee, Gi Wook; Yoon, Kyu; Chun, Byoungjin; Jung, Hyun Wook

2018-01-01

Flows through porous filter walls of wall-flow diesel particulate filter are investigated using the lattice Boltzmann method (LBM). The microscopic model of the realistic filter wall is represented by randomly overlapped arrays of solid spheres. The LB simulation results are first validated by comparison to those from previous hydrodynamic theories and constitutive models for flows in porous media with simple regular and random solid-wall configurations. We demonstrate that the newly designed randomly overlapped array structures of porous walls allow reliable and accurate simulations for the porous wall-flow dynamics in a wide range of solid volume fractions from 0.01 to about 0.8, which is beyond the maximum random packing limit of 0.625. The permeable performance of porous media is scrutinized by changing the solid volume fraction and particle Reynolds number using Darcy's law and Forchheimer's extension in the laminar flow region.

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

Science.gov (United States)

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

Correction of the dynamic response of the ''Gamma thermometers'' using a digital filter

International Nuclear Information System (INIS)

Jacquot, J.P.; Lobert, J.P.

1985-01-01

The ''gamma thermometer'' is a sensor used to measure on line the local power inside a PWR nuclear reactor. During transients, this sensor based on thermal exchanges, obes not give a fast response. This paper describes a microprocessor device that allows using a digital filtering technique, a correction of the dynamic response [fr

Brief, unidimensional melancholia rating scales are highly sensitive to the effect of citalopram and may have biological validity

DEFF Research Database (Denmark)

Østergaard, Søren Dinesen; Bech, Per; Trivedi, Madhukar H

2014-01-01

-item Inventory of Depressive Symptomatology (IDS-C30) to that of their unidimensional six-item melancholia subscales (HAM-D6 and IDS-C6). METHODS: A total of 2242 subjects from level 1 (citalopram) of the Sequenced Treatment Alternatives to Relieve Depression (STAR* study were included in the analysis...

Large eddy simulations of round free jets using explicit filtering with/without dynamic Smagorinsky model

International Nuclear Information System (INIS)

Bogey, Christophe; Bailly, Christophe

2006-01-01

Large eddy simulations (LES) of round free jets at Mach number M = 0.9 with Reynolds numbers over the range 2.5 x 10 3 ≤ Re D ≤ 4 x 10 5 are performed using explicit selective/high-order filtering with or without dynamic Smagorinsky model (DSM). Features of the flows and of the turbulent kinetic energy budgets in the turbulent jets are reported. The contributions of molecular viscosity, filtering and DSM to energy dissipation are also presented. Using filtering alone, the results are independent of the filtering strength, and the effects of the Reynolds number on jet development are successfully calculated. Using DSM, the effective jet Reynolds number is found to be artificially decreased by the eddy viscosity. The results are also not appreciably modified when subgrid-scale kinetic energy is used. Moreover, unlike filtering which does not significantly affect the larger computed scales, the eddy viscosity is shown to dissipate energy through all the turbulent scales, in the same way as molecular viscosity at lower Reynolds numbers

The 3-D alignment of objects in dynamic PET scans using filtered sinusoidal trajectories of sinogram

International Nuclear Information System (INIS)

Kostopoulos, Aristotelis E.; Happonen, Antti P.; Ruotsalainen, Ulla

2006-01-01

In this study, our goal is to employ a novel 3-D alignment method for dynamic positron emission tomography (PET) scans. Because the acquired data (i.e. sinograms) often contain noise considerably, filtering of the data prior to the alignment presumably improves the final results. In this study, we utilized a novel 3-D stackgram domain approach. In the stackgram domain, the signals along the sinusoidal trajectory signals of the sinogram can be processed separately. In this work, we performed angular stackgram domain filtering by employing well known 1-D filters: the Gaussian low-pass filter and the median filter. In addition, we employed two wavelet de-noising techniques. After filtering we performed alignment of objects in the stackgram domain. The local alignment technique we used is based on similarity comparisons between locus vectors (i.e. the signals along the sinusoidal trajectories of the sinogram) in a 3-D neighborhood of sequences of the stackgrams. Aligned stackgrams can be transformed back to sinograms (Method 1), or alternatively directly to filtered back-projected images (Method 2). In order to evaluate the alignment process, simulated data with different kinds of additive noises were used. The results indicated that the filtering prior to the alignment can be important concerning the accuracy

Investigation, development, and application of optimal output feedback theory. Volume 3: The relationship between dynamic compensators and observers and Kalman filters

Science.gov (United States)

Broussard, John R.

1987-01-01

Relationships between observers, Kalman Filters and dynamic compensators using feedforward control theory are investigated. In particular, the relationship, if any, between the dynamic compensator state and linear functions of a discrete plane state are investigated. It is shown that, in steady state, a dynamic compensator driven by the plant output can be expressed as the sum of two terms. The first term is a linear combination of the plant state. The second term depends on plant and measurement noise, and the plant control. Thus, the state of the dynamic compensator can be expressed as an estimator of the first term with additive error given by the second term. Conditions under which a dynamic compensator is a Kalman filter are presented, and reduced-order optimal estimaters are investigated.

Dynamic bowtie filter for cone-beam/multi-slice CT.

Directory of Open Access Journals (Sweden)

Fenglin Liu

Full Text Available A pre-patient attenuator ("bowtie filter" or "bowtie" is used to modulate an incoming x-ray beam as a function of the angle of the x-ray with respect to a patient to balance the photon flux on a detector array. While the current dynamic bowtie design is focused on fan-beam geometry, in this study we propose a methodology for dynamic bowtie design in multi-slice/cone-beam geometry. The proposed 3D dynamic bowtie is an extension of the 2D prior art. The 3D bowtie consists of a highly attenuating bowtie (HB filled in with heavy liquid and a weakly attenuating bowtie (WB immersed in the liquid of the HB. The HB targets a balanced flux distribution on a detector array when no object is in the field of view (FOV. The WB compensates for an object in the FOV, and hence is a scaled-down version of the object. The WB is rotated and translated in synchrony with the source rotation and patient translation so that the overall flux balance is maintained on the detector array. First, the mathematical models of different scanning modes are established for an elliptical water phantom. Then, a numerical simulation study is performed to compare the performance of the scanning modes in the cases of the water phantom and a patient cross-section without any bowtie and with a dynamic bowtie. The dynamic bowtie can equalize the numbers of detected photons in the case of the water phantom. In practical cases, the dynamic bowtie can effectively reduce the dynamic range of detected signals inside the FOV. Furthermore, the WB can be individualized using a 3D printing technique as the gold standard. We have extended the dynamic bowtie concept from 2D to 3D by using highly attenuating liquid and moving a scale-reduced negative copy of an object being scanned. Our methodology can be applied to reduce radiation dose and facilitate photon-counting detection.

Tracking single dynamic MEG dipole sources using the projected Extended Kalman Filter.

Science.gov (United States)

Yao, Yuchen; Swindlehurst, A Lee

2011-01-01

This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

The extended Kalman filter for forecast of algal bloom dynamics.

Science.gov (United States)

Mao, J Q; Lee, Joseph H W; Choi, K W

2009-09-01

A deterministic ecosystem model is combined with an extended Kalman filter (EKF) to produce short term forecasts of algal bloom and dissolved oxygen dynamics in a marine fish culture zone (FCZ). The weakly flushed FCZ is modelled as a well-mixed system; the tidal exchange with the outer bay is lumped into a flushing rate that is numerically determined from a three-dimensional hydrodynamic model. The ecosystem model incorporates phytoplankton growth kinetics, nutrient uptake, photosynthetic production, nutrient sources from organic fish farm loads, and nutrient exchange with a sediment bed layer. High frequency field observations of chlorophyll, dissolved oxygen (DO) and hydro-meteorological parameters (sampling interval Deltat=1 day, 2h, 1h, respectively) and bi-weekly nutrient data are assimilated into the model to produce the combined state estimate accounting for the uncertainties. In addition to the water quality state variables, the EKF incorporates dynamic estimation of algal growth rate and settling velocity. The effectiveness of the EKF data assimilation is studied for a wide range of sampling intervals and prediction lead-times. The chlorophyll and dissolved oxygen estimated by the EKF are compared with field data of seven algal bloom events observed at Lamma Island, Hong Kong. The results show that the EKF estimate well captures the nonlinear error evolution in time; the chlorophyll level can be satisfactorily predicted by the filtered model estimate with a mean absolute error of around 1-2 microg/L. Predictions with 1-2 day lead-time are highly correlated with the observations (r=0.7-0.9); the correlation stays at a high level for a lead-time of 3 days (r=0.6-0.7). Estimated algal growth and settling rates are in accord with field observations; the more frequent DO data can compensate for less frequent algal biomass measurements. The present study is the first time the EKF is successfully applied to forecast an entire algal bloom cycle, suggesting the

A dynamic particle filter-support vector regression method for reliability prediction

International Nuclear Information System (INIS)

Wei, Zhao; Tao, Tao; ZhuoShu, Ding; Zio, Enrico

2013-01-01

Support vector regression (SVR) has been applied to time series prediction and some works have demonstrated the feasibility of its use to forecast system reliability. For accuracy of reliability forecasting, the selection of SVR's parameters is important. The existing research works on SVR's parameters selection divide the example dataset into training and test subsets, and tune the parameters on the training data. However, these fixed parameters can lead to poor prediction capabilities if the data of the test subset differ significantly from those of training. Differently, the novel method proposed in this paper uses particle filtering to estimate the SVR model parameters according to the whole measurement sequence up to the last observation instance. By treating the SVR training model as the observation equation of a particle filter, our method allows updating the SVR model parameters dynamically when a new observation comes. Because of the adaptability of the parameters to dynamic data pattern, the new PF–SVR method has superior prediction performance over that of standard SVR. Four application results show that PF–SVR is more robust than SVR to the decrease of the number of training data and the change of initial SVR parameter values. Also, even if there are trends in the test data different from those in the training data, the method can capture the changes, correct the SVR parameters and obtain good predictions. -- Highlights: •A dynamic PF–SVR method is proposed to predict the system reliability. •The method can adjust the SVR parameters according to the change of data. •The method is robust to the size of training data and initial parameter values. •Some cases based on both artificial and real data are studied. •PF–SVR shows superior prediction performance over standard SVR

Increasing dynamic range of a fibre Bragg grating edge-filtering interrogator with a proportional control loop

International Nuclear Information System (INIS)

Stan, Nikola; Bailey, D C; Chadderdon, S L; Selfridge, R H; Schultz, S M; Webb, S; Zikry, M; Peters, K J

2014-01-01

We present a fibre Bragg grating (FBG) interrogator that uses a microcontroller board and a tunable optical filter in a proportional control loop to increase dynamic range and achieve high strain sensitivity. It is an edge-filtering interrogator with added proportional control loop that locks the operating wavelength to the mid-reflection point on the FBG spectrum. The interrogator separates low-frequency (LF) components of strain and measures them with extended dynamic range, while at the same time measuring high-frequency (HF) strain without loss in strain sensitivity. In this paper, we describe the implementation of the interrogator and analyse the characteristics of individual components, such as the speed and voltage resolution of the microcontroller and the tunable optical filter. We measure the performance of the proportional control loop at frequencies up to 1 kHz and characterize the system using control theory. We illustrate the limitation of the conventional interrogator to measure strains greater than 40 μϵ and demonstrate successful application of the proposed interrogator for simultaneous measurement of 450 μϵ LF strain at 50 Hz superimposed with 32 kHz HF strain. (paper)

Comparing Consider-Covariance Analysis with Sigma-Point Consider Filter and Linear-Theory Consider Filter Formulations

Science.gov (United States)

Lisano, Michael E.

2007-01-01

Recent literature in applied estimation theory reflects growing interest in the sigma-point (also called unscented ) formulation for optimal sequential state estimation, often describing performance comparisons with extended Kalman filters as applied to specific dynamical problems [c.f. 1, 2, 3]. Favorable attributes of sigma-point filters are described as including a lower expected error for nonlinear even non-differentiable dynamical systems, and a straightforward formulation not requiring derivation or implementation of any partial derivative Jacobian matrices. These attributes are particularly attractive, e.g. in terms of enabling simplified code architecture and streamlined testing, in the formulation of estimators for nonlinear spaceflight mechanics systems, such as filter software onboard deep-space robotic spacecraft. As presented in [4], the Sigma-Point Consider Filter (SPCF) algorithm extends the sigma-point filter algorithm to the problem of consider covariance analysis. Considering parameters in a dynamical system, while estimating its state, provides an upper bound on the estimated state covariance, which is viewed as a conservative approach to designing estimators for problems of general guidance, navigation and control. This is because, whether a parameter in the system model is observable or not, error in the knowledge of the value of a non-estimated parameter will increase the actual uncertainty of the estimated state of the system beyond the level formally indicated by the covariance of an estimator that neglects errors or uncertainty in that parameter. The equations for SPCF covariance evolution are obtained in a fashion similar to the derivation approach taken with standard (i.e. linearized or extended) consider parameterized Kalman filters (c.f. [5]). While in [4] the SPCF and linear-theory consider filter (LTCF) were applied to an illustrative linear dynamics/linear measurement problem, in the present work examines the SPCF as applied to

Spin filtering neutrons with a proton target dynamically polarized using photo-excited triplet states

International Nuclear Information System (INIS)

Haag, M.; Brandt, B. van den; Eichhorn, T.R.; Hautle, P.; Wenckebach, W.Th.

2012-01-01

In a test of principle a neutron spin filter has been built, which is based on dynamic nuclear polarization (DNP) using photo-excited triplet states. This DNP method has advantages over classical concepts as the requirements for cryogenic equipment and magnets are much relaxed: the spin filter is operated in a field of 0.3 T at a temperature of about 100 K and has performed reliably over periods of several weeks. The neutron beam was also used to analyze the polarization of the target employed as a spin filter. We obtained an independent measurement of the proton spin polarization of ∼0.13 in good agreement with the value determined with NMR. Moreover, the neutron beam was used to measure the proton spin polarization as a function of position in the naphthalene sample. The polarization was found to be homogeneous, even at low laser power, in contradiction to existing models describing the photo-excitation process.

Complementary filter implementation in the dynamic language Lua

Science.gov (United States)

Sadowski, Damian; Sawicki, Aleksander; Lukšys, Donatas; Slanina, Zdenek

2017-08-01

The article presents the complementary filter implementation, that is used for the estimation of the pitch angle, in Lua script language. Inertial sensors as accelerometer and gyroscope were used in the study. Methods of angles estimation using acceleration and angular velocity sensors were presented in the theoretical part of the article. The operating principle of complementary filter has been presented. The prototype of Butterworth's analogue filter and its digital equivalent have been designed. Practical implementation of the issue was performed with the use of PC and DISCOVERY evaluation board equipped with STM32F01 processor, L3GD20 gyroscope and LS303DLHC accelerometer. Measurement data was transmitted by UART serial interface, then processed with the use of Lua software and luaRS232 programming library. Practical implementation was divided into two stages. In the first part, measurement data has been recorded and then processed with help of a complementary filter. In the second step, coroutines mechanism was used to filter data in real time.

Dynamic State Estimation for Multi-Machine Power System by Unscented Kalman Filter With Enhanced Numerical Stability

Energy Technology Data Exchange (ETDEWEB)

Qi, Junjian; Sun, Kai; Wang, Jianhui; Liu, Hui

2018-03-01

In this paper, in order to enhance the numerical stability of the unscented Kalman filter (UKF) used for power system dynamic state estimation, a new UKF with guaranteed positive semidifinite estimation error covariance (UKFGPS) is proposed and compared with five existing approaches, including UKFschol, UKF-kappa, UKFmodified, UKF-Delta Q, and the squareroot UKF (SRUKF). These methods and the extended Kalman filter (EKF) are tested by performing dynamic state estimation on WSCC 3-machine 9-bus system and NPCC 48-machine 140-bus system. For WSCC system, all methods obtain good estimates. However, for NPCC system, both EKF and the classic UKF fail. It is found that UKFschol, UKF-kappa, and UKF-Delta Q do not work well in some estimations while UKFGPS works well in most cases. UKFmodified and SRUKF can always work well, indicating their better scalability mainly due to the enhanced numerical stability.

Parâmetros ecocardiográficos em modo unidimensional de cães da raça Poodle miniatura, clinicamente sadios Echocardiographic parameters in unidimensional mode from clinically normal miniature Poodle dogs

OpenAIRE

Ronaldo Jun Yamato; Maria Helena Matiko Akao Larsson; Regina Mieko Sakata Mirandola; Guilherme Gonçalves Pereira; Fernanda Lie Yamaki; Ana Carolina Brandão de Campos Fonseca Pinto; Elina Célia Nakandakari

2006-01-01

No Brasil, a população canina da raça Poodle, principalmente a variação miniatura, cresce em progressão geométrica, sendo esta raça freqüentemente acometida por cardiopatias congênitas e adquiridas. O escopo deste estudo foi padronizar e avaliar os parâmetros ecocardiográficos em modo unidimensional (M) de cães da raça Poodle miniatura, devido ao aumento populacional da mesma, a variação existente destes parâmetros entre as raças caninas e as diversas cardiopatias às quais os Poodles são pred...

Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics.

Science.gov (United States)

Madi, Mahmoud K; Karameh, Fadi N

2017-01-01

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate

Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics

Science.gov (United States)

2017-01-01

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate

Auditory filters at low-frequencies

DEFF Research Database (Denmark)

Orellana, Carlos Andrés Jurado; Pedersen, Christian Sejer; Møller, Henrik

2009-01-01

-ear transfer function), the asymmetry of the auditory filter changed from steeper high-frequency slopes at 1000 Hz to steeper low-frequency slopes below 100 Hz. Increasing steepness at low-frequencies of the middle-ear high-pass filter is thought to cause this effect. The dynamic range of the auditory filter...... was found to steadily decrease with decreasing center frequency. Although the observed decrease in filter bandwidth with decreasing center frequency was only approximately monotonic, the preliminary data indicates the filter bandwidth does not stabilize around 100 Hz, e.g. it still decreases below...

BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems.

Science.gov (United States)

Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M

2017-11-25

Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression

Experimental study of filter cake formation on different filter media

International Nuclear Information System (INIS)

Saleem, M.

2009-01-01

Removal of particulate matter from gases generated in the process industry is important for product recovery as well as emission control. Dynamics of filtration plant depend on operating conditions. The models, that predict filter plant behaviour, involve empirical resistance parameters which are usually derived from limited experimental data and are characteristics of the filter media and filter cake (dust deposited on filter medium). Filter cake characteristics are affected by the nature of filter media, process parameters and mode of filter regeneration. Removal of dust particles from air is studied in a pilot scale jet pulsed bag filter facility resembling closely to the industrial filters. Limestone dust and ambient air are used in this study with two widely different filter media. All important parameters like pressure drop, gas flow rate, dust settling, are recorded continuously at 1s interval. The data is processed for estimation of the resistance parameters. The pressure drop rise on test filter media is compared. Results reveal that the surface of filter media has an influence on pressure drop rise (concave pressure drop rise). Similar effect is produced by partially jet pulsed filter surface. Filter behaviour is also simulated using estimated parameters and a simplified model and compared with the experimental results. Distribution of cake area load is therefore an important aspect of jet pulse cleaned bag filter modeling. Mean specific cake resistance remains nearly constant on thoroughly jet pulse cleaned membrane coated filter bags. However, the trend can not be confirmed without independent cake height and density measurements. Thus the results reveal the importance of independent measurements of cake resistance. (author)

The effect of heterogeneous dynamics of online users on information filtering

International Nuclear Information System (INIS)

Chen, Bo-Lun; Zeng, An; Chen, Ling

2015-01-01

The rapid expansion of the Internet requires effective information filtering techniques to extract the most essential and relevant information for online users. Many recommendation algorithms have been proposed to predict the future items that a given user might be interested in. However, there is an important issue that has always been ignored so far in related works, namely the heterogeneous dynamics of online users. The interest of active users changes more often than that of less active users, which asks for different update frequency of their recommendation lists. In this paper, we develop a framework to study the effect of heterogeneous dynamics of users on the recommendation performance. We find that the personalized application of recommendation algorithms results in remarkable improvement in the recommendation accuracy and diversity. Our findings may help online retailers make better use of the existing recommendation methods. - Highlights: • We study the effect of heterogeneous dynamics of users on recommendation. • Due to the user heterogeneity, their amount of links in the probe set is different. • The personalized algorithm implementation improves the recommendation performance. • Our results suggest different update frequency for users – recommendation list.

The effect of heterogeneous dynamics of online users on information filtering

Energy Technology Data Exchange (ETDEWEB)

Chen, Bo-Lun [Department of Computer Science, Yangzhou University of China, Yangzhou 225127 (China); Department of Computer Science, Nanjing University of Aeronautics and Astronautics of China, Nanjing 210016 (China); Department of Physics, University of Fribourg, Chemin du Musee 3, CH-1700 Fribourg (Switzerland); Zeng, An, E-mail: anzeng@bnu.edu.cn [School of Systems Science, Beijing Normal University, Beijing 100875 (China); Chen, Ling [Department of Computer Science, Yangzhou University of China, Yangzhou 225127 (China); Department of Computer Science, Nanjing University of Aeronautics and Astronautics of China, Nanjing 210016 (China)

2015-11-06

The rapid expansion of the Internet requires effective information filtering techniques to extract the most essential and relevant information for online users. Many recommendation algorithms have been proposed to predict the future items that a given user might be interested in. However, there is an important issue that has always been ignored so far in related works, namely the heterogeneous dynamics of online users. The interest of active users changes more often than that of less active users, which asks for different update frequency of their recommendation lists. In this paper, we develop a framework to study the effect of heterogeneous dynamics of users on the recommendation performance. We find that the personalized application of recommendation algorithms results in remarkable improvement in the recommendation accuracy and diversity. Our findings may help online retailers make better use of the existing recommendation methods. - Highlights: • We study the effect of heterogeneous dynamics of users on recommendation. • Due to the user heterogeneity, their amount of links in the probe set is different. • The personalized algorithm implementation improves the recommendation performance. • Our results suggest different update frequency for users – recommendation list.

Extended-life nuclear air cleaning filters via dynamic exclusion prefilters

Energy Technology Data Exchange (ETDEWEB)

Wright, S.R.; Crouch, H.S.; Bond, J.H. [Micro Composite Materials Corp., Durham, NC (United States)

1997-08-01

The primary objective of this investigation was to ascertain if a dynamic, self-cleaning particulate exclusion precleaner, designed for relatively large dust removal (2 to 100+ {mu}m diameter particles) from helicopter turbine inlets, could be extended to submicron filtration. The improved device could be used as a prefilter for HEPA filtration systems, significantly increasing service life. In nuclear air cleaning, its use would reduce the amount of nuclear particulate matter that would otherwise be entrapped in the HEPA filter cartridge/panel, causing fouling and increased back pressure, as well as requiring subsequent disposal of the contaminated media at considerable expense. A unique (patent-pending) mechanical separation device has recently been developed to extract particulate matter from fluid process streams based on a proprietary concept called Boundary Layer Momentum Transfer (BLMT). The device creates multiple boundary layers that actively exclude particles from entering the perimeter of the device, while allowing air to traverse the boundaries relatively unimpeded. A modified two-dimensional (2-D) computerized flow simulation model was used to assist in the prototype design. Empirical results are presented from particle breakthrough and AP experiments obtained from a reduced-scale prototype filter. Particles larger than 0.23 {mu}m were actively excluded by the prototype, but at a higher pressure drop than anticipated. Experimental data collected indicates that the filter housing and the inlet flow configuration may contribute significantly to improvements in device particle separation capabilities. Furthermore, preliminary experiments have shown that other downstream pressure drop considerations (besides those just across the spinning filtration disks) must be included to accurately portray the AP across the device. Further detailed quantitative investigations on a larger scale (1,000 CFM) prototype are warranted. 3 refs., 5 figs., 2 tabs.

A comparative study between a simplified Kalman filter and Sliding Window Averaging for single trial dynamical estimation of event-related potentials

DEFF Research Database (Denmark)

Vedel-Larsen, Esben; Fuglø, Jacob; Channir, Fouad

2010-01-01

, are variable and depend on cognitive function. This study compares the performance of a simplified Kalman filter with Sliding Window Averaging in tracking dynamical changes in single trial P300. The comparison is performed on simulated P300 data with added background noise consisting of both simulated and real...... background EEG in various input signal to noise ratios. While both methods can be applied to track dynamical changes, the simplified Kalman filter has an advantage over the Sliding Window Averaging, most notable in a better noise suppression when both are optimized for faster changing latency and amplitude...

Retina-Inspired Filter.

Science.gov (United States)

Doutsi, Effrosyni; Fillatre, Lionel; Antonini, Marc; Gaulmin, Julien

2018-07-01

This paper introduces a novel filter, which is inspired by the human retina. The human retina consists of three different layers: the Outer Plexiform Layer (OPL), the inner plexiform layer, and the ganglionic layer. Our inspiration is the linear transform which takes place in the OPL and has been mathematically described by the neuroscientific model "virtual retina." This model is the cornerstone to derive the non-separable spatio-temporal OPL retina-inspired filter, briefly renamed retina-inspired filter, studied in this paper. This filter is connected to the dynamic behavior of the retina, which enables the retina to increase the sharpness of the visual stimulus during filtering before its transmission to the brain. We establish that this retina-inspired transform forms a group of spatio-temporal Weighted Difference of Gaussian (WDoG) filters when it is applied to a still image visible for a given time. We analyze the spatial frequency bandwidth of the retina-inspired filter with respect to time. It is shown that the WDoG spectrum varies from a lowpass filter to a bandpass filter. Therefore, while time increases, the retina-inspired filter enables to extract different kinds of information from the input image. Finally, we discuss the benefits of using the retina-inspired filter in image processing applications such as edge detection and compression.

Speckle and fringe dynamics in imagingspeckle-pattern interferometry for spatial-filtering velocimetry

DEFF Research Database (Denmark)

Jakobsen, Michael Linde; Iversen, Theis F. Q.; Yura, Harold T.

2011-01-01

This paper analyzes the dynamics of laser speckles and fringes, formed in an imaging-speckle-pattern interferometer with the purpose of sensing linear three-dimensional motion and out-of-plane components of rotation in real time, using optical spatial-filtering-velocimetry techniques. The ensemble......-average definition of the cross-correlation function is applied to the intensity distributions, obtained in the observation plane at two positions of the object. The theoretical analysis provides a description for the dynamics of both the speckles and the fringes. The analysis reveals that both the magnitude...... and direction of all three linear displacement components of the object movement can be determined. Simultaneously, out-ofplane rotation of the object including the corresponding directions can be determined from the spatial gradient of the in-plane fringe motion throughout the observation plane. The theory...

Numerical study of canister filters with alternatives filter cap configurations

Science.gov (United States)

Mohammed, A. N.; Daud, A. R.; Abdullah, K.; Seri, S. M.; Razali, M. A.; Hushim, M. F.; Khalid, A.

2017-09-01

Air filtration system and filter play an important role in getting a good quality air into turbo machinery such as gas turbine. The filtration system and filter has improved the quality of air and protect the gas turbine part from contaminants which could bring damage. During separation of contaminants from the air, pressure drop cannot be avoided but it can be minimized thus helps to reduce the intake losses of the engine [1]. This study is focused on the configuration of the filter in order to obtain the minimal pressure drop along the filter. The configuration used is the basic filter geometry provided by Salutary Avenue Manufacturing Sdn Bhd. and two modified canister filter cap which is designed based on the basic filter model. The geometries of the filter are generated by using SOLIDWORKS software and Computational Fluid Dynamics (CFD) software is used to analyse and simulates the flow through the filter. In this study, the parameters of the inlet velocity are 0.032 m/s, 0.063 m/s, 0.094 m/s and 0.126 m/s. The total pressure drop produce by basic, modified filter 1 and 2 is 292.3 Pa, 251.11 Pa and 274.7 Pa. The pressure drop reduction for the modified filter 1 is 41.19 Pa and 14.1% lower compared to basic filter and the pressure drop reduction for modified filter 2 is 17.6 Pa and 6.02% lower compared to the basic filter. The pressure drops for the basic filter are slightly different with the Salutary Avenue filter due to limited data and experiment details. CFD software are very reliable in running a simulation rather than produces the prototypes and conduct the experiment thus reducing overall time and cost in this study.

Particle Kalman Filtering: A Nonlinear Framework for Ensemble Kalman Filters

KAUST Repository

Hoteit, Ibrahim

2010-09-19

Optimal nonlinear filtering consists of sequentially determining the conditional probability distribution functions (pdf) of the system state, given the information of the dynamical and measurement processes and the previous measurements. Once the pdfs are obtained, one can determine different estimates, for instance, the minimum variance estimate, or the maximum a posteriori estimate, of the system state. It can be shown that, many filters, including the Kalman filter (KF) and the particle filter (PF), can be derived based on this sequential Bayesian estimation framework. In this contribution, we present a Gaussian mixture‐based framework, called the particle Kalman filter (PKF), and discuss how the different EnKF methods can be derived as simplified variants of the PKF. We also discuss approaches to reducing the computational burden of the PKF in order to make it suitable for complex geosciences applications. We use the strongly nonlinear Lorenz‐96 model to illustrate the performance of the PKF.

Risk Sensitive Filtering with Poisson Process Observations

International Nuclear Information System (INIS)

Malcolm, W. P.; James, M. R.; Elliott, R. J.

2000-01-01

In this paper we consider risk sensitive filtering for Poisson process observations. Risk sensitive filtering is a type of robust filtering which offers performance benefits in the presence of uncertainties. We derive a risk sensitive filter for a stochastic system where the signal variable has dynamics described by a diffusion equation and determines the rate function for an observation process. The filtering equations are stochastic integral equations. Computer simulations are presented to demonstrate the performance gain for the risk sensitive filter compared with the risk neutral filter

Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter

KAUST Repository

Ryu, Duchwan

2013-03-01

The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle filter to estimate the parameters of the dynamic model. We analyze the SST observed in the Caribbean Islands area after a hurricane using the proposed dynamic model. Comparing to the traditional grid-based approach that requires a supercomputer due to its high computational demand, our approach requires much less CPU time and makes real-time forecasting of SST doable on a personal computer. Supplementary materials for this article are available online. © 2013 American Statistical Association.

Adaptive filtering prediction and control

CERN Document Server

Goodwin, Graham C

2009-01-01

Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

Enhanced Microgrid Dynamic Performance Using a Modulated Power Filter Based on Enhanced Bacterial Foraging Optimization

Directory of Open Access Journals (Sweden)

Ahmed M. Othman

2017-06-01

Full Text Available This paper presents a design of microgrid (MG with enhanced dynamic performance. Distributed energy resources (DER are widely used in MGs to match the various load types and profiles. DERs include solar PV cells, wind energy sources, fuel cells, batteries, micro gas-engines and storage elements. MG will include AC/DC circuits, developed power electronics devices, inverters and power electronic controllers. A novel modulated power filters (MPF device will be applied in MG design. Enhanced bacterial foraging optimization (EBFO will be proposed to optimize and set the MPF parameters to enhance and tune the MG dynamic response. Recent dynamic control is applied to minimize the harmonic reference content. EBFO will adapt the gains of MPF dynamic control. The present research achieves an enhancement of MG dynamic performance, in addition to ensuring improvements in the power factor, bus voltage profile and power quality. MG operation will be evaluated by the dynamic response to be fine-tuned by MPF based on EBFO. Digital simulations have validated the results to show the effectiveness and efficient improvement by the proposed strategy.

The second order extended Kalman filter and Markov nonlinear filter for data processing in interferometric systems

International Nuclear Information System (INIS)

Ermolaev, P; Volynsky, M

2014-01-01

Recurrent stochastic data processing algorithms using representation of interferometric signal as output of a dynamic system, which state is described by vector of parameters, in some cases are more effective, compared with conventional algorithms. Interferometric signals depend on phase nonlinearly. Consequently it is expedient to apply algorithms of nonlinear stochastic filtering, such as Kalman type filters. An application of the second order extended Kalman filter and Markov nonlinear filter that allows to minimize estimation error is described. Experimental results of signals processing are illustrated. Comparison of the algorithms is presented and discussed.

Spatial filtering velocimetry for real-time out-of-plane displacement measurements

DEFF Research Database (Denmark)

Olesen, Anders Sig; Yura, H.T.; Jakobsen, Michael Linde

2016-01-01

power spectrum of the photocurrent produced by this filter. This main contribution of this paper is a model, which describe the selectivity of the sensor, applied to speckle dynamics generated by an object moving out-of-plane. To motivate our interest in these filters we also present an all optical......We probe the dynamics of objective laser speckles as the axial distance between the object and the observation plane changes. With the purpose of measuring out-of-plane motion in real time, we apply optical spatial filtering velocimetry to the speckle dynamics. To achieve this, a rotationally...... symmetric spatial filter is designed. The spatial filter converts the speckle dynamics into a photocurrent with a quasi-sinusoidal response to the out-of-plane motion. The selectivity of the sensor relates directly to the uncertainty on sensor measurements. The selectivity most be derived from a temporal...

Spatial filtering velocimetry of objective speckles for measuring out-of-plane motion

DEFF Research Database (Denmark)

Jakobsen, Michael Linde; Yura, H. T.; Hanson, Steen Grüner

2012-01-01

This paper analyzes the dynamics of objective laser speckles as the distance between the object and the observation plane continuously changes. With the purpose of applying optical spatial filtering velocimetry to the speckle dynamics, in order to measure out-of-plane motion in real time......, a rotational symmetric spatial filter is designed. The spatial filter converts the speckle dynamics into a photocurrent with a quasi-sinusoidal response to the out-of-plane motion. The spatial filter is here emulated with a CCD camera, and is tested on speckles arising from a real application. The analysis...

Hydrodynamics of microbial filter feeding

DEFF Research Database (Denmark)

Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia

2017-01-01

Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate......-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude......; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet...

Filtering in hybrid dynamic Bayesian networks

DEFF Research Database (Denmark)

Andersen, Morten Nonboe; Andersen, Rasmus Ørum; Wheeler, Kevin

2004-01-01

for inference. We extend the experiment and perform approximate inference using The Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Furthermore, we combine these techniques in a 'non-strict' Rao-Blackwellisation framework and apply it to the watertank system. We show that UKF and UKF in a PF...... framework outperform the generic PF, EKF and EKF in a PF framework with respect to accuracy and robustness in terms of estimation RMSE (root-mean-square error). Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. We also show...... that the choice of network structure is very important for the performance of the generic PF and the EKF algorithms, but not for the UKF algorithms. Furthermore, we investigate the influence of data noise in the watertank simulation. Theory and implementation is based on the theory presented in (v.d. Merwe et al...

Bowtie filters for dedicated breast CT: Analysis of bowtie filter material selection

Energy Technology Data Exchange (ETDEWEB)

Kontson, Kimberly, E-mail: Kimberly.Kontson@fda.hhs.gov; Jennings, Robert J. [Department of Bioengineering, University of Maryland, College Park, Maryland 20742 and Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993 (United States)

2015-09-15

, and scatter were investigated. Results: Analytical calculations with and without each bowtie filter show that some materials for a given design produce bowtie filters that are too large for implementation in breast CT scanners or too small to accurately manufacture. Results also demonstrate the ability to manipulate the energy fluence distribution (dynamic range) by using different materials, or different combinations of materials, for a given bowtie filter design. This feature is especially advantageous when using photon counting detector technology. Monte Carlo simulation results from PENELOPE show that all studied material choices for bowtie design #2 achieve nearly uniform dose distribution, noise uniformity index less than 5%, and nearly uniform scatter-to-primary ratio. These same features can also be obtained using certain materials with bowtie designs #1 and #3. Conclusions: With the three bowtie filter designs used in this work, the selection of material is an important design consideration. An appropriate material choice can improve image quality, dose uniformity, and dynamic range.

Bowtie filters for dedicated breast CT: Analysis of bowtie filter material selection

International Nuclear Information System (INIS)

Kontson, Kimberly; Jennings, Robert J.

2015-01-01

, and scatter were investigated. Results: Analytical calculations with and without each bowtie filter show that some materials for a given design produce bowtie filters that are too large for implementation in breast CT scanners or too small to accurately manufacture. Results also demonstrate the ability to manipulate the energy fluence distribution (dynamic range) by using different materials, or different combinations of materials, for a given bowtie filter design. This feature is especially advantageous when using photon counting detector technology. Monte Carlo simulation results from PENELOPE show that all studied material choices for bowtie design #2 achieve nearly uniform dose distribution, noise uniformity index less than 5%, and nearly uniform scatter-to-primary ratio. These same features can also be obtained using certain materials with bowtie designs #1 and #3. Conclusions: With the three bowtie filter designs used in this work, the selection of material is an important design consideration. An appropriate material choice can improve image quality, dose uniformity, and dynamic range

Dynamic Kalman filtering to separate low-frequency instabilities from turbulent fluctuations: Application to the Large-Eddy Simulation of unsteady turbulent flows

International Nuclear Information System (INIS)

Cahuzac, A; Boudet, J; Borgnat, P; Lévêque, E

2011-01-01

A dynamic method based on Kalman filtering is presented to isolate low-frequency unsteadiness from turbulent fluctuations in the large-eddy simulation (LES) of unsteady turbulent flows. The method can be viewed as an adaptive exponential smoothing, in which the smoothing factor adapts itself dynamically to the local behavior of the flow. Interestingly, the proposed method does not require any empirical tuning. In practice, it is used to estimate a shear-improved Smagorinsky viscosity, in which the low-frequency component of the velocity field is used to estimate a correction term to the Smagorinsky viscosity. The LES of the flow past a circular cylinder at Reynolds number Re D = 4.7 × 10 4 is examined as a challenging test case. Good comparisons are obtained with the experimental results, indicating the relevance of the shear-improved Smagorinsky model and the efficiency of the Kalman filtering. Finally, the adaptive cut-off of the Kalman filter is investigated, and shown to adapt locally and instantaneously to the complex flow around the cylinder.

TH-AB-207A-07: Radiation Dose Simulation for a Newly Proposed Dynamic Bowtie Filters for CT Using Fast Monte Carlo Methods

Energy Technology Data Exchange (ETDEWEB)

Liu, T; Lin, H; Gao, Y; Caracappa, P; Wang, G; Cong, W; Xu, X [Rensselaer Polytechnic Institute, Troy, NY (United States)

2016-06-15

Purpose: Dynamic bowtie filter is an innovative design capable of modulating the X-ray and balancing the flux in the detectors, and it introduces a new way of patient-specific CT scan optimizations. This study demonstrates the feasibility of performing fast Monte Carlo dose calculation for a type of dynamic bowtie filter for cone-beam CT (Liu et al. 2014 9(7) PloS one) using MIC coprocessors. Methods: The dynamic bowtie filter in question consists of a highly attenuating bowtie component (HB) and a weakly attenuating bowtie (WB). The HB is filled with CeCl3 solution and its surface is defined by a transcendental equation. The WB is an elliptical cylinder filled with air and immersed in the HB. As the scanner rotates, the orientation of WB remains the same with the static patient. In our Monte Carlo simulation, the HB was approximated by 576 boxes. The phantom was a voxelized elliptical cylinder composed of PMMA and surrounded by air (44cm×44cm×40cm, 1000×1000×1 voxels). The dose to the PMMA phantom was tallied with 0.15% statistical uncertainty under 100 kVp source. Two Monte Carlo codes ARCHER and MCNP-6.1 were compared. Both used double-precision. Compiler flags that may trade accuracy for speed were avoided. Results: The wall time of the simulation was 25.4 seconds by ARCHER on a 5110P MIC, 40 seconds on a X5650 CPU, and 523 seconds by the multithreaded MCNP on the same CPU. The high performance of ARCHER is attributed to the parameterized geometry and vectorization of the program hotspots. Conclusion: The dynamic bowtie filter modeled in this study is able to effectively reduce the dynamic range of the detected signals for the photon-counting detectors. With appropriate software optimization methods, the accelerator-based (MIC and GPU) Monte Carlo dose engines have shown good performance and can contribute to patient-specific CT scan optimizations.

IMPLICIT DUAL CONTROL BASED ON PARTICLE FILTERING AND FORWARD DYNAMIC PROGRAMMING.

Science.gov (United States)

Bayard, David S; Schumitzky, Alan

2010-03-01

This paper develops a sampling-based approach to implicit dual control. Implicit dual control methods synthesize stochastic control policies by systematically approximating the stochastic dynamic programming equations of Bellman, in contrast to explicit dual control methods that artificially induce probing into the control law by modifying the cost function to include a term that rewards learning. The proposed implicit dual control approach is novel in that it combines a particle filter with a policy-iteration method for forward dynamic programming. The integration of the two methods provides a complete sampling-based approach to the problem. Implementation of the approach is simplified by making use of a specific architecture denoted as an H-block. Practical suggestions are given for reducing computational loads within the H-block for real-time applications. As an example, the method is applied to the control of a stochastic pendulum model having unknown mass, length, initial position and velocity, and unknown sign of its dc gain. Simulation results indicate that active controllers based on the described method can systematically improve closed-loop performance with respect to other more common stochastic control approaches.

Numerical Study on Self-Cleaning Canister Filter With Add-On Filter Cap

Directory of Open Access Journals (Sweden)

Mohammed Akmal Nizam

2017-01-01

Full Text Available Filtration in a turbo machinery system such as a gas turbine will ensure that the air entering the inlet is free from contaminants that could bring damage to the main system. Self-cleaning filter systems for gas turbines are designed for continuously efficient flow filtration. A good filter would be able to maintain its effectiveness over a longer time period, prolonging the duration between filter replacements and providing lower pressure drop over its operating lifetime. With this goal in mind, the current study is focused on the difference in pressure loss of the benchmark Salutary Avenue Self-cleaning filter in comparison to a new design with an add-on filter cap. Geometry for the add-on filter cap will be based from Salutary Avenue Manufacturing Sdn.Bhd. SOLIDWORKS software was used to model the geometry of the filter, while simulation analysis on the flow through the filter was done using Computational Fluid Dynamic (CFD software. The simulations are based on a low velocity condition, in which the parameter for the inlet velocity are set at 0.032 m/s, 0.063 m/s, 0.094 m/s and 0.126 m/s respectively. From the simulation data obtained for the inlet velocities considered, the pressure drop reduction of the modified filter compared to the benchmark was found to be between 7.59% and 30.18%. All in all, the modification of the filter cap produced a lower pressure drop in comparison with the benchmark filter; an improvement of 27.02% for the total pressure drop was obtained.

Marcuse e o homem unidimensional: pensamento único atravessando o Estado e as instituições

Directory of Open Access Journals (Sweden)

Rogério Lustosa Bastos

2014-06-01

Full Text Available http://dx.doi.org/10.1590/S1414-49802014000100012 O presente artigo, baseando-se em Marcuse, critica a atual globalização e sua rubrica a um modelo dito consensual aos valores do mercado, o homem unidimensional. Este, pretendendo ser o pensamento único, se firmará não só por ditar as condições concretas e subjetivas para todos, mas também por reproduzi-las pelo Estado, notadamente, através das instituições sociais que, apresentando-se como uma rede hegemônica, tenderão a reproduzir essa unidimensionalidade pelo planeta. Sob tempos de quase absoluto consenso em prol desses valores, o artigo reflete sobre as possíveis rupturas ao referido modelo.

Dynamic Heterogeneous Multiscale Filtration Model: Probing Micro- and Macroscopic Filtration Characteristics of Gasoline Particulate Filters.

Science.gov (United States)

Gong, Jian; Viswanathan, Sandeep; Rothamer, David A; Foster, David E; Rutland, Christopher J

2017-10-03

Motivated by high filtration efficiency (mass- and number-based) and low pressure drop requirements for gasoline particulate filters (GPFs), a previously developed heterogeneous multiscale filtration (HMF) model is extended to simulate dynamic filtration characteristics of GPFs. This dynamic HMF model is based on a probability density function (PDF) description of the pore size distribution and classical filtration theory. The microstructure of the porous substrate in a GPF is resolved and included in the model. Fundamental particulate filtration experiments were conducted using an exhaust filtration analysis (EFA) system for model validation. The particulate in the filtration experiments was sampled from a spark-ignition direct-injection (SIDI) gasoline engine. With the dynamic HMF model, evolution of the microscopic characteristics of the substrate (pore size distribution, porosity, permeability, and deposited particulate inside the porous substrate) during filtration can be probed. Also, predicted macroscopic filtration characteristics including particle number concentration and normalized pressure drop show good agreement with the experimental data. The resulting dynamic HMF model can be used to study the dynamic particulate filtration process in GPFs with distinct microstructures, serving as a powerful tool for GPF design and optimization.

Filter-extruded liposomes revisited

DEFF Research Database (Denmark)

Hinna, Askell; Steiniger, Frank; Hupfeld, Stefan

2016-01-01

(pore-size, number of filter passages, and flow-rate), flow field-flow fractionation in conjunction with multi-angle laser light scattering (AF4-MALLS, Wyatt Technology Corp., Santa Barbara, CA) was employed. Liposome size-distributions determined by AF4-MALLS were compared with those of dynamic light...... is suggested to prepare large (300 nm) liposomes with rather narrow size distribution, based on the filter extrusion at defined flow-rates in combination with freeze-/ thaw-cycling and bench-top centrifugation....

Adaptive robust Kalman filtering for precise point positioning

International Nuclear Information System (INIS)

Guo, Fei; Zhang, Xiaohong

2014-01-01

The optimality of precise point postioning (PPP) solution using a Kalman filter is closely connected to the quality of the a priori information about the process noise and the updated mesurement noise, which are sometimes difficult to obtain. Also, the estimation enviroment in the case of dynamic or kinematic applications is not always fixed but is subject to change. To overcome these problems, an adaptive robust Kalman filtering algorithm, the main feature of which introduces an equivalent covariance matrix to resist the unexpected outliers and an adaptive factor to balance the contribution of observational information and predicted information from the system dynamic model, is applied for PPP processing. The basic models of PPP including the observation model, dynamic model and stochastic model are provided first. Then an adaptive robust Kalmam filter is developed for PPP. Compared with the conventional robust estimator, only the observation with largest standardized residual will be operated by the IGG III function in each iteration to avoid reducing the contribution of the normal observations or even filter divergence. Finally, tests carried out in both static and kinematic modes have confirmed that the adaptive robust Kalman filter outperforms the classic Kalman filter by turning either the equivalent variance matrix or the adaptive factor or both of them. This becomes evident when analyzing the positioning errors in flight tests at the turns due to the target maneuvering and unknown process/measurement noises. (paper)

Perspectives on Nonlinear Filtering

KAUST Repository

Law, Kody

2015-01-01

The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

Perspectives on Nonlinear Filtering

KAUST Repository

Law, Kody

2015-01-07

The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

Stable and efficient cubature-based filtering in dynamical systems

CERN Document Server

Ballreich, Dominik

2017-01-01

The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.

Active filter for the DESY III dipole circuit

International Nuclear Information System (INIS)

Bothe, W.

1991-01-01

The DESY 3 dipole circuit is now operated in a ramp mode cycle with 3.6 s repetition rate. Excitation is done by a 12-pulse thyristor converter, followed by a passive filter. The existing current control could be improved by addition of an active filter. The use of a more efficient passive filter reduces the size of the active filter and does not deteriorate the dynamic behavior. The design of the control loops and the results of the simulation are presented

A quantum extended Kalman filter

International Nuclear Information System (INIS)

Emzir, Muhammad F; Woolley, Matthew J; Petersen, Ian R

2017-01-01

In quantum physics, a stochastic master equation (SME) estimates the state (density operator) of a quantum system in the Schrödinger picture based on a record of measurements made on the system. In the Heisenberg picture, the SME is a quantum filter. For a linear quantum system subject to linear measurements and Gaussian noise, the dynamics may be described by quantum stochastic differential equations (QSDEs), also known as quantum Langevin equations, and the quantum filter reduces to a so-called quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to systems of nonlinear QSDEs. We will show that there are conditions under which a filter similar to a classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problem with ‘state-dependent’ covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems that involve multiple modes, nonlinear Hamiltonians, and simultaneous jump-diffusive measurements. (paper)

A quantum extended Kalman filter

Science.gov (United States)

Emzir, Muhammad F.; Woolley, Matthew J.; Petersen, Ian R.

2017-06-01

In quantum physics, a stochastic master equation (SME) estimates the state (density operator) of a quantum system in the Schrödinger picture based on a record of measurements made on the system. In the Heisenberg picture, the SME is a quantum filter. For a linear quantum system subject to linear measurements and Gaussian noise, the dynamics may be described by quantum stochastic differential equations (QSDEs), also known as quantum Langevin equations, and the quantum filter reduces to a so-called quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to systems of nonlinear QSDEs. We will show that there are conditions under which a filter similar to a classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problem with ‘state-dependent’ covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems that involve multiple modes, nonlinear Hamiltonians, and simultaneous jump-diffusive measurements.

Tunable Multiband Microwave Photonic Filters

Directory of Open Access Journals (Sweden)

Mable P. Fok

2017-11-01

Full Text Available The increasing demand for multifunctional devices, the use of cognitive wireless technology to solve the frequency resource shortage problem, as well as the capabilities and operational flexibility necessary to meet ever-changing environment result in an urgent need of multiband wireless communications. Spectral filter is an essential part of any communication systems, and in the case of multiband wireless communications, tunable multiband RF filters are required for channel selection, noise/interference removal, and RF signal processing. Unfortunately, it is difficult for RF electronics to achieve both tunable and multiband spectral filtering. Recent advancements of microwave photonics have proven itself to be a promising candidate to solve various challenges in RF electronics including spectral filtering, however, the development of multiband microwave photonic filtering still faces lots of difficulties, due to the limited scalability and tunability of existing microwave photonic schemes. In this review paper, we first discuss the challenges that were facing by multiband microwave photonic filter, then we review recent techniques that have been developed to tackle the challenge and lead to promising developments of tunable microwave photonic multiband filters. The successful design and implementation of tunable microwave photonic multiband filter facilitate the vision of dynamic multiband wireless communications and radio frequency signal processing for commercial, defense, and civilian applications.

Hydrodynamics of microbial filter feeding.

Science.gov (United States)

Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia; Walther, Jens H; Kiørboe, Thomas; Andersen, Anders

2017-08-29

Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate amounts of water. Also, the trade-off in the filter spacing remains unexplored, despite its simple formulation: A filter too coarse will allow suitably sized prey to pass unintercepted, whereas a filter too fine will cause strong flow resistance. We quantify the feeding flow of the filter-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), something notoriously difficult to visualize but sporadically observed in the related choanocytes (sponges). A CFD model with a flagellar vane correctly predicts the filtration rate of D. grandis , and using a simple model we can account for the filtration rates of other microbial filter feeders. We finally predict how optimum filter mesh size increases with cell size in microbial filter feeders, a prediction that accords very well with observations. We expect our results to be of significance for small-scale biophysics and trait-based ecological modeling.

Nonlinear consider covariance analysis using a sigma-point filter formulation

Science.gov (United States)

Lisano, Michael E.

2006-01-01

The research reported here extends the mathematical formulation of nonlinear, sigma-point estimators to enable consider covariance analysis for dynamical systems. This paper presents a novel sigma-point consider filter algorithm, for consider-parameterized nonlinear estimation, following the unscented Kalman filter (UKF) variation on the sigma-point filter formulation, which requires no partial derivatives of dynamics models or measurement models with respect to the parameter list. It is shown that, consistent with the attributes of sigma-point estimators, a consider-parameterized sigma-point estimator can be developed entirely without requiring the derivation of any partial-derivative matrices related to the dynamical system, the measurements, or the considered parameters, which appears to be an advantage over the formulation of a linear-theory sequential consider estimator. It is also demonstrated that a consider covariance analysis performed with this 'partial-derivative-free' formulation yields equivalent results to the linear-theory consider filter, for purely linear problems.

Dynamic Sensor Interrogation Using Wavelength-Swept Laser with a Polygon-Scanner-Based Wavelength Filter

Science.gov (United States)

Kwon, Yong Seok; Ko, Myeong Ock; Jung, Mi Sun; Park, Ik Gon; Kim, Namje; Han, Sang-Pil; Ryu, Han-Cheol; Park, Kyung Hyun; Jeon, Min Yong

2013-01-01

We report a high-speed (∼2 kHz) dynamic multiplexed fiber Bragg grating (FBG) sensor interrogation using a wavelength-swept laser (WSL) with a polygon-scanner-based wavelength filter. The scanning frequency of the WSL is 18 kHz, and the 10 dB scanning bandwidth is more than 90 nm around a center wavelength of 1,540 nm. The output from the WSL is coupled into the multiplexed FBG array, which consists of five FBGs. The reflected Bragg wavelengths of the FBGs are 1,532.02 nm, 1,537.84 nm, 1,543.48 nm, 1,547.98 nm, and 1,553.06 nm, respectively. A dynamic periodic strain ranging from 500 Hz to 2 kHz is applied to one of the multiplexed FBGs, which is fixed on the stage of the piezoelectric transducer stack. Good dynamic performance of the FBGs and recording of their fast Fourier transform spectra have been successfully achieved with a measuring speed of 18 kHz. The signal-to-noise ratio and the bandwidth over the whole frequency span are determined to be more than 30 dB and around 10 Hz, respectively. We successfully obtained a real-time measurement of the abrupt change of the periodic strain. The dynamic FBG sensor interrogation system can be read out with a WSL for high-speed and high-sensitivity real-time measurement. PMID:23899934

Stochastic processes and filtering theory

CERN Document Server

Jazwinski, Andrew H

1970-01-01

This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well.Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probab

Robust filtering for uncertain systems a parameter-dependent approach

CERN Document Server

Gao, Huijun

2014-01-01

This monograph provides the reader with a systematic treatment of robust filter design, a key issue in systems, control and signal processing, because of the fact that the inevitable presence of uncertainty in system and signal models often degrades the filtering performance and may even cause instability. The methods described are therefore not subject to the rigorous assumptions of traditional Kalman filtering. The monograph is concerned with robust filtering for various dynamical systems with parametric uncertainties, and focuses on parameter-dependent approaches to filter design. Classical filtering schemes, like H2 filtering and H¥ filtering, are addressed, and emerging issues such as robust filtering with constraints on communication channels and signal frequency characteristics are discussed. The text features: ·        design approaches to robust filters arranged according to varying complexity level, and emphasizing robust filtering in the parameter-dependent framework for the first time; ·...

Particle filters for random set models

CERN Document Server

Ristic, Branko

2013-01-01

“Particle Filters for Random Set Models” presents coverage of state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based  on the Monte Carlo statistical method. The resulting  algorithms, known as particle filters, in the last decade have become one of the essential tools for stochastic filtering, with applications ranging from  navigation and autonomous vehicles to bio-informatics and finance. While particle filters have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. These recent developments have dramatically widened the scope of applications, from single to multiple appearing/disappearing objects, from precise to imprecise measurements and measurement models. This book...

On tempo tracking: Tempogram representation and Kalman filtering

NARCIS (Netherlands)

Cemgil, A.T.; Kappen, H.J.; Desain, P.W.M.; Honing, H.J.

2001-01-01

We formulate tempo tracking in a Bayesian framework where a tempo tracker is modeled as a stochastic dynamical system. The tempo is modeled as a hidden state variable of the system and is estimated by a Kalman filter. The Kalman filter operates on a Tempogram, a wavelet-like multiscale expansion of

Sensor failure detection in dynamical systems by Kalman filtering methodology

International Nuclear Information System (INIS)

Ciftcioglu, O.

1991-03-01

Design of a sensor failure detection system by Kalman filtering methodology is described. The method models the process systems in state-space form, the information on each state being provided by relevant sensors present in the process system. Since the measured states are usually subject to noise, the estimation of the states optimally is an essential requirement. To this end the detection system comprises Kalman estimation filters, the number of which is equal to the number of states concerned. The estimated state of a particular signal in each filter is compared with the corresponding measured signal and difference beyond a predetermined bound is identified as failure, the sensor being identified/isolated as faulty. (author). 19 refs.; 8 figs.; 1 tab

Solution of unidimensional problems from monoenergetics neutrons diffusion through finite differences

International Nuclear Information System (INIS)

Filio Lopez, Carlos.

1979-01-01

A calculation program (URA 6.F4) was elaborated on FORTRAN IV language, that through finite differences solves the unidimensional scalar Helmholtz equation, assuming only one energy group, in spherical cylindrical or plane geometry. The purpose is the determination of the flow distribution in a reactor of spherical cylindrical or plane geometry and the critical dimensions. Feeding as entrance datas to the program the geometry, diffusion coefficients and macroscopic transversals cross sections of absorption and fission for each region. The differential diffusion equation is converted with its boundary conditions, to one system of homogeneous algebraic linear equations using the box integration technique. The investigation on criticality is converted then in a succession of eigenvalue problems for the critical eigenvalue. In general, only is necessary to solve the first eigenvalue and its corresponding eigenvector, employing the power method. The obtained results by the program for the critical dimensions of the clean reactors are admissible, the existing error as respect to the analytic is less of 0.5%; by the analysed reactors of three regions, the relative error with respect to the semianalytic result is less of 0.2%. With this program is possible to obtain one quantitative description of one reactor if the transversal sections that appears in the monoenergetic model are adequatedly averaged by the energy group used. (author)

Electrostatic air filters generated by electric fields

International Nuclear Information System (INIS)

Bergman, W.; Biermann, A.H.; Hebard, H.D.; Lum, B.Y.; Kuhl, W.D.

1981-01-01

This paper presents theoretical and experimental findings on fibrous filters converted to electrostatic operation by a nonionizing electric field. Compared to a conventional fibrous filter, the electrostatic filter has a higher efficiency and a longer, useful life. The increased efficiency is attributed to a time independent attraction between polarized fibers and charged, polarized particles and a time dependent attraction between charged fibers and charged, polarized particles. The charge on the fibers results from a dynamic process of charge accumulation due to the particle deposits and a charge dissipation due to the fiber conductivity

Implicit Kalman filter algorithm for nuclear reactor analysis

International Nuclear Information System (INIS)

Hassberger, J.A.; Lee, J.C.

1986-01-01

Artificial intelligence (AI) is currently the hot topic in nuclear power plant diagnostics and control. Recently, researchers have considered the use of simulation as knowledge in which faster than real-time best-estimate simulations based on first principles are tightly coupled with AI systems for analyzing power plant transients on-line. On-line simulations can be improved through a Kalman filter, a mathematical technique for obtaining the optimal estimate of a system state given the information contained in the equations of system dynamics and measurements made on the system. Filtering can be used to systemically adjust parameters of a low-order simulation model to obtain reasonable agreement between the model and actual plant dynamics. The authors present here a general Kalman filtering algorithm that derives its information of system dynamics implicitly and naturally from the discrete time step-series of state estimates available from a simulation program. Previous research has demonstrated that models adjusted on past data can be coupled with an intelligent controller to predict the future time-course of plant transients

Computational fluid dynamics simulation of transport and retention of nanoparticle in saturated sand filters

International Nuclear Information System (INIS)

Hassan, Ashraf Aly; Li, Zhen; Sahle-Demessie, Endalkachew; Sorial, George A.

2013-01-01

Highlights: ► Breakthrough curves used to study fate of NPs in slow sand filters (SSF). ► CFD simulate transport, attachment/detachment of NPs in SSFs. ► CFD predicted spatial and temporal changes for transient concentrations of NPs. ► CFD predicts low concentrations and steady NP influx would not be retained by SSFs. ► Pulse input is retained with outlet concentration of 0.2% of the inlet. -- Abstract: Experimental and computational investigation of the transport parameters of nanoparticles (NPs) flowing through porous media has been made. This work intends to develop a simulation applicable to the transport and retention of NPs in saturated porous media for investigating the effect of process conditions and operating parameters such, as ion strength, and filtration efficiency. Experimental data obtained from tracer and nano-ceria, CeO 2 , breakthrough studies were used to characterize dispersion of nanoparticle with the flow and their interaction with sand packed columns with different heights. Nanoparticle transport and concentration dynamics were solved using the Eulerian computational fluid dynamics (CFD) solver ANSYS/FLUENT ® based on a scaled down flow model. A numerical study using the Navier–Stokes equation with second order interaction terms was used to simulate the process. Parameters were estimated by fitting tracer, experimental NP transport data, and interaction of NP with the sand media. The model considers different concentrations of steady state inflow of NPs and different amounts of spike concentrations. Results suggest that steady state flow of dispersant-coated NPs would not be retained by a sand filter, while spike concentrations could be dampened effectively. Unlike analytical solutions, the CFD allows estimating flow profiles for structures with complex irregular geometry and uneven packing

Computational fluid dynamics simulation of transport and retention of nanoparticle in saturated sand filters

Energy Technology Data Exchange (ETDEWEB)

Hassan, Ashraf Aly [U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 W. Martin Luther King Drive, Cincinnati, OH 45268 (United States); Li, Zhen [School of Energy, Environmental, Biological, and Medical Engineering, Environmental Engineering Program, University of Cincinnati, Cincinnati, OH (United States); Sahle-Demessie, Endalkachew, E-mail: sahle-demessie.endalkachew@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 W. Martin Luther King Drive, Cincinnati, OH 45268 (United States); Sorial, George A. [School of Energy, Environmental, Biological, and Medical Engineering, Environmental Engineering Program, University of Cincinnati, Cincinnati, OH (United States)

2013-01-15

Highlights: ► Breakthrough curves used to study fate of NPs in slow sand filters (SSF). ► CFD simulate transport, attachment/detachment of NPs in SSFs. ► CFD predicted spatial and temporal changes for transient concentrations of NPs. ► CFD predicts low concentrations and steady NP influx would not be retained by SSFs. ► Pulse input is retained with outlet concentration of 0.2% of the inlet. -- Abstract: Experimental and computational investigation of the transport parameters of nanoparticles (NPs) flowing through porous media has been made. This work intends to develop a simulation applicable to the transport and retention of NPs in saturated porous media for investigating the effect of process conditions and operating parameters such, as ion strength, and filtration efficiency. Experimental data obtained from tracer and nano-ceria, CeO{sub 2}, breakthrough studies were used to characterize dispersion of nanoparticle with the flow and their interaction with sand packed columns with different heights. Nanoparticle transport and concentration dynamics were solved using the Eulerian computational fluid dynamics (CFD) solver ANSYS/FLUENT{sup ®} based on a scaled down flow model. A numerical study using the Navier–Stokes equation with second order interaction terms was used to simulate the process. Parameters were estimated by fitting tracer, experimental NP transport data, and interaction of NP with the sand media. The model considers different concentrations of steady state inflow of NPs and different amounts of spike concentrations. Results suggest that steady state flow of dispersant-coated NPs would not be retained by a sand filter, while spike concentrations could be dampened effectively. Unlike analytical solutions, the CFD allows estimating flow profiles for structures with complex irregular geometry and uneven packing.

Kalman filter-based gap conductance modeling

International Nuclear Information System (INIS)

Tylee, J.L.

1983-01-01

Geometric and thermal property uncertainties contribute greatly to the problem of determining conductance within the fuel-clad gas gap of a nuclear fuel pin. Accurate conductance values are needed for power plant licensing transient analysis and for test analyses at research facilities. Recent work by Meek, Doerner, and Adams has shown that use of Kalman filters to estimate gap conductance is a promising approach. A Kalman filter is simply a mathematical algorithm that employs available system measurements and assumed dynamic models to generate optimal system state vector estimates. This summary addresses another Kalman filter approach to gap conductance estimation and subsequent identification of an empirical conductance model

Computational fluid dynamics simulations of single-phase flow in a filter-press flow reactor having a stack of three cells

International Nuclear Information System (INIS)

Sandoval, Miguel A.; Fuentes, Rosalba; Walsh, Frank C.; Nava, José L.; Ponce de León, Carlos

2016-01-01

Highlights: • Computational fluid dynamic simulations in a filter-press stack of three cells. • The fluid velocity was different in each cell due to local turbulence. • The upper cell link pipe of the filter press cell acts as a fluid mixer. • The fluid behaviour tends towards a continuous mixing flow pattern. • Close agreement between simulations and experimental data was achieved. - Abstract: Computational fluid dynamics (CFD) simulations were carried out for single-phase flow in a pre-pilot filter press flow reactor with a stack of three cells. Velocity profiles and streamlines were obtained by solving the Reynolds-Averaged Navier-Stokes (RANS) equations with a standard k − ε turbulence model. The flow behaviour shows the appearance of jet flow at the entrance to each cell. At lengths from 12 to 15 cm along the cells channels, a plug flow pattern is developed at all mean linear flow rates studied here, 1.2 ≤ u ≤ 2.1 cm s −1 . The magnitude of the velocity profiles in each cell was different, due to the turbulence generated by the change of flow direction in the last fluid manifold. Residence time distribution (RTD) simulations indicated that the fluid behaviour tends towards a continuous mixing flow pattern, owing to flow at the output of each cell across the upper cell link pipe, which acts as a mixer. Close agreement between simulations and experimental RTD was obtained.

Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter

Directory of Open Access Journals (Sweden)

Jing Li

2016-01-01

Full Text Available Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF, which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF, which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation outputs of two filters are merged by interacting multiple model (IMM approach. Experimental results show the accuracy and robustness of the hybrid Kalman filter.

Quantum demolition filtering and optimal control of unstable systems.

Science.gov (United States)

Belavkin, V P

2012-11-28

A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.

Dynamic Filtering Improves Attentional State Prediction with fNIRS

Science.gov (United States)

Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

2016-01-01

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

An Estimation of Human Error Probability of Filtered Containment Venting System Using Dynamic HRA Method

Energy Technology Data Exchange (ETDEWEB)

Jang, Seunghyun; Jae, Moosung [Hanyang University, Seoul (Korea, Republic of)

2016-10-15

The human failure events (HFEs) are considered in the development of system fault trees as well as accident sequence event trees in part of Probabilistic Safety Assessment (PSA). As a method for analyzing the human error, several methods, such as Technique for Human Error Rate Prediction (THERP), Human Cognitive Reliability (HCR), and Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) are used and new methods for human reliability analysis (HRA) are under developing at this time. This paper presents a dynamic HRA method for assessing the human failure events and estimation of human error probability for filtered containment venting system (FCVS) is performed. The action associated with implementation of the containment venting during a station blackout sequence is used as an example. In this report, dynamic HRA method was used to analyze FCVS-related operator action. The distributions of the required time and the available time were developed by MAAP code and LHS sampling. Though the numerical calculations given here are only for illustrative purpose, the dynamic HRA method can be useful tools to estimate the human error estimation and it can be applied to any kind of the operator actions, including the severe accident management strategy.

Building blocks of temporal filters in retinal synapses.

Directory of Open Access Journals (Sweden)

Bongsoo Suh

2014-10-01

Full Text Available Sensory systems must be able to extract features of a stimulus to detect and represent properties of the world. Because sensory signals are constantly changing, a critical aspect of this transformation relates to the timing of signals and the ability to filter those signals to select dynamic properties, such as visual motion. At first assessment, one might think that the primary biophysical properties that construct a temporal filter would be dynamic mechanisms such as molecular concentration or membrane electrical properties. However, in the current issue of PLOS Biology, Baden et al. identify a mechanism of temporal filtering in the zebrafish and goldfish retina that is not dynamic but is in fact a structural building block-the physical size of a synapse itself. The authors observe that small, bipolar cell synaptic terminals are fast and highly adaptive, whereas large ones are slower and adapt less. Using a computational model, they conclude that the volume of the synaptic terminal influences the calcium concentration and the number of available vesicles. These results indicate that the size of the presynaptic terminal is an independent control for the dynamics of a synapse and may reveal aspects of synaptic function that can be inferred from anatomical structure.

Performance Improvement of Shunt Active Power Filter With Dual Parallel Topology

DEFF Research Database (Denmark)

Asiminoaei, Lucian; Lascu, Cristian; Blaabjerg, Frede

2007-01-01

loop and the other is in a feedforward loop for harmonic compensation. Thus, both active power filters bring their own characteristic advantages, i.e., the feedback filter improves the steady-state performance of the harmonic mitigation and the feedforward filter improves the dynamic response. Another......This paper describes the control and parallel operation of two active power filters (APFs). Possible parallel operation situations of two APFs are investigated, and then the proposed topology is analyzed. The filters are coupled in a combined topology in which one filter is connected in a feedback...

Voltage harmonic elimination with RLC based interface smoothing filter

International Nuclear Information System (INIS)

Chandrasekaran, K; Ramachandaramurthy, V K

2015-01-01

A method is proposed for designing a Dynamic Voltage Restorer (DVR) with RLC interface smoothing filter. The RLC filter connected between the IGBT based Voltage Source Inverter (VSI) is attempted to eliminate voltage harmonics in the busbar voltage and switching harmonics from VSI by producing a PWM controlled harmonic voltage. In this method, the DVR or series active filter produces PWM voltage that cancels the existing harmonic voltage due to any harmonic voltage source. The proposed method is valid for any distorted busbar voltage. The operating VSI handles no active power but only harmonic power. The DVR is able to suppress the lower order switching harmonics generated by the IGBT based VSI. Good dynamic and transient results obtained. The Total Harmonic Distortion (THD) is minimized to zero at the sensitive load end. Digital simulations are carried out using PSCAD/EMTDC to validate the performance of RLC filter. Simulated results are presented. (paper)

Study of Robust H∞ Filtering Application in Loosely Coupled INS/GPS System

Directory of Open Access Journals (Sweden)

Lin Zhao

2014-01-01

model, unstable model case is considered. We give an explanation for Kalman filter divergence under uncertain dynamic system and simultaneously investigate the relationship between H∞ filter and Kalman filter. A loosely coupled INS/GPS simulation system is given here to verify this application. Result shows that the robust H∞ filter has a better performance when system suffers uncertainty; also it is more robust compared to the conventional Kalman filter.

Scheme of adaptive polarization filtering based on Kalman model

Institute of Scientific and Technical Information of China (English)

Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

2006-01-01

A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

An Efficient State–Parameter Filtering Scheme Combining Ensemble Kalman and Particle Filters

KAUST Repository

Ait-El-Fquih, Boujemaa

2017-12-11

This work addresses the state-parameter filtering problem for dynamical systems with relatively large-dimensional state and low-dimensional parameters\\' vector. A Bayesian filtering algorithm combining the strengths of the particle filter (PF) and the ensemble Kalman filter (EnKF) is proposed. At each assimilation cycle of the proposed EnKF-PF, the PF is first used to sample the parameters\\' ensemble followed by the EnKF to compute the state ensemble conditional on the resulting parameters\\' ensemble. The proposed scheme is expected to be more efficient than the traditional state augmentation techniques, which suffer from the curse of dimensionality and inconsistency that is particularly pronounced when the state is a strongly nonlinear function of the parameters. In the new scheme, the EnKF and PF interact via their ensembles\\' members, in contrast with the recently introduced two-stage EnKF-PF (TS-EnKF-PF), which exchanges point estimates between EnKF and PF while requiring almost double the computational load. Numerical experiments are conducted with the Lorenz-96 model to assess the behavior of the proposed filter and to evaluate its performances against the joint PF, joint EnKF, and TS-EnKF-PF. Numerical results suggest that the EnKF-PF performs best in all tested scenarios. It was further found to be more robust, successfully estimating both state and parameters in different sensitivity experiments.

An Efficient State–Parameter Filtering Scheme Combining Ensemble Kalman and Particle Filters

KAUST Repository

Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

2017-01-01

This work addresses the state-parameter filtering problem for dynamical systems with relatively large-dimensional state and low-dimensional parameters' vector. A Bayesian filtering algorithm combining the strengths of the particle filter (PF) and the ensemble Kalman filter (EnKF) is proposed. At each assimilation cycle of the proposed EnKF-PF, the PF is first used to sample the parameters' ensemble followed by the EnKF to compute the state ensemble conditional on the resulting parameters' ensemble. The proposed scheme is expected to be more efficient than the traditional state augmentation techniques, which suffer from the curse of dimensionality and inconsistency that is particularly pronounced when the state is a strongly nonlinear function of the parameters. In the new scheme, the EnKF and PF interact via their ensembles' members, in contrast with the recently introduced two-stage EnKF-PF (TS-EnKF-PF), which exchanges point estimates between EnKF and PF while requiring almost double the computational load. Numerical experiments are conducted with the Lorenz-96 model to assess the behavior of the proposed filter and to evaluate its performances against the joint PF, joint EnKF, and TS-EnKF-PF. Numerical results suggest that the EnKF-PF performs best in all tested scenarios. It was further found to be more robust, successfully estimating both state and parameters in different sensitivity experiments.

Sensitivity to changes during antidepressant treatment: a comparison of unidimensional subscales of the Inventory of Depressive Symptomatology (IDS-C) and the Hamilton Depression Rating Scale (HAMD) in patients with mild major, minor or subsyndromal depression.

Science.gov (United States)

Helmreich, Isabella; Wagner, Stefanie; Mergl, Roland; Allgaier, Antje-Kathrin; Hautzinger, Martin; Henkel, Verena; Hegerl, Ulrich; Tadić, André

2012-06-01

In the efficacy evaluation of antidepressant treatments, the total score of the Hamilton Depression Rating Scale (HAMD) is still regarded as the 'gold standard'. We previously had shown that the Inventory of Depressive Symptomatology (IDS) was more sensitive to detect depressive symptom changes than the HAMD17 (Helmreich et al. 2011). Furthermore, studies suggest that the unidimensional subscales of the HAMD, which capture the core depressive symptoms, outperform the full HAMD regarding the detection of antidepressant treatment effects. The aim of the present study was to compare several unidimensional subscales of the HAMD and the IDS regarding their sensitivity to changes in depression symptoms in a sample of patients with mild major, minor or subsyndromal depression (MIND). Biweekly IDS-C28 and HAMD17 data from 287 patients of a 10-week randomised, placebo-controlled trial comparing the effectiveness of sertraline and cognitive-behavioural group therapy in patients with MIND were converted to subscale scores and analysed during the antidepressant treatment course. We investigated sensitivity to depressive change for all scales from assessment-to-assessment, in relation to depression severity level and placebo-verum differences. The subscales performed similarly during the treatment course, with slight advantages for some subscales in detecting treatment effects depending on the treatment modality and on the items included. Most changes in depressive symptomatology were detected by the IDS short scale, but regarding the effect sizes, it performed worse than most subscales. Unidimensional subscales are a time- and cost-saving option in judging drug therapy outcomes, especially in antidepressant treatment efficacy studies. However, subscales do not cover all facets of depression (e.g. atypical symptoms, sleep disturbances), which might be important for comprehensively understanding the nature of the disease depression. Therefore, the cost-to-benefit ratio must be

Caracterización de las proteínas totales de tres ecotipos de maca (Lepidium peruvianum G. Chacón, mediante electroforesis unidimensional y bidimensional

Directory of Open Access Journals (Sweden)

Mario Monteghirfo

2007-12-01

Full Text Available Objetivo: Caracterizar las proteínas solubles que se encuentran en la raíz del Lepidium peruvianum G. Chacón, maca, mediante electroforesis unidimensional y electroforesis bidimensional. Diseño: Estudio de tipo observacional y transversal. Lugar: Centro de Investigación de Bioquímica y Nutrición Alberto Guzmán Barrón. Facultad de Medicina, Universidad Nacional Mayor de San Marcos. Lima, Perú. Materiales: Raíces de Lepidium peruvianum G. Chacón ‘maca’ de los ecotipos blanco, amarillo y morado, procedentes de Junín que fueron obtenidas a través de la Universidad Nacional del Centro del Perú. Métodos: La extracción de las proteínas totales solubles se realizó con una solución antioxidante, seguida de electroforesis unidimensional y bidimensional para su caracterización. Principales medidas de resultados: Número de proteínas solubles, peso molecular de las proteínas y puntos isoelectricos de las proteínas más abundantes. Resultados: El análisis electroforético unidimensional mostró predominio de 2 proteínas (72% de las proteínas solubles totales. Una de 22,5 kDa, denominada en el presente trabajo ‘macatina’ (51% de la proteína total; la otra de 17,0 kDa (21% de la proteína soluble total. El mapa electroforético bidimensional mostró que tanto la ‘macatina’ como la proteína de 17,0 kDa son básicas y presentan 3 isómeros de carga que se distribuyen en un rango de punto isoeléctrico (pI de 7,1 a 8,2. Conclusiones: Las proteínas solubles mostraron un patrón electroforético complejo, siendo la macatina la proteína más abundante.

Void fraction measurement in two-phase flow processes via symbolic dynamic filtering of ultrasonic signals

International Nuclear Information System (INIS)

Chakraborty, Subhadeep; Keller, Eric; Talley, Justin; Srivastav, Abhishek; Ray, Asok; Kim, Seungjin

2009-01-01

This communication introduces a non-intrusive method for void fraction measurement and identification of two-phase flow regimes, based on ultrasonic sensing. The underlying algorithm is built upon the recently reported theory of a statistical pattern recognition method called symbolic dynamic filtering (SDF). The results of experimental validation, generated on a laboratory test apparatus, show a one-to-one correspondence between the flow measure derived from SDF and the void fraction measured by a conductivity probe. A sharp change in the slope of flow measure is found to be in agreement with a transition from fully bubbly flow to cap-bubbly flow. (rapid communication)

Parâmetros ecocardiográficos em modo unidimensional de cães da raça Poodle miniatura, clinicamente sadios Echocardiographic parameters in unidimensional mode from clinically normal miniature Poodle dogs

Directory of Open Access Journals (Sweden)

Ronaldo Jun Yamato

2006-02-01

Full Text Available No Brasil, a população canina da raça Poodle, principalmente a variação miniatura, cresce em progressão geométrica, sendo esta raça freqüentemente acometida por cardiopatias congênitas e adquiridas. O escopo deste estudo foi padronizar e avaliar os parâmetros ecocardiográficos em modo unidimensional (M de cães da raça Poodle miniatura, devido ao aumento populacional da mesma, a variação existente destes parâmetros entre as raças caninas e as diversas cardiopatias às quais os Poodles são predispostos. Foram utilizados 30 cães, da referida raça, sendo 09 machos e 21 fêmeas com idades entre 2 a 7 anos (3,87±1,55 e peso corpóreo variando de 2,0 a 8,7 quilos (4,49±1,38. Os cães incluídos neste estudo foram considerados sadios, após terem sido submetidos aos exames físico, laboratoriais, eletrocardiográfico, radiográfico e à mensuração da pressão arterial. Após a realização do exame ecocardiográfico e a análise dos resultados, foi possível obter os valores de referência do exame ecocardiográfico, em modo M, para os cães da raça Poodle miniatura e, ainda, sugerir que o peso corpóreo e altura podem exercer influência sobre os parâmetros ecocardiográficos.In Brazil, the canine population of the Poodle, mainly the Miniature variation, grows in geometric progression, beeing this breed frequently affected by congenital and adquired cardiopathies. The main objective of this study was the standardization and evaluation of the echocardiographic parameters in unidimensional (M mode, from clinically normal Miniature Poodle dogs. Thirthy Miniature Poodle dogs, 09 males and 21 females ageing between 2 and 7 years old (3.87±1.55, and weight varying from 2.0 to 8.7 kilogram (4.49±1.38 were studied. To be included in this study, physical exam, hemogram, biochemical profile, urinalysis, detection of circulating microfilaries as well as ELISA test for Dirofilaria immitis, electrocardiographic, radiographic exams and

Estimation of time-varying reactivity by the H∞ optimal linear filter

International Nuclear Information System (INIS)

Suzuki, Katsuo; Shimazaki, Junya; Watanabe, Koiti

1995-01-01

The problem of estimating the time-varying net reactivity from flux measurements is solved for a point reactor kinetics model using a linear filtering technique in an H ∞ settings. In order to sue this technique, an appropriate dynamical model of the reactivity is constructed that can be embedded into the reactor model as one of its variables. A filter, which minimizes the H ∞ norm of the estimation error power spectrum, operates on neutron density measurements corrupted by noise and provides an estimate of the dynamic net reactivity. Computer simulations are performed to reveal the basic characteristics of the H ∞ optimal filter. The results of the simulation indicate that the filter can be used to determine the time-varying reactivity from neutron density measurements that have been corrupted by noise

Filter Bank Approach to the Estimation of Flexible Modes in Dynamic Systems

National Research Council Canada - National Science Library

Tzellos, Konstantinos

2007-01-01

.... In this thesis the problem of identifying frequencies of disturbances in flexible systems using advanced Digital Signal Processing techniques such as filter banks and Quadrature Mirror Filters is addressed...

Noise reduction and functional maps image quality improvement in dynamic CT perfusion using a new k-means clustering guided bilateral filter (KMGB).

Science.gov (United States)

Pisana, Francesco; Henzler, Thomas; Schönberg, Stefan; Klotz, Ernst; Schmidt, Bernhard; Kachelrieß, Marc

2017-07-01

Dynamic CT perfusion (CTP) consists in repeated acquisitions of the same volume in different time steps, slightly before, during and slightly afterwards the injection of contrast media. Important functional information can be derived for each voxel, which reflect the local hemodynamic properties and hence the metabolism of the tissue. Different approaches are being investigated to exploit data redundancy and prior knowledge for noise reduction of such datasets, ranging from iterative reconstruction schemes to high dimensional filters. We propose a new spatial bilateral filter which makes use of the k-means clustering algorithm and of an optimal calculated guiding image. We named the proposed filter as k-means clustering guided bilateral filter (KMGB). In this study, the KMGB filter is compared with the partial temporal non-local means filter (PATEN), with the time-intensity profile similarity (TIPS) filter, and with a new version derived from it, by introducing the guiding image (GB-TIPS). All the filters were tested on a digital in-house developed brain CTP phantom, were noise was added to simulate 80 kV and 200 mAs (default scanning parameters), 100 mAs and 30 mAs. Moreover, the filters performances were tested on 7 noisy clinical datasets with different pathologies in different body regions. The original contribution of our work is two-fold: first we propose an efficient algorithm to calculate a guiding image to improve the results of the TIPS filter, secondly we propose the introduction of the k-means clustering step and demonstrate how this can potentially replace the TIPS part of the filter obtaining better results at lower computational efforts. As expected, in the GB-TIPS, the introduction of the guiding image limits the over-smoothing of the TIPS filter, improving spatial resolution by more than 50%. Furthermore, replacing the time-intensity profile similarity calculation with a fuzzy k-means clustering strategy (KMGB) allows to control the edge preserving

Fault diagnosis system of electromagnetic valve using neural network filter

International Nuclear Information System (INIS)

Hayashi, Shoji; Odaka, Tomohiro; Kuroiwa, Jousuke; Ogura, Hisakazu

2008-01-01

This paper is concerned with the gas leakage fault detection of electromagnetic valve using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty in detecting gas leakage faults by sound signals lies in the fact that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system, and an accurate mathematical model of the dynamic system can be established using a neural network filter. The predicted error between predicted values and practical ones constitutes the output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that the neural network filter was effective in gas leakage detection. (author)

Pedestrian Path Prediction with Recursive Bayesian Filters: A Comparative Study

NARCIS (Netherlands)

Schneider, N.; Gavrila, D.M.

2013-01-01

In the context of intelligent vehicles, we perform a comparative study on recursive Bayesian filters for pedestrian path prediction at short time horizons (< 2s). We consider Extended Kalman Filters (EKF) based on single dynamical models and Interacting Multiple Models (IMM) combining several such

Testing digital recursive filtering method for radiation measurement channel using pin diode detector

International Nuclear Information System (INIS)

Talpalariu, C. M.; Talpalariu, J.; Popescu, O.; Mocanasu, M.; Lita, I.; Visan, D. A.

2016-01-01

In this work we have studied a software filtering method implemented in a pulse counting computerized measuring channel using PIN diode radiation detector. In case our interest was focalized for low rate decay radiation measurement accuracies improvement and response time optimization. During works for digital mathematical algorithm development, we used a hardware radiation measurement channel configuration based on PIN diode BPW34 detector, preamplifier, filter and programmable counter, computer connected. We report measurement results using two digital recursive methods in statically and dynamically field evolution. Software for graphical input/output real time diagram representation was designed and implemented, facilitating performances evaluation between the response of fixed configuration software recursive filter and dynamically adaptive configuration recursive filter. (authors)

GASDRA: Galaxy Spectrum Dynamic Range Analysis for Photometric Redshift Filter Partition Optimization

Energy Technology Data Exchange (ETDEWEB)

Vicente, J. de; Sanchez, E.; Sevilla, I.; Castilla, J.; Ponce, R.; Sanchez, F. J.

2012-04-11

The photometric redshift is an active area of research. It is becoming the preferred method for redshift measurement above spectroscopy one for large surveys. In these surveys, the requirement in redshift precision is relaxed in benefit of obtaining the measurements of large number of galaxies. One of the more relevant decisions to be taken in the design of a photometric redshift experiment is the number of filters since it affects deeply to the precision and survey time. Currently, there is not a clear method for evaluating the impact in both precision and exposure time of a determined filter partition set and usually it is determined by detailed simulations on the behavior of photo-z algorithms. In this note we describe GASDRA, a new method for extracting the minimal signal to noise requirement, depending on the number of filters needed for preserving the filtered spectrum shape, and hence to make feasible the spectrum identification. The application of this requirement guaranties a determined precision in the spectrum measurement. Although it cannot be translated directly to absolute photometric redshift error, it does provide a method for comparing the relative precision achieved in the spectrum representation by different sets of filters. We foresee that this relative precision is close related to photo-z error. In addition, we can evaluate the impact in the exposure time of any filter partition set with respect to other. (Author) 11 refs.

GASDRA: Galaxy Spectrum Dynamic Range Analysis for Photometric Redshift Filter Partition Optimization

International Nuclear Information System (INIS)

Vicente, J. de; Sanchez, E.; Sevilla, I.; Castilla, J.; Ponce, R.; Sanchez, F. J.

2012-01-01

The photometric redshift is an active area of research. It is becoming the preferred method for redshift measurement above spectroscopy one for large surveys. In these surveys, the requirement in redshift precision is relaxed in benefit of obtaining the measurements of large number of galaxies. One of the more relevant decisions to be taken in the design of a photometric redshift experiment is the number of filters since it affects deeply to the precision and survey time. Currently, there is not a clear method for evaluating the impact in both precision and exposure time of a determined filter partition set and usually it is determined by detailed simulations on the behavior of photo-z algorithms. In this note we describe GASDRA, a new method for extracting the minimal signal to noise requirement, depending on the number of filters needed for preserving the filtered spectrum shape, and hence to make feasible the spectrum identification. The application of this requirement guaranties a determined precision in the spectrum measurement. Although it cannot be translated directly to absolute photometric redshift error, it does provide a method for comparing the relative precision achieved in the spectrum representation by different sets of filters. We foresee that this relative precision is close related to photo-z error. In addition, we can evaluate the impact in the exposure time of any filter partition set with respect to other. (Author) 11 refs.

A reduced-order filtering approach for 3D dynamical electrical impedance tomography

International Nuclear Information System (INIS)

Voutilainen, A; Lehikoinen, A; Vauhkonen, M; Kaipio, J P

2011-01-01

Recently, it has been shown that the state estimation approach to process tomography can provide estimates that are significantly better than (a sequence of) conventional stationary snapshot estimates. One of the main obstacles of the adoption of the recursive state estimation algorithms, most commonly different versions of the Kalman filter, is the computational complexity. This is due to both the required large dimension for the state variable and the need to use iterative versions of the Kalman filter in such cases in which there are large contrasts or varying background. In this paper, we propose to use a reduced-order representation for the state variable. In particular, we propose to use the proper orthogonal decomposition-related basis for the state. We consider a simulation study with fluctuating background conductivity, and, in particular, with fluctuating contact impedances. We compare the proposed approach to three different versions of the Kalman filter having different computational complexities. We show that this approach allows the reduction of the dimension of the problem approximately by an order of magnitude and yields essentially as accurate estimates as the most accurate traditional Kalman filter version, the iterated extended Kalman filter

Mechanical design and qualification of IR filter mounts and filter wheel of INSAT-3D sounder for low temperature

Science.gov (United States)

Vora, A. P.; Rami, J. B.; Hait, A. K.; Dewan, C. P.; Subrahmanyam, D.; Kirankumar, A. S.

2017-11-01

Next generation Indian Meteorological Satellite will carry Sounder instrument having subsystem of filter wheel measuring Ø260mm and carrying 18 filters arranged in three concentric rings. These filters made from Germanium, are used to separate spectral channels in IR band. Filter wheel is required to be cooled to 214K and rotated at 600 rpm. This Paper discusses the challenges faced in mechanical design of the filter wheel, mainly filter mount design to protect brittle germanium filters from failure under stresses due to very low temperature, compactness of the wheel and casings for improved thermal efficiency, survival under vibration loads and material selection to keep it lighter in weight. Properties of Titanium, Kovar, Invar and Aluminium materials are considered for design. The mount has been designed to accommodate both thermal and dynamic loadings without introducing significant aberrations into the optics or incurring permanent alignment shifts. Detailed finite element analysis of mounts was carried out for stress verification. Results of the qualification tests are discussed for given temperature range of 100K and vibration loads of 12g in Sine and 11.8grms in Random at mount level. Results of the filter wheel qualification as mounted in Electro Optics Module (EOM) are also presented.

Power Efficient Design of Parallel/Serial FIR Filters in RNS

DEFF Research Database (Denmark)

Petricca, Massimo; Albicocco, Pietro; Cardarilli, Gian Carlo

2012-01-01

It is well known that the Residue Number System (RNS) provides an efficient implementation of parallel FIR filters especially when the filter order and the dynamic range are high. The two main drawbacks of RNS, need of converters and coding overhead, make a serialized implementation of the FIR...

An efficient incremental learning mechanism for tracking concept drift in spam filtering.

Directory of Open Access Journals (Sweden)

Jyh-Jian Sheu

Full Text Available This research manages in-depth analysis on the knowledge about spams and expects to propose an efficient spam filtering method with the ability of adapting to the dynamic environment. We focus on the analysis of email's header and apply decision tree data mining technique to look for the association rules about spams. Then, we propose an efficient systematic filtering method based on these association rules. Our systematic method has the following major advantages: (1 Checking only the header sections of emails, which is different from those spam filtering methods at present that have to analyze fully the email's content. Meanwhile, the email filtering accuracy is expected to be enhanced. (2 Regarding the solution to the problem of concept drift, we propose a window-based technique to estimate for the condition of concept drift for each unknown email, which will help our filtering method in recognizing the occurrence of spam. (3 We propose an incremental learning mechanism for our filtering method to strengthen the ability of adapting to the dynamic environment.

Monte Carlo filters for identification of nonlinear structural dynamical ...

Indian Academy of Sciences (India)

The theory of Kalman filtering provides one of ...... expansion (appendix B contains a reasonably self-contained account of how such expansions ...... Shinozuka M, Ghanem R 1995 Structural system identification II: experimental verification.

X-ray fluorescence determination of Au, Pd and Pt from chloride solutions after preconcentration on cellulose filters

International Nuclear Information System (INIS)

Gordeeva, V.P.; Glazkova, S.V.; Tsysin, G.I.; Ivanov, V.M.; Zolotov, Yu. A.

2003-01-01

The aim of this work was synthesis of new sorption cellulose filters for dynamic preconcentration of Au, Pd and Pt from chloride solutions and subsequent XRF determination of these elements on the filters. New filters were prepared by impregnation of a filter paper with solution of tri-n-octylamine and paraffin in hexane (TOA-filters). The effect of paraffin and TOA concentration in hexane on a content of nitrogen in a filter was studied. It was found that Au(III), Pd(II) and Pt(IV) were quantitatively recovered on the TOA-filters (filtering surface diameter of 23 mm, thickness of 0.15 mm) from 0.5 - 1 M HCl at a flow rates of 2-5 ml min-1 from 10-100 ml of solution. The mathematical model of sorption dynamics was offered for the estimation of potential possibilities of new impregnated sorbents and for the evaluation of optimum dynamic conditions allowing to achieve of maximum concentration efficiency (CE max ). The elements were determined directly on the filters by XRF spectrometer. Palladium was also determined on the TOA-filters after formation of coloured compounds of metal with 4-(2-pyridylazo)resorcinol (PAR) by diffuse reflectance spectroscopy with the calculation of calorimetric characteristics and using test-scale. (authors)

Experimental demonstration of H∞ filter performance for dynamic compensation of rhodium neutron detectors

International Nuclear Information System (INIS)

Park, Moon-Ghu; Choi, Yu-Sun; Lee, Kwang-Dae

2008-01-01

This paper describes the experimental demonstration of the theoretical result of the previous work on LMI (linear matrix inequality) based H ∞ filter for time-delay compensation of self-powered neutron detectors. The filter gains are optimized in the sense of noise attenuation level of H ∞ setting. By introducing bounded real lemma, the conventional algebraic Riccati inequalities are converted into linear matrix inequalities (LMIs). Finally, the filter design problem is solved via the convex optimization framework using LMIs. The experimental measurements of rhodium detector signal from a research reactor show that the predicted theoretical filter performance is verified by showing successful reconstruction of the reference power signal

Rasch analysis suggested three unidimensional domains for Affiliate Stigma Scale: additional psychometric evaluation.

Science.gov (United States)

Chang, Chih-Cheng; Su, Jian-An; Tsai, Ching-Shu; Yen, Cheng-Fang; Liu, Jiun-Horng; Lin, Chung-Ying

2015-06-01

To examine the psychometrics of the Affiliate Stigma Scale using rigorous psychometric analysis: classical test theory (CTT) (traditional) and Rasch analysis (modern). Differential item functioning (DIF) items were also tested using Rasch analysis. Caregivers of relatives with mental illness (n = 453; mean age: 53.29 ± 13.50 years) were recruited from southern Taiwan. Each participant filled out four questionnaires: Affiliate Stigma Scale, Rosenberg Self-Esteem Scale, Beck Anxiety Inventory, and one background information sheet. CTT analyses showed that the Affiliate Stigma Scale had satisfactory internal consistency (α = 0.85-0.94) and concurrent validity (Rosenberg Self-Esteem Scale: r = -0.52 to -0.46; Beck Anxiety Inventory: r = 0.27-0.34). Rasch analyses supported the unidimensionality of three domains in the Affiliate Stigma Scale and indicated four DIF items (affect domain: 1; cognitive domain: 3) across gender. Our findings, based on rigorous statistical analysis, verified the psychometrics of the Affiliate Stigma Scale and reported its DIF items. We conclude that the three domains of the Affiliate Stigma Scale can be separately used and are suitable for measuring the affiliate stigma of caregivers of relatives with mental illness. Copyright © 2015 Elsevier Inc. All rights reserved.

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

Science.gov (United States)

Simon, Dan; Simon, Donald L.

2005-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

International Nuclear Information System (INIS)

Zhao, Yibo; Jiang, Yi; Feng, Jiuchao; Wu, Lifu

2016-01-01

Highlights: • A novel nonlinear Wiener adaptive filters based on the backslash operator are proposed. • The identification approach to the memristor-based chaotic systems using the proposed adaptive filters. • The weight update algorithm and convergence characteristics for the proposed adaptive filters are derived. - Abstract: Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

Low temperature properties of spin filter NbN/GdN/NbN Josephson junctions

Energy Technology Data Exchange (ETDEWEB)

Massarotti, D., E-mail: dmassarotti@na.infn.it [Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università di Napoli, via Roma 29, 81031 Aversa (CE) (Italy); CNR-SPIN UOS Napoli, Complesso Universitario di Monte Sant’Angelo, via Cinthia, 80126 Napoli (Italy); Caruso, R. [Dipartimento di Fisica, Università degli Studi di Napoli Federico II, Via Cinthia, 80126 Napoli (Italy); CNR-SPIN UOS Napoli, Complesso Universitario di Monte Sant’Angelo, via Cinthia, 80126 Napoli (Italy); Pal, A. [Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS (United Kingdom); Rotoli, G. [Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università di Napoli, via Roma 29, 81031 Aversa (CE) (Italy); Longobardi, L. [Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università di Napoli, via Roma 29, 81031 Aversa (CE) (Italy); American Physical Society, 1 Research Road, Ridge, New York 11961 (United States); Pepe, G.P. [Dipartimento di Fisica, Università degli Studi di Napoli Federico II, Via Cinthia, 80126 Napoli (Italy); CNR-SPIN UOS Napoli, Complesso Universitario di Monte Sant’Angelo, via Cinthia, 80126 Napoli (Italy); Blamire, M.G. [Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS (United Kingdom); Tafuri, F. [Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università di Napoli, via Roma 29, 81031 Aversa (CE) (Italy); CNR-SPIN UOS Napoli, Complesso Universitario di Monte Sant’Angelo, via Cinthia, 80126 Napoli (Italy)

2017-02-15

Highlights: • We study the phase dynamics of ferromagnetic NbN/GdN/NbN Josephson junctions. • The ferromagnetic insulator GdN barrier generates spin-filtering properties. • Spin filter junctions fall in the underdamped regime. • MQT occurs with the same phenomenology as in conventional Josephson junctions. • Dissipation is studied in a wide range of critical current density values. - Abstract: A ferromagnetic Josephson junction (JJ) represents a special class of hybrid system where different ordered phases meet and generate novel physics. In this work we report on the transport measurements of underdamped ferromagnetic NbN/GdN/NbN JJs at low temperatures. In these junctions the ferromagnetic insulator gadolinium nitride barrier generates spin-filtering properties and a dominant second harmonic component in the current-phase relation. These features make spin filter junctions quite interesting also in terms of fundamental studies on phase dynamics and dissipation. We discuss the fingerprints of spin filter JJs, through complementary transport measurements, and their implications on the phase dynamics, through standard measurements of switching current distributions. NbN/GdN/NbN JJs, where spin filter properties can be controllably tuned along with the critical current density (J{sub c}), turn to be a very relevant term of reference to understand phase dynamics and dissipation in an enlarged class of JJs, not necessarily falling in the standard tunnel limit characterized by low J{sub c} values.

Dosimetry and clinical implementation of dynamic wedge

International Nuclear Information System (INIS)

Klein, Eric E.; Low, Daniel A.; Meigooni, Ali S.; Purdy, James A.

1995-01-01

Purpose: Wedge-shaped isodoses are desired in a number of clinical situations. Physical wedge filters have provided nominal angled isodoses with dosimetric consequences of beam hardening, increased peripheral dosing, nonidealized gradients at deep depths, along with the practical consequences of filter handling and placement problems. Dynamic wedging uses a combination of a moving jaw and changing dose rate to achieve angled isodoses. The clinical implementation of dynamic wedge and an accompanying quality assurance program are discussed in detail. Methods and Materials: The accelerator at our facility has two photon energies (6 MV and 18 MV), currently with dynamic wedge angles of 15 deg. , 30 deg. , 45 deg. , and 60 deg. . The segmented treatment tables (STT) that drive the jaw in concert with a changing dose rate are unique for field sizes ranging from 4.0 cm to 20.0 cm in 05 cm steps, resulting in 256 STTs. Transmission wedge factors were measured for each STT with an ion chamber. Isodose profiles were accumulated with film after dose conversion. For treatment-planning purposes, d max orthogonal dose profiles were measured for open and dynamic fields. Physical filters were assigned empirically via the ratio of open and wedge profiles. Results: A nonlinear relationship with wedge factor and field size was found. The factors were found to be independent of the stationary field setting or second order blocking. Dynamic wedging provided more consistent gradients across the field compared with physical filters. Percent depth doses were found to be closer to open field. The created physical filters provided planned isodoses that closely resembled measured isodoses. Comparative isodose plans show improvement with dynamic wedging. Conclusions: Dynamic weding has practical and dosimetric advantages over physical filters. Table collisions with physical filters are alleviated. Treatment planning has been solved with an empirical solution. Dynamic wedge is a positive

Robotic fish tracking method based on suboptimal interval Kalman filter

Science.gov (United States)

Tong, Xiaohong; Tang, Chao

2017-11-01

Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

On a New Family of Kalman Filter Algorithms for Integrated Navigation

Science.gov (United States)

Mahboub, V.; Saadatseresht, M.; Ardalan, A. A.

2017-09-01

Here we present a review on a new family of Kalman filter algorithms which recently developed for integrated navigation. In particular it is useful for vision based navigation due to the type of data. Here we mainly focus on three algorithms namely weighted Total Kalman filter (WTKF), integrated Kalman filter (IKF) and constrained integrated Kalman filter (CIKF). The common characteristic of these algorithms is that they can consider the neglected random observed quantities which may appear in the dynamic model. Moreover, our approach makes use of condition equations and straightforward variance propagation rules. The WTKF algorithm can deal with problems with arbitrary weight matrixes. Both of the observation equations and system equations can be dynamic-errors-in-variables (DEIV) models in the IKF algorithms. In some problems a quadratic constraint may exist. They can be solved by CIKF algorithm. Finally, we compare four algorithms WTKF, IKF, CIKF and EKF in numerical examples.

Application of Consider Covariance to the Extended Kalman Filter

Science.gov (United States)

Lundberg, John B.

1996-01-01

The extended Kalman filter (EKF) is the basis for many applications of filtering theory to real-time problems where estimates of the state of a dynamical system are to be computed based upon some set of observations. The form of the EKF may vary somewhat from one application to another, but the fundamental principles are typically unchanged among these various applications. As is the case in many filtering applications, models of the dynamical system (differential equations describing the state variables) and models of the relationship between the observations and the state variables are created. These models typically employ a set of constants whose values are established my means of theory or experimental procedure. Since the estimates of the state are formed assuming that the models are perfect, any modeling errors will affect the accuracy of the computed estimates. Note that the modeling errors may be errors of commission (errors in terms included in the model) or omission (errors in terms excluded from the model). Consequently, it becomes imperative when evaluating the performance of real-time filters to evaluate the effect of modeling errors on the estimates of the state.

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering

Institute of Scientific and Technical Information of China (English)

FENG Yu-hu

2005-01-01

By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.

A comparative analysis of the categorization of multidimensional stimuli: I. Unidimensional classification does not necessarily imply analytic processing; evidence from pigeons (Columba livia), squirrels (Sciurus carolinensis), and humans (Homo sapiens).

Science.gov (United States)

Wills, A J; Lea, Stephen E G; Leaver, Lisa A; Osthaus, Britta; Ryan, Catriona M E; Suret, Mark B; Bryant, Catherine M L; Chapman, Sue J A; Millar, Louise

2009-11-01

Pigeons (Columba livia), gray squirrels (Sciurus carolinensis), and undergraduates (Homo sapiens) learned discrimination tasks involving multiple mutually redundant dimensions. First, pigeons and undergraduates learned conditional discriminations between stimuli composed of three spatially separated dimensions, after first learning to discriminate the individual elements of the stimuli. When subsequently tested with stimuli in which one of the dimensions took an anomalous value, the majority of both species categorized test stimuli by their overall similarity to training stimuli. However some individuals of both species categorized them according to a single dimension. In a second set of experiments, squirrels, pigeons, and undergraduates learned go/no-go discriminations using multiple simultaneous presentations of stimuli composed of three spatially integrated, highly salient dimensions. The tendency to categorize test stimuli including anomalous dimension values unidimensionally was higher than in the first set of experiments and did not differ significantly between species. The authors conclude that unidimensional categorization of multidimensional stimuli is not diagnostic for analytic cognitive processing, and that any differences between human's and pigeons' behavior in such tasks are not due to special features of avian visual cognition.

Damage Detection for Continuous Bridge Based on Static-Dynamic Condensation and Extended Kalman Filtering

Directory of Open Access Journals (Sweden)

Haoxiang He

2014-01-01

Full Text Available As an effective and classical method about physical parameter identification, extended Kalman filtering (EKF algorithm is widely used in structural damage identification, but the equations and solutions for the structure with bending deformation are not established based on EKF. The degrees of freedom about rotation can be eliminated by the static condensation method, and the dynamic condensation method considering Rayleigh damping is proposed in order to establish the equivalent and simplified modal based on complex finite element model such as continuous girder bridge. According to the requirement of bridge inspection and health monitoring, the online and convenient damage detection method based on EKF is presented. The impact excitation can be generated only on one location by one hammer actuator, and the signal in free vibration is analyzed. The deficiency that the complex excitation information is needed based on the traditional method is overcome. As a numerical example, a three-span continuous girder bridge is simulated, and the corresponding stiffness, the damage location and degree, and the damping parameter are identified accurately. It is verified that the method is suitable for the dynamic signal with high noise-signal ratio; the convergence speed is fast and this method is feasible for application.

Nonlinear control and filtering using differential flatness approaches applications to electromechanical systems

CERN Document Server

Rigatos, Gerasimos G

2015-01-01

This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of nonlinear adaptive controllers and nonlinear filters, using exact linearization based on differential flatness theory. The adaptive controllers obtained can be applied to a wide class of nonlinear systems with unknown dynamics, and assure reliable functioning of the control loop under uncertainty and varying operating conditions. The filters obtained outperform other nonlinear filters in terms of accuracy of estimation and computation speed. The bo...

Comparison of three nonlinear filters for fault detection in continuous glucose monitors.

Science.gov (United States)

Mahmoudi, Zeinab; Wendt, Sabrina Lyngbye; Boiroux, Dimitri; Hagdrup, Morten; Norgaard, Kirsten; Poulsen, Niels Kjolstad; Madsen, Henrik; Jorgensen, John Bagterp

2016-08-01

The purpose of this study is to compare the performance of three nonlinear filters in online drift detection of continuous glucose monitors. The nonlinear filters are the extended Kalman filter (EKF), the unscented Kalman filter (UKF), and the particle filter (PF). They are all based on a nonlinear model of the glucose-insulin dynamics in people with type 1 diabetes. Drift is modelled by a Gaussian random walk and is detected based on the statistical tests of the 90-min prediction residuals of the filters. The unscented Kalman filter had the highest average F score of 85.9%, and the smallest average detection delay of 84.1%, with the average detection sensitivity of 82.6%, and average specificity of 91.0%.

Kalman and particle filtering methods for full vehicle and tyre identification

Science.gov (United States)

Bogdanski, Karol; Best, Matthew C.

2018-05-01

This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators.

Identification and simulation for steam generator water level based on Kalman Filter

International Nuclear Information System (INIS)

Deng Chen; Zhang Qinshun

2008-01-01

In order to effectively control the water level of the steam generator (SG), this paper has set about the state-observer theory in modern control and put forward a method to detect the 'false water level' based on Kalman Filter. Kalman Filter is a efficient tool to estimate state-variable by measured value including noise. For heavy measurement noise of steam flow, constructing a 'false water level' observer by Kalman Filter could availably obtain state variable of 'false water level'. The simulation computing for the dynamics characteristic of nuclear SG water level process under several typically running power was implemented by employing the simulation model. The result shows that the simulation model accurately identifies the 'false water level' produced in the reverse thermal-dynamic effects of nuclear SG water level process. The simulation model can realize the precise analysis of dynamics characteristic for the nuclear SG water level process. It can provide a kind of new ideas for the 'false water level' detecting of SG. (authors)

The research of radar target tracking observed information linear filter method

Science.gov (United States)

Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

2018-05-01

Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

Extended Kalman filtering applied to a two-axis robotic arm with flexible links

Energy Technology Data Exchange (ETDEWEB)

Lertpiriyasuwat, V.; Berg, M.C.; Buffinton, K.W.

2000-03-01

An industrial robot today uses measurements of its joint positions and models of its kinematics and dynamics to estimate and control its end-effector position. Substantially better end-effector position estimation and control performance would be obtainable if direct measurements of its end-effector position were also used. The subject of this paper is extended Kalman filtering for precise estimation of the position of the end-effector of a robot using, in addition to the usual measurements of the joint positions, direct measurements of the end-effector position. The estimation performances of extended Kalman filters are compared in applications to a planar two-axis robotic arm with very flexible links. The comparisons shed new light on the dependence of extended Kalman filter estimation performance on the quality of the model of the arm dynamics that the extended Kalman filter operates with.

Observations of vector magnetic fields with a magneto-optic filter

Science.gov (United States)

Cacciani, Alessandro; Varsik, John; Zirin, Harold

1990-01-01

The use of the magnetooptic filter to observe solar magnetic fields in the potassium line at 7699 A is described. The filter has been used in the Big Bear videomagnetograph since October 23. It gives a high sensitivity and dynamic range for longitudnal magnetic fields and enables measurement of transverse magnetic fields using the sigma component. Examples of the observations are presented.

Aggregated filter-feeding consumers alter nutrient limitation: consequences for ecosystem and community dynamics.

Science.gov (United States)

Atkinson, Carla L; Vaughn, Caryn C; Forshay, Kenneth J; Cooper, Joshua T

2013-06-01

Nutrient cycling is a key process linking organisms in ecosystems. This is especially apparent in stream environments in which nutrients are taken up readily and cycled through the system in a downstream trajectory. Ecological stoichiometry predicts that biogeochemical cycles of different elements are interdependent because the organisms that drive these cycles require fixed ratios of nutrients. There is growing recognition that animals play an important role in biogeochemical cycling across ecosystems. In particular, dense aggregations of consumers can create biogeochemical hotspots in aquatic ecosystems via nutrient translocation. We predicted that filter-feeding freshwater mussels, which occur as speciose, high-biomass aggregates, would create biogeochemical hotspots in streams by altering nutrient limitation and algal dynamics. In a field study, we manipulated nitrogen and phosphorus using nutrient-diffusing substrates in areas with high and low mussel abundance, recorded algal growth and community composition, and determined in situ mussel excretion stoichiometry at 18 sites in three rivers (Kiamichi, Little, and Mountain Fork Rivers, south-central United States). Our results indicate that mussels greatly influence ecosystem processes by modifying the nutrients that limit primary productivity. Sites without mussels were N-limited with -26% higher relative abundances of N-fixing blue-green algae, while sites with high mussel densities were co-limited (N and P) and dominated by diatoms. These results corroborated the results of our excretion experiments; our path analysis indicated that mussel excretion has a strong influence on stream water column N:P. Due to the high N:P of mussel excretion, strict N-limitation was alleviated, and the system switched to being co-limited by both N and P. This shows that translocation of nutrients by mussel aggregations is important to nutrient dynamics and algal species composition in these rivers. Our study highlights the

Research on Kalman-filter based multisensor data fusion

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc.Various multisensor data fusion methods have been extensively investigated by researchers,of which Klaman filtering is one of the most important.Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown.states of a dynamic system,which has found widespread application in many areas.The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods.then a new method of state fusion is proposed.Finally the simulation results demonstrate the effectiveness of the introduced method.

A comparative study of Kalman filter and Linear Matrix Inequality based H infinity filter for SPND delay compensation

International Nuclear Information System (INIS)

Tamboli, P.K.; Duttagupta, Siddhartha P.; Roy, Kallol

2016-01-01

Highlights: • Derivation for delay compensation algorithm using recursive Kalman filter. • Derivation for delay compensation algorithm using Linear Matrix Inequality based H infinity filter. • Process modeling suitable for delay compensation. • Dynamic tuning of the delay compensation algorithm for both Kalman and H infinity filter. • Simulations and trade-off curve for Kalman and H infinity filter. - Abstract: This paper deals with delay compensation of vanadium Self Powered Neutron Detectors (SPNDs) using Linear Matrix Inequality (LMI) based H-infinity filtering method and compares the results with Kalman filtering method. The entire study is established upon the framework of neutron flux estimation in large core Pressurized Heavy Water Reactor (PHWR) in which delayed SPNDs such as vanadium SPNDs are used as in-core flux monitoring detectors. The use of vanadium SPNDs are limited to 3-D flux mapping despite of providing better Signal to Noise Ratio as compared to other prompt SPNDs, due to their small prompt component in the signal. The use of an appropriate delay compensation technique has been always considered to be an effective strategy to build a prompt and accurate estimate of the neutron flux. We also indicate the noise-response trade-off curve for both the techniques. Since all the delay compensation algorithms always suffer from noise amplification, we propose an efficient adaptive parameter tuning technique for improving performance of the filtering algorithm against noise in the measurement.

Comparison between 3D dynamics filter technique, field-in-field, electronic compensator in breast cancer; Comparacao entre tecnica 3D com filtro dinamico, field-in-field e compensacao eletronica para cancer de mama

Energy Technology Data Exchange (ETDEWEB)

Trindade, Cassia; Silva, Leonardo P.; Martins, Lais P.; Garcia, Paulo L.; Santos, Maira R.; Bastista, Delano V.S.; Vieira, Anna Myrian M.T.L.; Rocha, Igor M., E-mail: cassiatr@gmail.com [Instituto Nacional de Cancer (INCA), Rio de Janeiro, RJ (Brazil)

2012-12-15

The radiotherapy has been used in a wild scale in breast cancer treatment. With this high demand, new technologies have been developed to improve the dose distribution in the target while reducing the dose delivered in critical organs. In this study, performed with one clinical case, three planning were done for comparison: 3D technique with dynamic filter, 3D with field-in-field technique (forward-planned IMRT) and 3D technique using electronic compensator (ECOMP). The planning were done with a 6MV photon beam using the Eclipse software, version 8.6 (Varian Medical Systems). The PTV was drawn covering the whole breast and the critical organs were: the lung on the irradiated side, the heart, the contralateral breast and the anterior descending coronary artery (LAD). The planning using the compensator technique permitted more homogeneous dose distribution in the target volume. The V20 value of the lung on the irradiated side was 8,3% for the electronic compensator technique, 8,9% for the field-in-field technique and 8,2% for the dynamic filter technique. For the heart the dose range was 15.7 - 139.9 cGy, 16.3 - 148.4 cGy for the dynamic filter technique and 19.6 - 157.0 cGy for the field-in-field technique. The dose gradient was 11% with compensator electronic, 15% dynamic filter technique and 13% with field-in-field. The application of electronic technique in breast cancer treatment allows better dose distribution while reduces dose in critical organs, but in the same time requires a quality assurance. (author)

Sensorless Control of Electric Motors with Kalman Filters: Applications to Robotic and Industrial Systems

Directory of Open Access Journals (Sweden)

Gerasimos G. Rigatos

2011-12-01

Full Text Available The paper studies sensorless control for DC and induction motors, using Kalman Filtering techniques. First the case of a DC motor is considered and Kalman Filter-based control is implemented. Next the nonlinear model of a field-oriented induction motor is examined and the motor's angular velocity is estimated by an Extended Kalman Filter which processes measurements of the rotor's angle. Sensorless control of the induction motor is again implemented through feedback of the estimated state vector. Additionally, a state estimation-based control loop is implemented using the Unscented Kalman Filter. Moreover, state estimation-based control is developed for the induction motor model using a nonlinear flatness-based controller and the state estimation that is provided by the Extended Kalman Filter. Unlike field oriented control, in the latter approach there is no assumption about decoupling between the rotor speed dynamics and the magnetic flux dynamics. The efficiency of the Kalman Filter-based control schemes, for both the DC and induction motor models, is evaluated through simulation experiments.

Modeling Flow Past a Tilted Vena Cava Filter

Energy Technology Data Exchange (ETDEWEB)

Singer, M A; Wang, S L

2009-06-29

Inferior vena cava filters are medical devices used to prevent pulmonary embolism (PE) from deep vein thrombosis. In particular, retrievable filters are well-suited for patients who are unresponsive to anticoagulation therapy and whose risk of PE decreased with time. The goal of this work is to use computational fluid dynamics to evaluate the flow past an unoccluded and partially occluded Celect inferior vena cava filter. In particular, the hemodynamic response to thrombus volume and filter tilt is examined, and the results are compared with flow conditions that are known to be thrombogenic. A computer model of the filter inside a model vena cava is constructed using high resolution digital photographs and methods of computer aided design. The models are parameterized using the Overture software framework, and a collection of overlapping grids is constructed to discretize the flow domain. The incompressible Navier-Stokes equations are solved, and the characteristics of the flow (i.e., velocity contours and wall shear stresses) are computed. The volume of stagnant and recirculating flow increases with thrombus volume. In addition, as the filter increases tilt, the cava wall adjacent to the tilted filter is subjected to low velocity flow that gives rise to regions of low wall shear stress. The results demonstrate the ease of IVC filter modeling with the Overture software framework. Flow conditions caused by the tilted Celect filter may elevate the risk of intrafilter thrombosis and facilitate vascular remodeling. This latter condition also increases the risk of penetration and potential incorporation of the hook of the filter into the vena caval wall, thereby complicating filter retrieval. Consequently, severe tilt at the time of filter deployment may warrant early clinical intervention.

Sensory Pollution from Bag Filters, Carbon Filters and Combinations

DEFF Research Database (Denmark)

Bekö, Gabriel; Clausen, Geo; Weschler, Charles J.

2008-01-01

by an upstream pre-filter (changed monthly), an EU7 filter protected by an upstream activated carbon (AC) filter, and EU7 filters with an AC filter either downstream or both upstream and downstream. In addition, two types of stand-alone combination filters were evaluated: a bag-type fiberglass filter...... that contained AC and a synthetic fiber cartridge filter that contained AC. Air that had passed through used filters was most acceptable for those sets in which an AC filter was used downstream of the particle filter. Comparable air quality was achieved with the stand-alone bag filter that contained AC...

A computational fluid dynamics simulation of the hypersonic flight of the Pegasus(TM) vehicle using an artificial viscosity model and a nonlinear filtering method. M.S. Thesis

Science.gov (United States)

Mendoza, John Cadiz

1995-01-01

The computational fluid dynamics code, PARC3D, is tested to see if its use of non-physical artificial dissipation affects the accuracy of its results. This is accomplished by simulating a shock-laminar boundary layer interaction and several hypersonic flight conditions of the Pegasus(TM) launch vehicle using full artificial dissipation, low artificial dissipation, and the Engquist filter. Before the filter is applied to the PARC3D code, it is validated in one-dimensional and two-dimensional form in a MacCormack scheme against the Riemann and convergent duct problem. For this explicit scheme, the filter shows great improvements in accuracy and computational time as opposed to the nonfiltered solutions. However, for the implicit PARC3D code it is found that the best estimate of the Pegasus experimental heat fluxes and surface pressures is the simulation utilizing low artificial dissipation and no filter. The filter does improve accuracy over the artificially dissipative case but at a computational expense greater than that achieved by the low artificial dissipation case which has no computational time penalty and shows better results. For the shock-boundary layer simulation, the filter does well in terms of accuracy for a strong impingement shock but not as well for weaker shock strengths. Furthermore, for the latter problem the filter reduces the required computational time to convergence by 18.7 percent.

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

Science.gov (United States)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

Collaborative Filtering Recommendation on Users' Interest Sequences.

Directory of Open Access Journals (Sweden)

Weijie Cheng

Full Text Available As an important factor for improving recommendations, time information has been introduced to model users' dynamic preferences in many papers. However, the sequence of users' behaviour is rarely studied in recommender systems. Due to the users' unique behavior evolution patterns and personalized interest transitions among items, users' similarity in sequential dimension should be introduced to further distinguish users' preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users' interest sequences (IS that rank users' ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users' longest common sub-IS (LCSIS and the count of users' total common sub-IS (ACSIS. Then, these semantics are utilized to obtain users' IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users' preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction.

Collaborative Filtering Recommendation on Users' Interest Sequences.

Science.gov (United States)

Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

2016-01-01

As an important factor for improving recommendations, time information has been introduced to model users' dynamic preferences in many papers. However, the sequence of users' behaviour is rarely studied in recommender systems. Due to the users' unique behavior evolution patterns and personalized interest transitions among items, users' similarity in sequential dimension should be introduced to further distinguish users' preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users' interest sequences (IS) that rank users' ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users' longest common sub-IS (LCSIS) and the count of users' total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users' IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users' preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction.

Collaborative Filtering Recommendation on Users’ Interest Sequences

Science.gov (United States)

Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

2016-01-01

As an important factor for improving recommendations, time information has been introduced to model users’ dynamic preferences in many papers. However, the sequence of users’ behaviour is rarely studied in recommender systems. Due to the users’ unique behavior evolution patterns and personalized interest transitions among items, users’ similarity in sequential dimension should be introduced to further distinguish users’ preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users’ interest sequences (IS) that rank users’ ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users’ longest common sub-IS (LCSIS) and the count of users’ total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users’ IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users’ preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction. PMID:27195787

US images encoding envelope amplitude following narrow band filtering

International Nuclear Information System (INIS)

Sommer, F.G.; Stern, R.A.; Chen, H.S.

1986-01-01

Ultrasonic waveform data from phantoms having differing scattering characteristics and from normal and cirrhotic human liver in vivo were recorded within a standardized dynamic range and filtered with narrow band filters either above or below the mean recorded ultrasonic center frequency. Images created by mapping the amplitudes of received ultrasound following such filtration permitted dramatic differentiation, not discernible in conventional US images, of phantoms having differing scattering characteristics, and of normal and cirrhotic human livers

Design and control of an LCL-filter-based three-phase active rectifier

DEFF Research Database (Denmark)

Liserre, Marco; Blaabjerg, Frede; Hansen, Steffan

2005-01-01

This paper proposes a step-by-step procedure for designing the LCL filter of a front-end three-phase active rectifier. The primary goal is to reduce the switching frequency ripple at a reasonable cost, while at the same time achieving a high-performance front-end rectifier (as characterized...... by a rapid dynamic response and good stability margin). An example LCL filter design is reported and a filter has been built and tested using the values obtained from this design. The experimental results demonstrate the performance of the design procedure both for the LCL filter and for the rectifier...... a powerful tool to design an LCL-filter-based active rectifier while avoiding trial-and-error procedures that can result in having to build several filter prototypes....

Switched Current Micropower 4th Order Lowpass / Highpass Filter

DEFF Research Database (Denmark)

Bogason, Gudmundur

1993-01-01

This paper describes a 4th order lowpass / highpass Butterworth filter implemented in switched current technique. The filter has been designed for low power operation. A prototype implementation has been made and it operates with supply voltages down to 2V and with a total supply current of 211Â......¿A at a sampling rate of 50kHz. The chip includes a clock-generator, three current-followers, sample-and-hold and two 4th order filters. The sampling frequency is restricted to approximately 50kHz and the ratio between sampling frequency and cutoff frequency is 12.5. The dynamic-range was found to be 49d...

Thermally controlled femtosecond pulse shaping using metasurface based optical filters

Science.gov (United States)

Rahimi, Eesa; Şendur, Kürşat

2018-02-01

Shaping of the temporal distribution of the ultrashort pulses, compensation of pulse deformations due to phase shift in transmission and amplification are of interest in various optical applications. To address these problems, in this study, we have demonstrated an ultra-thin reconfigurable localized surface plasmon (LSP) band-stop optical filter driven by insulator-metal phase transition of vanadium dioxide. A Joule heating mechanism is proposed to control the thermal phase transition of the material. The resulting permittivity variation of vanadium dioxide tailors spectral response of the transmitted pulse from the stack. Depending on how the pulse's spectrum is located with respect to the resonance of the band-stop filter, the thin film stack can dynamically compress/expand the output pulse span up to 20% or shift its phase up to 360°. Multi-stacked filters have shown the ability to dynamically compensate input carrier frequency shifts and pulse span variations besides their higher span expansion rates.

Thermally controlled femtosecond pulse shaping using metasurface based optical filters

Directory of Open Access Journals (Sweden)

Rahimi Eesa

2018-02-01

Full Text Available Shaping of the temporal distribution of the ultrashort pulses, compensation of pulse deformations due to phase shift in transmission and amplification are of interest in various optical applications. To address these problems, in this study, we have demonstrated an ultra-thin reconfigurable localized surface plasmon (LSP band-stop optical filter driven by insulator-metal phase transition of vanadium dioxide. A Joule heating mechanism is proposed to control the thermal phase transition of the material. The resulting permittivity variation of vanadium dioxide tailors spectral response of the transmitted pulse from the stack. Depending on how the pulse’s spectrum is located with respect to the resonance of the band-stop filter, the thin film stack can dynamically compress/expand the output pulse span up to 20% or shift its phase up to 360°. Multi-stacked filters have shown the ability to dynamically compensate input carrier frequency shifts and pulse span variations besides their higher span expansion rates.

Realisation of low-voltage square-root-domain all-pass filters

Directory of Open Access Journals (Sweden)

Farooq A. Khanday

2013-10-01

Full Text Available Novel l ow-voltage first-order and second-order square-root-domain all-pass filters derived systematically by means of transfer function decomposition and state -space synthesis techniques are proposed. The employment of only a few geometric-mean cells and grounded capacitors permits the circuits to absorb shunt parasitic capacitances, which is desirable for production in monolithic form . The circuits enjoy the features of electronic adjustment of frequency characteristics, wider dynamic range and low-voltage environment operation. The filters are employed to design high-order all-pass filters using cascade approach. First-order low-pass and second-order band-pass filters, being the inherited building blocks of the proposed low-order all-pass filters are also discussed. The behaviour of the filters is evaluated through simulations using Taiwan semiconductor manufacturing company 0.25 μm level-3 complementary metal oxide semiconductor process parameters, where the most important performance factors are considered.

A decentralized square root information filter/smoother

Science.gov (United States)

Bierman, G. J.; Belzer, M. R.

1985-01-01

A number of developments has recently led to a considerable interest in the decentralization of linear least squares estimators. The developments are partly related to the impending emergence of VLSI technology, the realization of parallel processing, and the need for algorithmic ways to speed the solution of dynamically decoupled, high dimensional estimation problems. A new method is presented for combining Square Root Information Filters (SRIF) estimates obtained from independent data sets. The new method involves an orthogonal transformation, and an information matrix filter 'homework' problem discussed by Schweppe (1973) is generalized. The employed SRIF orthogonal transformation methodology has been described by Bierman (1977).

Dynamic Compensation for Two-Axis Robot Wrist Force Sensors

Directory of Open Access Journals (Sweden)

Junqing Ma

2013-01-01

Full Text Available To improve the dynamic characteristic of two-axis force sensors, a dynamic compensation method is proposed. The two-axis force sensor system is assumed to be a first-order system. The operation frequency of the system is expanded by a digital filter with backward difference network. To filter high-frequency noises, a low-pass filter is added after the dynamic compensation network. To avoid overcompensation, parameters of the proposed dynamic compensation method are defined by trial and error. Step response methods are utilized in dynamic calibration experiments. Compared to experiment data without compensation, the response time of the dynamic compensated data is reduced by 30%~40%. Experiments results demonstrate the effectiveness of our method.

Dynamics of nonlinear feedback control.

Science.gov (United States)

Snippe, H P; van Hateren, J H

2007-05-01

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path.

Corrosive environment tester for filter media

International Nuclear Information System (INIS)

Petit, G.S.; Weber, C.W.; Keinberger, C.A.; Rivers, R.D.

1977-02-01

Two continuous dynamic systems have been designed and fabricated for testing filter media in humid, corrosive environments--one for fluorine or fluoride exposures, and the other for nitrogen dioxide exposures. The tester using fluorine or fluoride atmospheres was constructed of nickel and the one using nitrogen dioxide was fabricated of stainless steel. Other corrosive gases could be used with the appropriate choice of system. For example, chlorine or hydrogen chloride could be used in the system fabricated of nickel, and sulfur dioxides or ammonia could be used in the stainless steel testing apparatus. Each tester is comprised of four equivalent dynamic systems designed for diluting a corrosive reagent with dry air, then with humidified air to provide a humid-corrosive environment for filter media testing. Auxiliary equipment includes a water injection system, corrosive reagent supply systems, and an automatic pressure differential (ΔP) monitoring and recording system. The testers are relatively maintenance-free and have operated continuously for periods as long as 96 h without requiring any attention, during total exposures of materials exceeding 600 h

Conduction properties of KcsA measured using brownian dynamics with flexible carbonyl groups in the selectivity filter.

Science.gov (United States)

Chung, Shin-Ho; Corry, Ben

2007-07-01

In the narrow segment of an ion conducting pathway, it is likely that a permeating ion influences the positions of the nearby atoms that carry partial or full electronic charges. Here we introduce a method of incorporating the motion of charged atoms lining the pore into Brownian dynamics simulations of ion conduction. The movements of the carbonyl groups in the selectivity filter of the KcsA channel are calculated explicitly, allowing their bond lengths, bond angles, and dihedral angels to change in response to the forces acting upon them. By systematically changing the coefficients of bond stretching and of angle bending, the carbon and oxygen atoms can be made to fluctuate from their fixed positions by varying mean distances. We show that incorporating carbonyl motion in this way does not alter the mechanism of ion conduction and only has a small influence on the computed current. The slope conductance of the channel increases by approximately 25% when the root mean-square fluctuations of the carbonyl groups are increased from 0.01 to 0.61 A. The energy profiles and the number of resident ions in the channel remain unchanged. The method we utilized here can be extended to allow the movement of glutamate or aspartate side chains lining the selectivity filters of other ionic channels.

Comparison of Three Nonlinear Filters for Fault Detection in Continuous Glucose Monitors

DEFF Research Database (Denmark)

Mahmoudi, Zeinab; Wendt, Sabrina Lyngbye; Boiroux, Dimitri

2016-01-01

model of the glucose-insulin dynamics in people with type 1 diabetes. Drift is modelled by a Gaussian random walk and is detected based on the statistical tests of the 90-min prediction residuals of the filters. The unscented Kalman filter had the highest average F score of 85.9%, and the smallest...

Filter arrays

Science.gov (United States)

Page, Ralph H.; Doty, Patrick F.

2017-08-01

The various technologies presented herein relate to a tiled filter array that can be used in connection with performance of spatial sampling of optical signals. The filter array comprises filter tiles, wherein a first plurality of filter tiles are formed from a first material, the first material being configured such that only photons having wavelengths in a first wavelength band pass therethrough. A second plurality of filter tiles is formed from a second material, the second material being configured such that only photons having wavelengths in a second wavelength band pass therethrough. The first plurality of filter tiles and the second plurality of filter tiles can be interspersed to form the filter array comprising an alternating arrangement of first filter tiles and second filter tiles.

Design and fabrication of broadband rugate filter

International Nuclear Information System (INIS)

Zhang Jun-Chao; Fang Ming; Shao Yu-Chuan; Jin Yun-Xia; He Hong-Bo

2012-01-01

The design and the deposition of a rugate filter for broadband applications are discussed. The bandwidth is extended by increasing the rugate period continuously with depth. The width and the smoothness of the reflection band with the distribution of the periods are investigated. The improvement of the steepness of the stopband edges and the suppression of the side lobes in the transmission zone are realized by adding two apodized rugate structures with fixed periods at the external broadband rugate filter interfaces. The rapidly alternating deposition technology is used to fabricate a rugate filter sample. The measured transmission spectrum with a reflection bandwidth of approximately 505 nm is close to that of the designed broadband rugate filter except a transmittance peak in the stopband. Based on the analysis of the cross-sectional scanning electron microscopic image of the sample, it is found that the transmission peak is most likely to be caused by the instability of the deposition rate. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Adsorption of Chloroform by the Rapid Response System Filter

National Research Council Canada - National Science Library

Karwacki, Christopher

1997-01-01

Adsorption equilibria and dynamic breakthrough data were measured to determine the adsorption capacity and effect of purge air on the desorption of chloroform from activated carbon simulating the Rapid Response System (RRS) filter...

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

Science.gov (United States)

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-01-01

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

Nonlinear Control of Back-to-Back VSC-HVDC System via Command-Filter Backstepping

Directory of Open Access Journals (Sweden)

Jie Huang

2017-01-01

Full Text Available This paper proposed a command-filtered backstepping controller to improve the dynamic performance of back-to-back voltage-source-converter high voltage direct current (BTB VSC-HVDC. First, the principle and model of BTB VSC-HVDC in abc and d-q frame are described. Then, backstepping method is applied to design a controller to maintain the voltage balance and realize coordinated control of active and reactive power. Meanwhile, command filter is introduced to deal with the problem of input saturation and explosion of complexity in conventional backstepping, and a filter compensation signal is designed to diminish the adverse effects caused by the command filter. Next, the stability and convergence of the whole system are proved via the Lyapunov theorem of asymptotic stability. Finally, simulation results are given to demonstrate that proposed controller has a better dynamic performance and stronger robustness compared to the traditional PID algorithm, which also proves the effectiveness and possibility of the designed controller.

Nonlinear Kalman Filtering in Affine Term Structure Models

DEFF Research Database (Denmark)

Christoffersen, Peter; Dorion, Christian; Jacobs, Kris

When the relationship between security prices and state variables in dynamic term structure models is nonlinear, existing studies usually linearize this relationship because nonlinear fi…ltering is computationally demanding. We conduct an extensive investigation of this linearization and analyze...... the potential of the unscented Kalman …filter to properly capture nonlinearities. To illustrate the advantages of the unscented Kalman …filter, we analyze the cross section of swap rates, which are relatively simple non-linear instruments, and cap prices, which are highly nonlinear in the states. An extensive...

Efficient Hardware Implementation For Fingerprint Image Enhancement Using Anisotropic Gaussian Filter.

Science.gov (United States)

Khan, Tariq Mahmood; Bailey, Donald G; Khan, Mohammad A U; Kong, Yinan

2017-05-01

A real-time image filtering technique is proposed which could result in faster implementation for fingerprint image enhancement. One major hurdle associated with fingerprint filtering techniques is the expensive nature of their hardware implementations. To circumvent this, a modified anisotropic Gaussian filter is efficiently adopted in hardware by decomposing the filter into two orthogonal Gaussians and an oriented line Gaussian. An architecture is developed for dynamically controlling the orientation of the line Gaussian filter. To further improve the performance of the filter, the input image is homogenized by a local image normalization. In the proposed structure, for a middle-range reconfigurable FPGA, both parallel compute-intensive and real-time demands were achieved. We manage to efficiently speed up the image-processing time and improve the resource utilization of the FPGA. Test results show an improved speed for its hardware architecture while maintaining reasonable enhancement benchmarks.

Analysis of piezoelectric energy harvester under modulated and filtered white Gaussian noise

Science.gov (United States)

Quaranta, Giuseppe; Trentadue, Francesco; Maruccio, Claudio; Marano, Giuseppe C.

2018-05-01

This paper proposes a comprehensive method for the electromechanical probabilistic analysis of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN) at the base. Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN, which is filtered through the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with a concentrated mass at the free-end, and its global behavior is approximated by the fundamental vibration mode (which is tuned with the dominant frequency of the dynamic input). A resistive electrical load is considered in the circuit. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original and efficient semi-analytical procedure is proposed to estimate mean and standard deviation of the electrical energy extracted from the piezoelectric layers.

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Welch, Gregory Francis [UNC-Chapel Hill/University of Central Florida; Zhang, Jinghe [UNC-Chapel Hill/Virginia Tech

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuities caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.

Digital Simulation of a Hybrid Active Filter - An Active Filter in Series with a Shunt Passive Filter

OpenAIRE

Sitaram, Mahesh I; Padiyar, KR; Ramanarayanan, V

1998-01-01

Active filters have long been in use for the filtering of power system load harmonics. In this paper, the digital simulation results of a hybrid active power filter system for a rectifier load are presented. The active filter is used for filtering higher order harmonics as the dominant harmonics are filtered by the passive filter. This reduces the rating of the active filter significantly. The DC capacitor voltage of the active filter is controlled using a PI controller.

Laboratory measurement of secondary pollutant yields from ozone reaction with HVAC filters

International Nuclear Information System (INIS)

Destaillats, Hugo; Chen, Wenhao; Apte, Michael; Li, Nuan; Spears, Michael; Almosni, Jeremie; Zhang, Jianshun Jensen; Fisk, William J.

2009-01-01

We used Proton Transfer Reaction - Mass Spectrometry (PTR-MS) and conventional sampling methods to monitor and identify trace level organic pollutants formed in heterogeneous reactions between ozone and HVAC filters in real time. Experiments were carried out using a bench-scale flow tube reactor operating with dry air and humidified air (50% RH), at realistically high ozone concentrations (150 ppbv). We explored different filter media (i.e., fiberglass and cotton/polyester blends) and different particle loadings (i.e., clean filter and filters loaded with particles for 3 months at the Lawrence Berkeley National Laboratory and the Port of Oakland, CA). Detailed emission dynamics of very low levels of certain organic pollutants from filter media upon ozone exposure in the presence of moisture have been obtained and analyzed.

Multirate Digital Filters Based on FPGA and Its Applications

International Nuclear Information System (INIS)

Sharaf El-Din, R.M.A.

2013-01-01

Digital Signal Processing (DSP) is one of the fastest growing techniques in the electronics industry. It is used in a wide range of application fields such as, telecommunications, data communications, image enhancement and processing, video signals, digital TV broadcasting, and voice synthesis and recognition. Field Programmable Gate Array (FPGA) offers good solution for addressing the needs of high performance DSP systems. The focus of this thesis is on one of the basic DSP functions, namely filtering signals to remove unwanted frequency bands. Multi rate Digital Filters (MDFs) are the main theme here. Theory and implementation of MDF, as a special class of digital filters, will be discussed. Multi rate digital filters represent a class of digital filters having a number of attractive features like, low requirements for the coefficient word lengths, significant saving in computation and storage requirements results in a significant reduction in its dynamic power consumption. This thesis introduces an efficient FPGA realization of a multi rate decimation filter with narrow pass-band and narrow transition band to reduce the frequency sample rate by factor of 64 for noise thermometer applications. The proposed multi rate decimation filter is composed of three stages; the first stage is a Cascaded Integrator Comb (CIC) decimation filter, the second stage is a two-coefficient Half-Band (HB) filter and the last stage is a sharper transition HB filter. The frequency responses of individual stages as well as the overall filter response have been demonstrated with full simulation using MATLAB. The design and implementation of the proposed MDF on FPGA (XILINX Virtex XCV800 BG432-4), using VHSIC Hardware Description Language (VHDL), has been introduced. The implementation areas of the proposed filter stages are compared. Using CIC-HB technique saves 18% of the design area, compared to using six stages HB decimation filters.

Neural network training by Kalman filtering in process system monitoring

International Nuclear Information System (INIS)

Ciftcioglu, Oe.

1996-03-01

Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

A 10.7 MHz CMOS SC radio IF filter using orthogonal hardware modulation

NARCIS (Netherlands)

Quinn, P.J.; Hartingsveldt, van K.; Roermund, van A.H.M.

2000-01-01

FM radio receivers require an IF filter for channel selection, customarily set at an IF center frequency of 10.7 MHz. Up until now, the limitations of integrated radio selectivity filters in terms of power dissipation, dynamic range, and cost are such that it is still required to use an external

Volterra Filtering for ADC Error Correction

Directory of Open Access Journals (Sweden)

J. Saliga

2001-09-01

Full Text Available Dynamic non-linearity of analog-to-digital converters (ADCcontributes significantly to the distortion of digitized signals. Thispaper introduces a new effective method for compensation such adistortion based on application of Volterra filtering. Considering ana-priori error model of ADC allows finding an efficient inverseVolterra model for error correction. Efficiency of proposed method isdemonstrated on experimental results.

A Kalman Filtering Perspective for Multiatlas Segmentation*

Science.gov (United States)

Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S.; Bouix, Sylvain; Tannenbaum, Allen

2016-01-01

In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity—neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy. PMID:26807162

Kalman filtering state of charge estimation for battery management system based on a stochastic fuzzy neural network battery model

International Nuclear Information System (INIS)

Xu Long; Wang Junping; Chen Quanshi

2012-01-01

Highlights: ► A novel extended Kalman Filtering SOC estimation method based on a stochastic fuzzy neural network (SFNN) battery model is proposed. ► The SFNN which has filtering effect on noisy input can model the battery nonlinear dynamic with high accuracy. ► A robust parameter learning algorithm for SFNN is studied so that the parameters can converge to its true value with noisy data. ► The maximum SOC estimation error based on the proposed method is 0.6%. - Abstract: Extended Kalman filtering is an intelligent and optimal means for estimating the state of a dynamic system. In order to use extended Kalman filtering to estimate the state of charge (SOC), we require a mathematical model that can accurately capture the dynamics of battery pack. In this paper, we propose a stochastic fuzzy neural network (SFNN) instead of the traditional neural network that has filtering effect on noisy input to model the battery nonlinear dynamic. Then, the paper studies the extended Kalman filtering SOC estimation method based on a SFNN model. The modeling test is realized on an 80 Ah Ni/MH battery pack and the Federal Urban Driving Schedule (FUDS) cycle is used to verify the SOC estimation method. The maximum SOC estimation error is 0.6% compared with the real SOC obtained from the discharging test.

Non-stationary reconstruction for dynamic fluorescence molecular tomography with extended kalman filter.

Science.gov (United States)

Liu, Xin; Wang, Hongkai; Yan, Zhuangzhi

2016-11-01

Dynamic fluorescence molecular tomography (FMT) plays an important role in drug delivery research. However, the majority of current reconstruction methods focus on solving the stationary FMT problems. If the stationary reconstruction methods are applied to the time-varying fluorescence measurements, the reconstructed results may suffer from a high level of artifacts. In addition, based on the stationary methods, only one tomographic image can be obtained after scanning one circle projection data. As a result, the movement of fluorophore in imaged object may not be detected due to the relative long data acquisition time (typically >1 min). In this paper, we apply extended kalman filter (EKF) technique to solve the non-stationary fluorescence tomography problem. Especially, to improve the EKF reconstruction performance, the generalized inverse of kalman gain is calculated by a second-order iterative method. The numerical simulation, phantom, and in vivo experiments are performed to evaluate the performance of the method. The experimental results indicate that by using the proposed EKF-based second-order iterative (EKF-SOI) method, we cannot only clearly resolve the time-varying distributions of fluorophore within imaged object, but also greatly improve the reconstruction time resolution (~2.5 sec/frame) which makes it possible to detect the movement of fluorophore during the imaging processes.

Filter assembly for metallic and intermetallic tube filters

Science.gov (United States)

Alvin, Mary Anne; Lippert, Thomas E.; Bruck, Gerald J.; Smeltzer, Eugene E.

2001-01-01

A filter assembly (60) for holding a filter element (28) within a hot gas cleanup system pressure vessel is provided, containing: a filter housing (62), said filter housing having a certain axial length and having a peripheral sidewall, said sidewall defining an interior chamber (66); a one piece, all metal, fail-safe/regenerator device (68) within the interior chamber (66) of the filter housing (62) and/or extending beyond the axial length of the filter housing, said device containing an outward extending radial flange (71) within the filter housing for seating an essential seal (70), the device also having heat transfer media (72) disposed inside and screens (80) for particulate removal; one compliant gasket (70) positioned next to and above the outward extending radial flange of the fail-safe/regenerator device; and a porous metallic corrosion resistant superalloy type filter element body welded at the bottom of the metal fail-safe/regenerator device.

Tracking the business cycle of the Euro area: A multivariate model-based band-pass filter

NARCIS (Netherlands)

Azevedo, J.M.; Koopman, S.J.; Rua, A.

2006-01-01

This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition model. The underlying multivariate dynamic factor model relies on specific formulations for trend and cycle components and produces smooth business cycle indicators with bandpass filter properties.

Statistically-Efficient Filtering in Impulsive Environments: Weighted Myriad Filters

Directory of Open Access Journals (Sweden)

Juan G. Gonzalez

2002-01-01

Full Text Available Linear filtering theory has been largely motivated by the characteristics of Gaussian signals. In the same manner, the proposed Myriad Filtering methods are motivated by the need for a flexible filter class with high statistical efficiency in non-Gaussian impulsive environments that can appear in practice. Myriad filters have a solid theoretical basis, are inherently more powerful than median filters, and are very general, subsuming traditional linear FIR filters. The foundation of the proposed filtering algorithms lies in the definition of the myriad as a tunable estimator of location derived from the theory of robust statistics. We prove several fundamental properties of this estimator and show its optimality in practical impulsive models such as the α-stable and generalized-t. We then extend the myriad estimation framework to allow the use of weights. In the same way as linear FIR filters become a powerful generalization of the mean filter, filters based on running myriads reach all of their potential when a weighting scheme is utilized. We derive the “normal” equations for the optimal myriad filter, and introduce a suboptimal methodology for filter tuning and design. The strong potential of myriad filtering and estimation in impulsive environments is illustrated with several examples.

Filter material charging apparatus for filter assembly for radioactive contaminants

International Nuclear Information System (INIS)

Goldsmith, J.M.; O'Nan, A. Jr.

1977-01-01

A filter charging apparatus for a filter assembly is described. The filter assembly includes a housing with at least one filter bed therein and the filter charging apparatus for adding filter material to the filter assembly includes a tank with an opening therein, the tank opening being disposed in flow communication with opposed first and second conduit means, the first conduit means being in flow communication with the filter assembly housing and the second conduit means being in flow communication with a blower means. Upon activation of the blower means, the blower means pneumatically conveys the filter material from the tank to the filter housing

The Kalman Filter Revisited Using Maximum Relative Entropy

Directory of Open Access Journals (Sweden)

Adom Giffin

2014-02-01

Full Text Available In 1960, Rudolf E. Kalman created what is known as the Kalman filter, which is a way to estimate unknown variables from noisy measurements. The algorithm follows the logic that if the previous state of the system is known, it could be used as the best guess for the current state. This information is first applied a priori to any measurement by using it in the underlying dynamics of the system. Second, measurements of the unknown variables are taken. These two pieces of information are taken into account to determine the current state of the system. Bayesian inference is specifically designed to accommodate the problem of updating what we think of the world based on partial or uncertain information. In this paper, we present a derivation of the general Bayesian filter, then adapt it for Markov systems. A simple example is shown for pedagogical purposes. We also show that by using the Kalman assumptions or “constraints”, we can arrive at the Kalman filter using the method of maximum (relative entropy (MrE, which goes beyond Bayesian methods. Finally, we derive a generalized, nonlinear filter using MrE, where the original Kalman Filter is a special case. We further show that the variable relationship can be any function, and thus, approximations, such as the extended Kalman filter, the unscented Kalman filter and other Kalman variants are special cases as well.

Design of Filter for a Class of Switched Linear Neutral Systems

Directory of Open Access Journals (Sweden)

Caiyun Wu

2013-01-01

Full Text Available This paper is concerned with the filtering problem for a class of switched linear neutral systems with time-varying delays. The time-varying delays appear not only in the state but also in the state derivatives. Based on the average dwell time approach and the piecewise Lyapunov functional technique, sufficient conditions are proposed for the exponential stability of the filtering error dynamic system. Then, the corresponding solvability condition for a desired filter satisfying a weighted performance is established. All the conditions obtained are delay-dependent. Finally, two numerical examples are given to illustrate the effectiveness of the proposed theory.

External modes in quantum dot light emitting diode with filtered optical feedback

International Nuclear Information System (INIS)

Al Husseini, Hussein B.; Al Naimee, Kais A.; Al-Khursan, Amin H.; Khedir, Ali. H.

2016-01-01

This research reports a theoretical investigation on the role of filtered optical feedback (FOF) in the quantum dot light emitting diode (QD-LED). The underlying dynamics is affected by a sidle node, which returns to an elliptical shape when the wetting layer (WL) is neglected. Both filter width and time delay change the appearance of different dynamics (chaotic and mixed mode oscillations, MMOs). The results agree with the experimental observations. Here, the fixed point analysis for QDs was done for the first time. For QD-LED with FOF, the system transits from the coherence collapse case in conventional optical feedback to a coherent case with a filtered mode in FOF. It was found that the WL washes out the modes which is an unexpected result. This may attributed to the longer capture time of WL compared with that between QD states. Thus, WL reduces the chaotic behavior.

Optimization of internet content filtering-Combined with KNN and OCAT algorithms

Science.gov (United States)

Guo, Tianze; Wu, Lingjing; Liu, Jiaming

2018-04-01

The face of the status quo that rampant illegal content in the Internet, the result of traditional way to filter information, keyword recognition and manual screening, is getting worse. Based on this, this paper uses OCAT algorithm nested by KNN classification algorithm to construct a corpus training library that can dynamically learn and update, which can be improved on the filter corpus for constantly updated illegal content of the network, including text and pictures, and thus can better filter and investigate illegal content and its source. After that, the research direction will focus on the simplified updating of recognition and comparison algorithms and the optimization of the corpus learning ability in order to improve the efficiency of filtering, save time and resources.

A compact quadrupole ion filter for helium detection

International Nuclear Information System (INIS)

Pereira, E.B.

1981-01-01

A compact quadrupole ion filter was conceived and constructed for optimum performance at the mass four region of the mass spectra. It was primarely designed for geological applications in the measurements of helium of soil-gases. The whole ion filter structure is 15 cm long by 3.5 cm diameter, including ion source and collecting plate. The sensitivity to helium is of the order of 10 - 2 A.torr - 1 measured at a total pressure of 6x10 - 6 torr and resolution 6. The system can be easily adapted to work as a dynamic residual gas analyser for other purposes. (Author) [pt

Observation Quality Control with a Robust Ensemble Kalman Filter

KAUST Repository

Roh, Soojin

2013-12-01

Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.

Observation Quality Control with a Robust Ensemble Kalman Filter

KAUST Repository

Roh, Soojin; Genton, Marc G.; Jun, Mikyoung; Szunyogh, Istvan; Hoteit, Ibrahim

2013-01-01

Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.

Estimation of aircraft aerodynamic derivatives using Extended Kalman Filter

OpenAIRE

Curvo, M.

2000-01-01

Design of flight control laws, verification of performance predictions, and the implementation of flight simulations are tasks that require a mathematical model of the aircraft dynamics. The dynamical models are characterized by coefficients (aerodynamic derivatives) whose values must be determined from flight tests. This work outlines the use of the Extended Kalman Filter (EKF) in obtaining the aerodynamic derivatives of an aircraft. The EKF shows several advantages over the more traditional...

Voltage Harmonics Mitigation through Hybrid Active Power Filter

Directory of Open Access Journals (Sweden)

Anwer Ali Sahito

2016-01-01

Full Text Available Fast dynamic response, high efficiency, low cost and small size of power electronic converters have exponentially increased their use in modern power system which resulted in harmonically distorted voltage and currents. Voltage harmonics mainly caused by current harmonics are more dangerous as performance and expected operating life of other power system equipment are affected by harmonically distorted supply voltage. Electronic filter circuits are used to improve system power quality by mitigating adverse effects of harmonics. Hybrid filters having advantages of both passive and active filters are preferred to resolve the problem of harmonics efficiently and avoiding any chance of resonance. In this paper, a three phase three wire network is considered to supply an adjustable speed drive represented by a resistive load connected across a three phase bridge rectifier. Simulation of the considered system shows THD (Total Harmonic Distortion of 18.91 and 7.61% in supply current and voltage respectively. A HAPF (Hybrid Active Power Filter is proposed to reduce these THD values below 5% as recommended by IEEE Standard-519. P-Q theorem is used to calculate required parameters for proposed filter, which is implemented through hysteresis control. Simulation results confirm the effectiveness of the designed filter as THD for both current and voltage have reduced below allowable limit of 5%.

On the evaluation of uncertainties for state estimation with the Kalman filter

International Nuclear Information System (INIS)

Eichstädt, S; Makarava, N; Elster, C

2016-01-01

The Kalman filter is an established tool for the analysis of dynamic systems with normally distributed noise, and it has been successfully applied in numerous areas. It provides sequentially calculated estimates of the system states along with a corresponding covariance matrix. For nonlinear systems, the extended Kalman filter is often used. This is derived from the Kalman filter by linearization around the current estimate. A key issue in metrology is the evaluation of the uncertainty associated with the Kalman filter state estimates. The ‘Guide to the Expression of Uncertainty in Measurement’ (GUM) and its supplements serve as the de facto standard for uncertainty evaluation in metrology. We explore the relationship between the covariance matrix produced by the Kalman filter and a GUM-compliant uncertainty analysis. In addition, the results of a Bayesian analysis are considered. For the case of linear systems with known system matrices, we show that all three approaches are compatible. When the system matrices are not precisely known, however, or when the system is nonlinear, this equivalence breaks down and different results can then be reached. For precisely known nonlinear systems, though, the result of the extended Kalman filter still corresponds to the linearized uncertainty propagation of the GUM. The extended Kalman filter can suffer from linearization and convergence errors. These disadvantages can be avoided to some extent by applying Monte Carlo procedures, and we propose such a method which is GUM-compliant and can also be applied online during the estimation. We illustrate all procedures in terms of a 2D dynamic system and compare the results with those obtained by particle filtering, which has been proposed for the approximate calculation of a Bayesian solution. Finally, we give some recommendations based on our findings. (paper)

Progress on the development of NbZr Radio frequency band reject filters

International Nuclear Information System (INIS)

Hudak, J.J.; Alper, M.; Cotte, D.; Gardner, C.G.; Harvey, A.

1983-01-01

This chapter reports on the design and testing of a tunable superconducting filter element fabricated from Nb25%Zr having a transition temperature of 11 K. The filter element will serve as a component in a multielement filter bank to be cooled to less than 10 K by a two stage Gifford-McMahon refrigerator. A radio frequency (RF) interference rejection system composed of a set of tunable superconducting filter elements is being developed to supplement conventional interference rejection tehcniques. The thermal loading performance of the 8.5 K Gifford-McMahon refrigerator is found to exceed 2 watts at 10 K on the second stage with a 10 watt loading on the first stage. A superconducting filter bank consisting of tunable narrow band RF filters applied to strong interfering signals can be used to match the dynamic range of the RF signal environment to that of the receiving system

A novel methodology for adaptive wave filtering of marine vessels: Theory and experiments

Digital Repository Service at National Institute of Oceanography (India)

Hassani, V.; Pascoal, A.M.; Sorensen, A.J.

This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. The vessel`s dynamic model adopted captures the sea state as an uncertain...

Control and filtering for semi-Markovian jump systems

CERN Document Server

Li, Fanbiao; Wu, Ligang

2017-01-01

This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

Development of discrete-time H∞ filtering method for time-delay compensation of rhodium incore detectors

International Nuclear Information System (INIS)

Park, Moon Kyu; Kim, Yong Hee; Cha, Kune Ho; Kim, Myung Ki

1998-01-01

A method is described to develop an H∞ filtering method for the dynamic compensation of self-powered neutron detectors normally used for fixed incore instruments. An H∞ norm of the filter transfer matrix is used as the optimization criteria in the worst-case estimation error sense. Filter modeling is performed for discrete-time model. The filter gains are optimized in the sense of noise attenuation level of H∞ setting. By introducing Bounded Real Lemma, the conventional algebraic Riccati inequalities are converted into Linear Matrix Inequalities (LMIs). Finally, the filter design problem is solved via the convex optimization framework using LMIs. The simulation results show that remarkable improvements are achieved in view of the filter response time and the filter design efficiency

Pseudo-real-time low-pass filter in ECG, self-adjustable to the frequency spectra of the waves.

Science.gov (United States)

Christov, Ivaylo; Neycheva, Tatyana; Schmid, Ramun; Stoyanov, Todor; Abächerli, Roger

2017-09-01

The electrocardiogram (ECG) acquisition is often accompanied by high-frequency electromyographic (EMG) noise. The noise is difficult to be filtered, due to considerable overlapping of its frequency spectrum to the frequency spectrum of the ECG. Today, filters must conform to the new guidelines (2007) for low-pass filtering in ECG with cutoffs of 150 Hz for adolescents and adults, and to 250 Hz for children. We are suggesting a pseudo-real-time low-pass filter, self-adjustable to the frequency spectra of the ECG waves. The filter is based on the approximation procedure of Savitzky-Golay with dynamic change in the cutoff frequency. The filter is implemented pseudo-real-time (real-time with a certain delay). An additional option is the automatic on/off triggering, depending on the presence/absence of EMG noise. The analysis of the proposed filter shows that the low-frequency components of the ECG (low-power P- and T-waves, PQ-, ST- and TP-segments) are filtered with a cutoff of 14 Hz, the high-power P- and T-waves are filtered with a cutoff frequency in the range of 20-30 Hz, and the high-frequency QRS complexes are filtered with cutoff frequency of higher than 100 Hz. The suggested dynamic filter satisfies the conflicting requirements for a strong suppression of EMG noise and at the same time a maximal preservation of the ECG high-frequency components.

DIGITAL FILTERS IMPLEMENTATION IN MICROPROCESSOR-BASED RELAY PROTECTION

Directory of Open Access Journals (Sweden)

Yu. V. Rumiantsev

2016-01-01

Full Text Available This article presents the implementation of digital filters used in digital relay protection current measuring elements. Mathematical descriptions of the considered digital filters as well as the computer programs for their coefficients calculation are described. It has been shown that in order to reliable estimate the digital filter performance its input signals waveforms must be close to the actual secondary current waveform of the current transformer to which the digital protection with the estimated digital filter is connected. For these purposes in MatLab–Simulink dynamic simulation environment the power system and the current measuring element models were developed. Performed calculations allowed to reveal that the exponentially decaying DC component which in some cases contains in primary fault current drives the current transformer core into saturation even when its nominal parameters are not exceeded. This results in distortion of the current transformer secondary current which in this case contains higher and inter-harmonics. Moreover, such harmonic content is not completely taking into account during coefficients calculation of the considered digital filters what results in signal magnitude estimation inaccuracy. Comparison of the digital filters response to the above-mentioned input signals allowed to find out such digital filter implementations which enable signal magnitude estimation with a minimum error. Ways of filtering quality improvement concerned with the window functions are proposed. Thus, the joint usage of digital filter and Hamming window allows to achieve the zero value of the signal magnitude gain factor in high-frequency range and substantially suppress all spectral components above 100 Hz. The increasing of the signal magnitude settling time in this case can be reduced by choosing the most optimal parameters of the all components of the current measuring element.

Wien filter using in exploring on low-energy radioactive nuclei

International Nuclear Information System (INIS)

Bobyleva, L.V.; Kuznetsov, I.V.; Perel'shtejn, Eh.A.; Perel'shtejn, O.Eh.

2002-01-01

The possibility of using the Wien filter as a mass separator for the neutron enriched nuclei study is under discussion. The nuclei are produced as a result of 238 U fission within the frame of the 'DRIBs' project. The main ion-optics characteristics of the Wien filter are obtained using the moment method. Parameter optimization has been fulfilled to obtain the maximum resolution. The ion beam dynamics and heavy ion separation have been illustrated using the macroparticle simulation for the chosen optimal filter parameter. It is shown that the resolution can be obtained on the level higher than 10 2 . It provides an effective separation of the fission fragments with the high atomic numbers

Analytically solvable chaotic oscillator based on a first-order filter

Energy Technology Data Exchange (ETDEWEB)

Corron, Ned J.; Cooper, Roy M.; Blakely, Jonathan N. [Charles M. Bowden Laboratory, Aviation and Missile Research, Development and Engineering Center, U.S. Army RDECOM, Redstone Arsenal, Alabama 35898 (United States)

2016-02-15

A chaotic hybrid dynamical system is introduced and its analytic solution is derived. The system is described as an unstable first order filter subject to occasional switching of a set point according to a feedback rule. The system qualitatively differs from other recently studied solvable chaotic hybrid systems in that the timing of the switching is regulated by an external clock. The chaotic analytic solution is an optimal waveform for communications in noise when a resistor-capacitor-integrate-and-dump filter is used as a receiver. As such, these results provide evidence in support of a recent conjecture that the optimal communication waveform for any stable infinite-impulse response filter is chaotic.

Assimilating irregularly spaced sparsely observed turbulent signals with hierarchical Bayesian reduced stochastic filters

International Nuclear Information System (INIS)

Brown, Kristen A.; Harlim, John

2013-01-01

In this paper, we consider a practical filtering approach for assimilating irregularly spaced, sparsely observed turbulent signals through a hierarchical Bayesian reduced stochastic filtering framework. The proposed hierarchical Bayesian approach consists of two steps, blending a data-driven interpolation scheme and the Mean Stochastic Model (MSM) filter. We examine the potential of using the deterministic piecewise linear interpolation scheme and the ordinary kriging scheme in interpolating irregularly spaced raw data to regularly spaced processed data and the importance of dynamical constraint (through MSM) in filtering the processed data on a numerically stiff state estimation problem. In particular, we test this approach on a two-layer quasi-geostrophic model in a two-dimensional domain with a small radius of deformation to mimic ocean turbulence. Our numerical results suggest that the dynamical constraint becomes important when the observation noise variance is large. Second, we find that the filtered estimates with ordinary kriging are superior to those with linear interpolation when observation networks are not too sparse; such robust results are found from numerical simulations with many randomly simulated irregularly spaced observation networks, various observation time intervals, and observation error variances. Third, when the observation network is very sparse, we find that both the kriging and linear interpolations are comparable

Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters

Science.gov (United States)

Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.

2016-11-01

Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Hakon

2016-06-14

This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Hakon; Law, Kody J. H.; Tempone, Raul

2016-01-01

This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

The Reduced Rank of Ensemble Kalman Filter to Estimate the Temperature of Non Isothermal Continue Stirred Tank Reactor

OpenAIRE

Erna Apriliani; Dieky Adzkiya; Arief Baihaqi

2011-01-01

Kalman filter is an algorithm to estimate the state variable of dynamical stochastic system. The square root ensemble Kalman filter is an modification of Kalman filter. The square root ensemble Kalman filter is proposed to keep the computational stability and reduce the computational time. In this paper we study the efficiency of the reduced rank ensemble Kalman filter. We apply this algorithm to the non isothermal continue stirred tank reactor problem. We decompose the covariance of the ense...

Design considerations for a suboptimal Kalman filter

Science.gov (United States)

Difilippo, D. J.

1995-06-01

In designing a suboptimal Kalman filter, the designer must decide how to simplify the system error model without causing the filter estimation errors to increase to unacceptable levels. Deletion of certain error states and decoupling of error state dynamics are the two principal model simplifications that are commonly used in suboptimal filter design. For the most part, the decisions as to which error states can be deleted or decoupled are based on the designer's understanding of the physics of the particular system. Consequently, the details of a suboptimal design are usually unique to the specific application. In this paper, the process of designing a suboptimal Kalman filter is illustrated for the case of an airborne transfer-of-alignment (TOA) system used for synthetic aperture radar (SAR) motion compensation. In this application, the filter must continuously transfer the alignment of an onboard Doppler-damped master inertial navigation system (INS) to a strapdown navigator that processes information from a less accurate inertial measurement unit (IMU) mounted on the radar antenna. The IMU is used to measure spurious antenna motion during the SAR imaging interval, so that compensating phase corrections can be computed and applied to the radar returns, thereby presenting image degradation that would otherwise result from such motions. The principles of SAR are described in many references, for instance. The primary function of the TOA Kalman filter in a SAR motion compensation system is to control strapdown navigator attitude errors, and to a less degree, velocity and heading errors. Unlike a classical navigation application, absolute positional accuracy is not important. The motion compensation requirements for SAR imaging are discussed in some detail. This TOA application is particularly appropriate as a vehicle for discussing suboptimal filter design, because the system contains features that can be exploited to allow both deletion and decoupling of error

MST Filterability Tests

Energy Technology Data Exchange (ETDEWEB)

Poirier, M. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Burket, P. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Duignan, M. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2015-03-12

The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). The low filter flux through the ARP has limited the rate at which radioactive liquid waste can be treated. Recent filter flux has averaged approximately 5 gallons per minute (gpm). Salt Batch 6 has had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. In addition, at the time the testing started, SRR was assessing the impact of replacing the 0.1 micron filter with a 0.5 micron filter. This report describes testing of MST filterability to investigate the impact of filter pore size and MST particle size on filter flux and testing of filter enhancers to attempt to increase filter flux. The authors constructed a laboratory-scale crossflow filter apparatus with two crossflow filters operating in parallel. One filter was a 0.1 micron Mott sintered SS filter and the other was a 0.5 micron Mott sintered SS filter. The authors also constructed a dead-end filtration apparatus to conduct screening tests with potential filter aids and body feeds, referred to as filter enhancers. The original baseline for ARP was 5.6 M sodium salt solution with a free hydroxide concentration of approximately 1.7 M.3 ARP has been operating with a sodium concentration of approximately 6.4 M and a free hydroxide concentration of approximately 2.5 M. SRNL conducted tests varying the concentration of sodium and free hydroxide to determine whether those changes had a significant effect on filter flux. The feed slurries for the MST filterability tests were composed of simple salts (NaOH, NaNO₂, and NaNO₃) and MST (0.2 – 4.8 g/L). The feed slurry for the filter enhancer tests contained simulated salt batch 6 supernate, MST, and filter enhancers.

Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

Science.gov (United States)

Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

2016-07-26

This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.

A nested sampling particle filter for nonlinear data assimilation

KAUST Repository

Elsheikh, Ahmed H.

2014-04-15

We present an efficient nonlinear data assimilation filter that combines particle filtering with the nested sampling algorithm. Particle filters (PF) utilize a set of weighted particles as a discrete representation of probability distribution functions (PDF). These particles are propagated through the system dynamics and their weights are sequentially updated based on the likelihood of the observed data. Nested sampling (NS) is an efficient sampling algorithm that iteratively builds a discrete representation of the posterior distributions by focusing a set of particles to high-likelihood regions. This would allow the representation of the posterior PDF with a smaller number of particles and reduce the effects of the curse of dimensionality. The proposed nested sampling particle filter (NSPF) iteratively builds the posterior distribution by applying a constrained sampling from the prior distribution to obtain particles in high-likelihood regions of the search space, resulting in a reduction of the number of particles required for an efficient behaviour of particle filters. Numerical experiments with the 3-dimensional Lorenz63 and the 40-dimensional Lorenz96 models show that NSPF outperforms PF in accuracy with a relatively smaller number of particles. © 2013 Royal Meteorological Society.

Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

Directory of Open Access Journals (Sweden)

Chien-Hao Tseng

2016-07-01

Full Text Available This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF and fuzzy logic adaptive system (FLAS for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF, unscented Kalman filter (UKF, and CKF approaches.

Optimization of nonlinear, non-Gaussian Bayesian filtering for diagnosis and prognosis of monotonic degradation processes

Science.gov (United States)

Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.

2018-05-01

The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.

Nonlinear Filtering with IMM Algorithm for Ultra-Tight GPS/INS Integration

Directory of Open Access Journals (Sweden)

Dah-Jing Jwo

2013-05-01

Full Text Available Abstract This paper conducts a performance evaluation for the ultra-tight integration of a Global positioning system (GPS and an inertial navigation system (INS, using nonlinear filtering approaches with an interacting multiple model (IMM algorithm. An ultra-tight GPS/INS architecture involves the integration of in-phase and quadrature components from the correlator of a GPS receiver with INS data. An unscented Kalman filter (UKF, which employs a set of sigma points by deterministic sampling, avoids the error caused by linearization as in an extended Kalman filter (EKF. Based on the filter structural adaptation for describing various dynamic behaviours, the IMM nonlinear filtering provides an alternative for designing the adaptive filter in the ultra-tight GPS/INS integration. The use of IMM enables tuning of an appropriate value for the process of noise covariance so as to maintain good estimation accuracy and tracking capability. Two examples are provided to illustrate the effectiveness of the design and demonstrate the effective improvement in navigation estimation accuracy. A performance comparison among various filtering methods for ultra-tight integration of GPS and INS is also presented. The IMM based nonlinear filtering approach demonstrates the effectiveness of the algorithm for improved positioning performance.

Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

Coalescence of silver unidimensional structures by molecular dynamics simulation; Coalescencia de estructuras unidimensionales de plata por simulacion dinamica molecular

Energy Technology Data Exchange (ETDEWEB)

Perez A, M.; Gutierrez W, C.E.; Mondragon, G. [ININ, 52750 La Marquesa, Estado de Mexico (Mexico); Arenas, J. [IFUNAM, 04510 Mexico D.F. (Mexico)

2007-07-01

The study of nanoparticles coalescence and silver nano rods phenomena by means of molecular dynamics simulation under the thermodynamic laws is reported. In this work we focus ourselves to see the conditions under which the one can be given one dimension growth of silver nano rods for the coalescence phenomenon among two nano rods or one nano rod and one particle; what allows us to study those structural, dynamic and morphological properties of the silver nano rods to different thermodynamic conditions. The simulations are carried out using the Sutton-Chen potentials of interaction of many bodies that allow to obtain appropriate results with the real physical systems. (Author)

DOMINAÇÃO E REPRESSÃO DA SOCIEDADE INDUSTRIAL AVANÇADA EM HOMEM UNIDIMENSIONAL DE HERBERT MARCUSE

Directory of Open Access Journals (Sweden)

Ramom Gomes da Silva

2017-08-01

Full Text Available Este trabalho apresenta uma reflexão acerca dos instrumentos de dominação e repressão da sociedade industrial avançada. A partir da leitura da primeira parte do livro Ideologia da sociedade industrial: O homem unidimensional, Herbert Marcuse analisa a sociedade industrial avançada e as tendências do capitalismo tardio expondo as novas formas de controle e dominação dos indivíduos na contemporaneidade. Os meios de dominação do capitalismo avançado têm-se mostrado mais eficientes e eficazes do que antigos regimes baseados na violência explícita, isto é, sem uso de um terror aberto, tem o domínio das esferas da existência humana, sejam elas públicas ou privadas. Esses mecanismos de controles proporcionaram a integração entre o pensamento e o comportamento dos indivíduos, de tal modo que o sujeito sente-se livre em situação de não liberdade, situação em que  necessidades impostas são aceitas e ainda repassadas às gerações seguintes sem o menor questionamento.

Gated myocardial SPECT using spatial and temporal filtering

International Nuclear Information System (INIS)

Hatton, R.L.; Hutton, B.F.; Kyme, A.Z.; Larcos, G.

2002-01-01

Full text: Standard protocols for examining myocardial perfusion and motion defects involve the use of gated SPECT images, and a composite of the gated frames. This study examines the usefulness of extracting one or a combination of frames from the gated image to assess perfusion, and whether the addition of a temporal filter to the gated image improves signal to noise. Choice of the most appropriate frame was also considered. Sixteen and eight frame gated SPECT studies were simulated using the dynamic NURBS-based cardiac torso (NCAT) phantom. Variously sized perfusion defects were included in the inferior wall to assess contrast to normal tissue. Scatter and attenuation were not included. Butterworth spatial cutoff frequencies were varied to establish the most appropriate combination of temporal/spatial filters to reduce noise and retain contrast in the images. The 16 frame data produced higher ejection fraction across all spatial filter cutoffs, and generally was unaffected by temporal filtering. Temporal filtering reduced the noise in a uniform liver region in the gated images to within 25% of the composite image noise. The lesion extent and contrast were greater in the end-diastolic frames compared to end-systolic and mid-cycle frames. In conclusion, by using a temporally filtered end-diastolic image from the gated sequence, a favourable balance between noise and contrast can be achieved. Work is progress to confirm these findings in the clinical situation. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

Automated pulmonary nodule volumetry with an optimized algorithm - accuracy at different slice thicknesses compared to unidimensional and bidimentional measurements

International Nuclear Information System (INIS)

Vogel, M.N.; Schmuecker, S.; Maksimovich, O.; Claussen, C.D.; Horger, M.; Vonthein, R.; Bethge, W.; Dicken, V.

2008-01-01

Purpose: This in-vivo study quantifies the accuracy of automated pulmonary nodule volumetry in reconstructions with different slice thicknesses (ST) of clinical routine CT scans. The accuracy of volumetry is compared to that of unidimensional and bidimensional measurements. Materials and Methods: 28 patients underwent contrast enhanced 64-row CT scans of the chest and abdomen obtained in the clinical routine. All scans were reconstructed with 1, 3, and 5 mm ST. Volume, maximum axial diameter, and areas following the guidelines of Response Evaluation Criteria in Solid Tumors (RECIST) and the World Health Organization (WHO) were measured in all 101 lesions located in the overlap region of both scans using the new software tool OncoTreat (MeVis, Deutschland). The accuracy of quantifications in both scans was evaluated using the Bland and Altmann method. The reproducibility of measurements in dependence on the ST was compared using the likelihood ratio Chi-squared test. Results: A total of 101 nodules were identified in all patients. Segmentation was considered successful in 88.1% of the cases without local manual correction which was deliberately not employed in this study. For 80 nodules all 6 measurements were successful. These were statistically evaluated. The volumes were in the range 0.1 to 15.6 ml. Of all 80 lesions, 34 (42%) had direct contact to the pleura parietalis oder diaphragmalis and were termed parapleural, 32 (40%) were paravascular, 7 (9%) both parapleural and paravascular, the remaining 21 (27%) were free standing in the lung. The trueness differed significantly (Chi-square 7.22, p value 0.027) and was best with an ST of 3 mm and worst at 5 mm. Differences in precision were not significant (Chi-square 5.20, p value 0.074). The limits of agreement for an ST of 3 mm were ± 17.5% of the mean volume for volumetry, for maximum diameters ± 1.3 mm, and ± 31.8% for the calculated areas. Conclusion: Automated volumetry of pulmonary nodules using Onco

The Kalman filter for the pedologist's tool kit

NARCIS (Netherlands)

Webster, R.; Heuvelink, G.B.M.

2006-01-01

The Kalman filter is a tool designed primarily to estimate the values of the `state¿ of a dynamic system in time. There are two main equations. These are the state equation, which describes the behaviour of the state over time, and the measurement equation, which describes at what times and in what

Adaptive Kalman Filter of Transfer Alignment with Un-modeled Wing Flexure of Aircraft

Institute of Scientific and Technical Information of China (English)

无

2008-01-01

The alignment accuracy of the strap-down inertial navigation system (SINS) of airborne weapon is greatly degraded by the dynamic wing flexure of the aircraft. An adaptive Kalman filter uses innovation sequences based on the maximum likelihood estimated criterion to adapt the system noise covariance matrix and the measurement noise covariance matrix on line, which is used to estimate the misalignment if the model of wing flexure of the aircraft is unknown. From a number of simulations, it is shown that the accuracy of the adaptive Kalman filter is better than the conventional Kalman filter, and the erroneous misalignment models of the wing flexure of aircraft will cause bad estimation results of Kalman filter using attitude match method.

Controlling flow conditions of test filters in iodine filters

International Nuclear Information System (INIS)

Holmberg, R.; Laine, J.

1979-03-01

Several different iodine filter and test filter designs and experience gained from their operation are presented. For the flow experiments, an iodine filter system equipped with flow regulating and measuring devices was built. In the experiments the influence of the packing method of the iodine sorption material and the influence of the flow regulating and measuring divices upon the flow conditions in the test filters was studied. On the basis of the experiments it has been shown that the flows through the test filters always can be adjusted to a correct value if there only is a high enough pressure difference available across the test filter ducting. As a result of the research, several different methods are presented with which the flows through the test filters in both operating and future iodine sorption system can easily be measured and adjusted to their correct values. (author)

CFD simulation of an internal spin-filter: evidence of lateral migration and exchange flow through the mesh.

Science.gov (United States)

Figueredo-Cardero, Alvio; Chico, Ernesto; Castilho, Leda R; Medronho, Ricardo A

2009-11-01

In the present work Computational Fluid Dynamics (CFD) was used to study the flow field and particle dynamics in an internal spin-filter (SF) bioreactor system. Evidence of a radial exchange flow through the filter mesh was detected, with a magnitude up to 130-fold higher than the perfusion flow, thus significantly contributing to radial drag. The exchange flow magnitude was significantly influenced by the filter rotation rate, but not by the perfusion flow, within the ranges evaluated. Previous reports had only given indirect evidences of this exchange flow phenomenon in spin-filters, but the current simulations were able to quantify and explain it. Flow pattern inside the spin-filter bioreactor resembled a typical Taylor-Couette flow, with vortices being formed in the annular gap and eventually penetrating the internal volume of the filter, thus being the probable reason for the significant exchange flow observed. The simulations also showed that cells become depleted in the vicinity of the mesh due to lateral particle migration. Cell concentration near the filter was approximately 50% of the bulk concentration, explaining why cell separation achieved in SFs is not solely due to size exclusion. The results presented indicate the power of CFD techniques to study and better understand spin-filter systems, aiming at the establishment of effective design, operation and scale-up criteria.

An Improved Strong Tracking Cubature Kalman Filter for GPS/INS Integrated Navigation Systems.

Science.gov (United States)

Feng, Kaiqiang; Li, Jie; Zhang, Xi; Zhang, Xiaoming; Shen, Chong; Cao, Huiliang; Yang, Yanyu; Liu, Jun

2018-06-12

The cubature Kalman filter (CKF) is widely used in the application of GPS/INS integrated navigation systems. However, its performance may decline in accuracy and even diverge in the presence of process uncertainties. To solve the problem, a new algorithm named improved strong tracking seventh-degree spherical simplex-radial cubature Kalman filter (IST-7thSSRCKF) is proposed in this paper. In the proposed algorithm, the effect of process uncertainty is mitigated by using the improved strong tracking Kalman filter technique, in which the hypothesis testing method is adopted to identify the process uncertainty and the prior state estimate covariance in the CKF is further modified online according to the change in vehicle dynamics. In addition, a new seventh-degree spherical simplex-radial rule is employed to further improve the estimation accuracy of the strong tracking cubature Kalman filter. In this way, the proposed comprehensive algorithm integrates the advantage of 7thSSRCKF’s high accuracy and strong tracking filter’s strong robustness against process uncertainties. The GPS/INS integrated navigation problem with significant dynamic model errors is utilized to validate the performance of proposed IST-7thSSRCKF. Results demonstrate that the improved strong tracking cubature Kalman filter can achieve higher accuracy than the existing CKF and ST-CKF, and is more robust for the GPS/INS integrated navigation system.

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

Science.gov (United States)

Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.

2011-02-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

International Nuclear Information System (INIS)

Olivares, A; Olivares, G; Górriz, J M; Ramírez, J

2011-01-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed

The Rao-Blackwellized Particle Filter: A Filter Bank Implementation

Directory of Open Access Journals (Sweden)

Karlsson Rickard

2010-01-01

Full Text Available For computational efficiency, it is important to utilize model structure in particle filtering. One of the most important cases occurs when there exists a linear Gaussian substructure, which can be efficiently handled by Kalman filters. This is the standard formulation of the Rao-Blackwellized particle filter (RBPF. This contribution suggests an alternative formulation of this well-known result that facilitates reuse of standard filtering components and which is also suitable for object-oriented programming. Our RBPF formulation can be seen as a Kalman filter bank with stochastic branching and pruning.

A generalized model via random walks for information filtering

Energy Technology Data Exchange (ETDEWEB)

Ren, Zhuo-Ming, E-mail: zhuomingren@gmail.com [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Kong, Yixiu [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Shang, Ming-Sheng, E-mail: msshang@cigit.ac.cn [Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Zhang, Yi-Cheng [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland)

2016-08-06

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

A generalized model via random walks for information filtering

International Nuclear Information System (INIS)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-01-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

Convergent Filter Bases

Directory of Open Access Journals (Sweden)

Coghetto Roland

2015-09-01

Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.

Identification of chaotic memristor systems based on piecewise adaptive Legendre filters

International Nuclear Information System (INIS)

Zhao, Yibo; Zhang, Xiuzai; Xu, Jin; Guo, Yecai

2015-01-01

Memristor is a nonlinear device, which plays an important role in the design and implementation of chaotic systems. In order to be able to understand in-depth the complex nonlinear dynamic behaviors in chaotic memristor systems, modeling or identification of its nonlinear model is very important premise. This paper presents a chaotic memristor system identification method based on piecewise adaptive Legendre filters. The threshold decomposition is carried out for the input vector, and also the input signal subintervals via decomposition satisfy the convergence condition of the adaptive Legendre filters. Then the adaptive Legendre filter structure and adaptive weight update algorithm are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics.

Input shaping filter methods for the control of structurally flexible, long-reach manipulators

International Nuclear Information System (INIS)

Kwon, Dong-Soo; Hwang, Dong-Hwan; Babcock, S.M.; Burks, B.L.

1993-01-01

Within the Environmental Restoration and Waste Management Program of the US Department of Energy, the remediation of single-shell radioactive waste storage tanks is one of the areas that challenge state-of-the-art equipment and methods. Concepts that utilize long-reach manipulators are being seriously considered for this task. Due to high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to exhibit significant structural flexibility. To avoid structural vibrations during operation, various types of shaping filter methods have been investigated. A robust notch filtering method and an impulse shaping method were used as simulation benchmarks. In addition to that, two very different approaches have been developed and compared. One new approach, referred to as a ''feedforward simulation filter,'' uses imbedded simulation with complete knowledge of the system dynamics. The other approach, ''fuzzy shaping method,'' employs a fuzzy logic method to modify the joint trajectory from the desired end-position trajectory without precise knowledge of the system dynamics

Application of DFT Filter Banks and Cosine Modulated Filter Banks in Filtering

Science.gov (United States)

Lin, Yuan-Pei; Vaidyanathan, P. P.

1994-01-01

None given. This is a proposal for a paper to be presented at APCCAS '94 in Taipei, Taiwan. (From outline): This work is organized as follows: Sec. II is devoted to the construction of the new 2m channel under-decimated DFT filter bank. Implementation and complexity of this DFT filter bank are discussed therein. IN a similar manner, the new 2m channel cosine modulated filter bank is discussed in Sec. III. Design examples are given in Sec. IV.

A Study of Parallel Operation of an active Filter and passive Filters

DEFF Research Database (Denmark)

Chen, Zhe; Blaabjerg, Frede; Pedersen, John Kim

2002-01-01

This paper reports investigations of the parallel operations of a current controlled active filter and passive filters in a system with current harmonic sources. The task of reactive power and harmonic compensation is shared by the active filter and passive filters. The passive filters are used...... arrangements of the active and passive filters can operate relatively independently, also the compensation flexibility of the active filter can be fully exploited, such as one active filter for several harmonic sources.The simulation studies on various systems have been performed to evaluate the effectiveness...... of the systems. The results show that the power factor is corrected by the passive filters, harmonics are minimized by both active and passive filters and overloading of the filter system can be avoided....

Kalman filtering for rhodium self-powered neutron detectors

International Nuclear Information System (INIS)

Kantrowitz, M.L.

1988-01-01

Rhodium self-powered neutron detectors are utilized in many pressurized water reactors to determine the neutronic behavior within the core. In order to compensate for the inherent time delay associated with the response of these detectors, a dynamic compensation algorithm is currently used in Combustion Engineering plants to reconstruct the dynamic flux signal which is being sensed by the rhodium detectors. This paper describes a new dynamic compensation algorithm, based on Kalman filtering, which improves on the noise gain and response time characteristics of the algorithm currently used, and offers the possibility of utilizing the proven rhodium detector based fixed in-core detector system as an integral part of advanced core control and/or protection systems

A fast ellipse extended target PHD filter using box-particle implementation

Science.gov (United States)

Zhang, Yongquan; Ji, Hongbing; Hu, Qi

2018-01-01

This paper presents a box-particle implementation of the ellipse extended target probability hypothesis density (ET-PHD) filter, called the ellipse extended target box particle PHD (EET-BP-PHD) filter, where the extended targets are described as a Poisson model developed by Gilholm et al. and the term "box" is here equivalent to the term "interval" used in interval analysis. The proposed EET-BP-PHD filter is capable of dynamically tracking multiple ellipse extended targets and estimating the target states and the number of targets, in the presence of clutter measurements, false alarms and missed detections. To derive the PHD recursion of the EET-BP-PHD filter, a suitable measurement likelihood is defined for a given partitioning cell, and the main implementation steps are presented along with the necessary box approximations and manipulations. The limitations and capabilities of the proposed EET-BP-PHD filter are illustrated by simulation examples. The simulation results show that a box-particle implementation of the ET-PHD filter can avoid the high number of particles and reduce computational burden, compared to a particle implementation of that for extended target tracking.

Passive Power Filters

CERN Document Server

Künzi, R.

2015-06-15

Power converters require passive low-pass filters which are capable of reducing voltage ripples effectively. In contrast to signal filters, the components of power filters must carry large currents or withstand large voltages, respectively. In this paper, three different suitable filter struc tures for d.c./d.c. power converters with inductive load are introduced. The formulas needed to calculate the filter components are derived step by step and practical examples are given. The behaviour of the three discussed filters is compared by means of the examples. P ractical aspects for the realization of power filters are also discussed.

Workplace Exposure to Titanium Dioxide Nanopowder Released from a Bag Filter System

Directory of Open Access Journals (Sweden)

Jun Ho Ji

2015-01-01

Full Text Available Many researchers who use laboratory-scale synthesis systems to manufacture nanomaterials could be easily exposed to airborne nanomaterials during the research and development stage. This study used various real-time aerosol detectors to investigate the presence of nanoaerosols in a laboratory used to manufacture titanium dioxide (TiO2. The TiO2 nanopowders were produced via flame synthesis and collected by a bag filter system for subsequent harvesting. Highly concentrated nanopowders were released from the outlet of the bag filter system into the laboratory. The fractional particle collection efficiency of the bag filter system was only 20% at particle diameter of 100 nm, which is much lower than the performance of a high-efficiency particulate air (HEPA filter. Furthermore, the laboratory hood system was inadequate to fully exhaust the air discharged from the bag filter system. Unbalanced air flow rates between bag filter and laboratory hood systems could result in high exposure to nanopowder in laboratory settings. Finally, we simulated behavior of nanopowders released in the laboratory using computational fluid dynamics (CFD.

Chaotic secure communication based on strong tracking filtering

International Nuclear Information System (INIS)

Li Xiongjie; Xu Zhengguo; Zhou Donghua

2008-01-01

A scheme for implementing secure communication based on chaotic maps and strong tracking filter (STF) is presented, and a modified STF algorithm with message estimation is developed for the special requirement of chaotic secure communication. At the emitter, the message symbol is modulated by chaotic mapping and is output through a nonlinear function. At the receiver, the driving signal is received and the message symbol is recovered dynamically by the STF with estimation of message symbol. Simulation results of Holmes map demonstrate that when message symbols are binary codes, STF can effectively recover the codes of the message from the noisy chaotic signals. Compared with the extended Kalman filter (EKF), STF has a lower bit error rate

Estimation of atmospheric fluoride by limed filter papers

International Nuclear Information System (INIS)

Smith, D.R.

1988-09-01

The limed filter paper method of static sampling of atmospheric fluoride is reviewed in this report. Use of the technique, in conjunction with precise measurement of the absorbed fluoride and calibration with dynamic air sampling techniques, to estimate atmospheric fluoride levels, is considered to give only qualitative data (± 50%). The limed filter paper method is site specific due to variations in meteorological conditions. Its main value is to indicate seasonal and annual trends in fluoride exposure of vegetation. Subject to these considerations, the lower and upper limits of atmospheric fluoride exposure and the applicability to atmospheric fluoride estimation under routine or emergency fluoride release conditions are discussed, with special emphasis on the limiting factors

An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

Science.gov (United States)

Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

2009-01-01

In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

Decentralized Riemannian Particle Filtering with Applications to Multi-Agent Localization

Science.gov (United States)

2012-06-14

ex- ample, Montijano et al., [93] proposed a method based on dynamic voting , Noack et al., proposed an approach based on pseudo-Gaussian probability...Carlos Saques. “Distributed Robust Data Fusion Based on Dynamic Voting ”. IEEE International Conference on Robotics and Automation, 5893–5898. Shanghai... Tensors ”. Jour- nal of Elasticity, 82:273–296, 2006. 200. Mohammad Sadegh and Mohebbi Nazar. “A Comparative Study of Different Kalman Filtering Methods

Detecting an atomic clock frequency anomaly using an adaptive Kalman filter algorithm

Science.gov (United States)

Song, Huijie; Dong, Shaowu; Wu, Wenjun; Jiang, Meng; Wang, Weixiong

2018-06-01

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. The Kalman filter algorithm, as a linear optimal algorithm, has been widely used in real-time detection for abnormal frequency. In order to obtain an optimal state estimation, the observation model and dynamic model of the Kalman filter algorithm should satisfy Gaussian white noise conditions. The detection performance is degraded if anomalies affect the observation model or dynamic model. The idea of the adaptive Kalman filter algorithm, applied to clock frequency anomaly detection, uses the residuals given by the prediction for building ‘an adaptive factor’ the prediction state covariance matrix is real-time corrected by the adaptive factor. The results show that the model error is reduced and the detection performance is improved. The effectiveness of the algorithm is verified by the frequency jump simulation, the frequency drift jump simulation and the measured data of the atomic clock by using the chi-square test.

Neural Network-Based Passive Filtering for Delayed Neutral-Type Semi-Markovian Jump Systems.

Science.gov (United States)

Shi, Peng; Li, Fanbiao; Wu, Ligang; Lim, Cheng-Chew

2017-09-01

This paper investigates the problem of exponential passive filtering for a class of stochastic neutral-type neural networks with both semi-Markovian jump parameters and mixed time delays. Our aim is to estimate the states by designing a Luenberger-type observer, such that the filter error dynamics are mean-square exponentially stable with an expected decay rate and an attenuation level. Sufficient conditions for the existence of passive filters are obtained, and a convex optimization algorithm for the filter design is given. In addition, a cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem, which can be readily solved by the existing optimization techniques. Numerical examples are given to demonstrate the effectiveness of the proposed techniques.

Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters*

KAUST Repository

Hoteit, Ibrahim

2012-02-01

This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. The authors show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman filter (PKF). In the PKF, the solution of a nonlinear filtering problem is expressed as the weighted average of an “ensemble of Kalman filters” operating in parallel. Running an ensemble of Kalman filters is, however, computationally prohibitive for realistic atmospheric and oceanic data assimilation problems. For this reason, the authors consider the construction of the PKF through an “ensemble” of ensemble Kalman filters (EnKFs) instead, and call the implementation the particle EnKF (PEnKF). It is shown that different types of the EnKFs can be considered as special cases of the PEnKF. Similar to the situation in the particle filter, the authors also introduce a resampling step to the PEnKF in order to reduce the risk of weights collapse and improve the performance of the filter. Numerical experiments with the strongly nonlinear Lorenz-96 model are presented and discussed.

Rectifier Filters

Directory of Open Access Journals (Sweden)

Y. A. Bladyko

2010-01-01

Full Text Available The paper contains definition of a smoothing factor which is suitable for any rectifier filter. The formulae of complex smoothing factors have been developed for simple and complex passive filters. The paper shows conditions for application of calculation formulae and filters. 

Applying a particle filtering technique for canola crop growth stage estimation in Canada

Science.gov (United States)

Sinha, Abhijit; Tan, Weikai; Li, Yifeng; McNairn, Heather; Jiao, Xianfeng; Hosseini, Mehdi

2017-10-01

Accurate crop growth stage estimation is important in precision agriculture as it facilitates improved crop management, pest and disease mitigation and resource planning. Earth observation imagery, specifically Synthetic Aperture Radar (SAR) data, can provide field level growth estimates while covering regional scales. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization SAR data and ground truth growth stage data are used to model the influence of canola growth stages on SAR imagery extracted parameters. The details of the growth stage modeling work are provided, including a) the development of a new crop growth stage indicator that is continuous and suitable as the state variable in the dynamic estimation procedure; b) a selection procedure for SAR polarimetric parameters that is sensitive to both linear and nonlinear dependency between variables; and c) procedures for compensation of SAR polarimetric parameters for different beam modes. The data was collected over three crop growth seasons in Manitoba, Canada, and the growth model provides the foundation of a novel dynamic filtering framework for real-time estimation of canola growth stages using the multi-sensor and multi-mode SAR data. A description of the dynamic filtering framework that uses particle filter as the estimator is also provided in this paper.

Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation.

Science.gov (United States)

Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin

2014-03-01

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.

Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining

Directory of Open Access Journals (Sweden)

S. Sadesh

2015-01-01

Full Text Available Web with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not analyzed in an extensive manner. At the same time, existing user profile based prediction in web data mining is not exhaustive in producing personalized result rate. To improve the query result rate on dynamics of user behavior over time, Hamilton Filtered Regime Switching User Query Probability (HFRS-UQP framework is proposed. HFRS-UQP framework is split into two processes, where filtering and switching are carried out. The data mining based filtering in our research work uses the Hamilton Filtering framework to filter user result based on personalized information on automatic updated profiles through search engine. Maximized result is fetched, that is, filtered out with respect to user behavior profiles. The switching performs accurate filtering updated profiles using regime switching. The updating in profile change (i.e., switches regime in HFRS-UQP framework identifies the second- and higher-order association of query result on the updated profiles. Experiment is conducted on factors such as personalized information search retrieval rate, filtering efficiency, and precision ratio.

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

Science.gov (United States)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

Spatial filters for focusing ultrasound images

DEFF Research Database (Denmark)

Jensen, Jørgen Arendt; Gori, Paola

2001-01-01

, but the approach always yields point spread functions better or equal to a traditional dynamically focused image. Finally, the process was applied to in-vivo clinical images of the liver and right kidney from a 28 years old male. The data was obtained with a single element transducer focused at 100 mm....... A new method for making spatial matched filter focusing of RF ultrasound data is proposed based on the spatial impulse response description of the imaging. The response from a scatterer at any given point in space relative to the transducer can be calculated, and this gives the spatial matched filter...... for synthetic aperture imaging for single element transducers. It is evaluated using the Field II program. Data from a single 3 MHz transducer focused at a distance of 80 mm is processed. Far from the transducer focal region, the processing greatly improves the image resolution: the lateral slice...

Wave-filter-based approach for generation of a quiet space in a rectangular cavity

Science.gov (United States)

Iwamoto, Hiroyuki; Tanaka, Nobuo; Sanada, Akira

2018-02-01

This paper is concerned with the generation of a quiet space in a rectangular cavity using active wave control methodology. It is the purpose of this paper to present the wave filtering method for a rectangular cavity using multiple microphones and its application to an adaptive feedforward control system. Firstly, the transfer matrix method is introduced for describing the wave dynamics of the sound field, and then feedforward control laws for eliminating transmitted waves is derived. Furthermore, some numerical simulations are conducted that show the best possible result of active wave control. This is followed by the derivation of the wave filtering equations that indicates the structure of the wave filter. It is clarified that the wave filter consists of three portions; modal group filter, rearrangement filter and wave decomposition filter. Next, from a numerical point of view, the accuracy of the wave decomposition filter which is expressed as a function of frequency is investigated using condition numbers. Finally, an experiment on the adaptive feedforward control system using the wave filter is carried out, demonstrating that a quiet space is generated in the target space by the proposed method.

The Brazilian version of the Constant-Murley Score (CMS-BR): convergent and construct validity, internal consistency, and unidimensionality.

Science.gov (United States)

Barreto, Rodrigo Py Gonçalves; Barbosa, Marcus Levi Lopes; Balbinotti, Marcos Alencar Abaide; Mothes, Fernando Carlos; da Rosa, Luís Henrique Telles; Silva, Marcelo Faria

2016-01-01

To translate and culturally adapt the CMS and assess the validity of the Brazilian version (CMS-BR). The translation was carried out according to the back-translation method by four independent translators. The produced versions were synthesized through extensive analysis and by consensus of an expert committee, reaching a final version used for the cultural adaptation. A field test was conducted with 30 subjects in order to obtain semantic considerations. For the psychometric analyzes, the sample was increased to 110 participants who answered two instruments: CMS-BR and the Disabilities of the Arm, shoulder and Hand (DASH). The CMS-BR and DASH score range from 0 to 100 points. For the first, higher points reflect better function and for the latter, the inverse is true. The validity was verified by Pearson's correlation test, the unidimensionality by factorial analysis, and the internal consistency by Cronbach's alpha. The explained variance was 60.28% with factor loadings ranging from 0.60 to 0.91. The CMS-BR exhibited strong negative correlation with the DASH score (-0.82, p  CMS was satisfactorily adapted for Brazilian Portuguese and demonstrated evidence of validity that allows its use in this population.

Mixed-integrator-based bi-quad cell for designing a continuous time filter

International Nuclear Information System (INIS)

Chen Yong; Zhou Yumei

2010-01-01

A new mixed-integrator-based bi-quad cell is proposed. An alternative synthesis mechanism of complex poles is proposed compared with source-follower-based bi-quad cells which is designed applying the positive feedback technique. Using the negative feedback technique to combine different integrators, the proposed bi-quad cell synthesizes complex poles for designing a continuous time filter. It exhibits various advantages including compact topology, high gain, no parasitic pole, no CMFB circuit, and high capability. The fourth-order Butterworth lowpass filter using the proposed cells has been fabricated in 0.18 μm CMOS technology. The active area occupied by the filter with test buffer is only 200 x 170 μm 2 . The proposed filter consumes a low power of 201 μW and achieves a 68.5 dB dynamic range. (semiconductor integrated circuits)

Multi-Flight-Phase GPS Navigation Filter Applications to Terrestrial Vehicle Navigation and Positioning

Science.gov (United States)

Park, Young W.; Montez, Moises N.

1994-01-01

A candidate onboard space navigation filter demonstrated excellent performance (less than 8 meter level RMS semi-major axis accuracy) in performing orbit determination of a low-Earth orbit Explorer satellite using single-frequency real GPS data. This performance is significantly better than predicted by other simulation studies using dual-frequency GPS data. The study results revealed the significance of two new modeling approaches evaluated in the work. One approach introduces a single-frequency ionospheric correction through pseudo-range and phase range averaging implementation. The other approach demonstrates a precise axis-dependent characterization of dynamic sample space uncertainty to compute a more accurate Kalman filter gain. Additionally, this navigation filter demonstrates a flexibility to accommodate both perturbational dynamic and observational biases required for multi-flight phase and inhomogeneous application environments. This paper reviews the potential application of these methods and the filter structure to terrestrial vehicle and positioning applications. Both the single-frequency ionospheric correction method and the axis-dependent state noise modeling approach offer valuable contributions in cost and accuracy improvements for terrestrial GPS receivers. With a modular design approach to either 'plug-in' or 'unplug' various force models, this multi-flight phase navigation filter design structure also provides a versatile GPS navigation software engine for both atmospheric and exo-atmospheric navigation or positioning use, thereby streamlining the flight phase or application-dependent software requirements. Thus, a standardized GPS navigation software engine that can reduce the development and maintenance cost of commercial GPS receivers is now possible.

Hybrid three-dimensional variation and particle filtering for nonlinear systems

International Nuclear Information System (INIS)

Leng Hong-Ze; Song Jun-Qiang

2013-01-01

This work addresses the problem of estimating the states of nonlinear dynamic systems with sparse observations. We present a hybrid three-dimensional variation (3DVar) and particle piltering (PF) method, which combines the advantages of 3DVar and particle-based filters. By minimizing the cost function, this approach will produce a better proposal distribution of the state. Afterwards the stochastic resampling step in standard PF can be avoided through a deterministic scheme. The simulation results show that the performance of the new method is superior to the traditional ensemble Kalman filtering (EnKF) and the standard PF, especially in highly nonlinear systems

Braile vena cava filter and greenfield filter in terms of centralization.

Science.gov (United States)

de Godoy, José Maria Pereira; Menezes da Silva, Adinaldo A; Reis, Luis Fernando; Miquelin, Daniel; Torati, José Luis Simon

2013-01-01

The aim of this study was to evaluate complications experienced during implantation of the Braile Vena Cava filter (VCF) and the efficacy of the centralization mechanism of the filter. This retrospective cohort study evaluated all Braile Biomédica VCFs implanted from 2004 to 2009 in Hospital de Base Medicine School in São José do Rio Preto, Brazil. Of particular concern was the filter's symmetry during implantation and complications experienced during the procedure. All the angiographic examinations performed during the implantation of the filters were analyzed in respect to the following parameters: migration of the filter, non-opening or difficulties in the implantation and centralization of the filter. A total of 112 Braile CVFs were implanted and there were no reports of filter opening difficulties or in respect to migration. Asymmetry was observed in 1/112 (0.9%) cases. A statistically significant difference was seen on comparing historical data on decentralization of the Greenfield filter with the data of this study. The Braile Biomédico filter is an evolution of the Greenfield filter providing improved embolus capture and better implantation symmetry.

Solar-blind ultraviolet band-pass filter based on metal—dielectric multilayer structures

International Nuclear Information System (INIS)

Wang Tian-Jiao; Xu Wei-Zong; Lu Hai; Ren Fang-Fang; Chen Dun-Jun; Zhang Rong; Zheng You-Dou

2014-01-01

Solar-blind ultraviolet (UV) band-pass filter has significant value in many scientific, commercial, and military applications, in which the detection of weak UV signal against a strong background of solar radiation is required. In this work, a solar-blind filter is designed based on the concept of “transparent metal”. The filter consisting of Al/SiO 2 multilayers could exhibit a high transmission in the solar-blind wavelength region and a wide stopband extending from near-ultraviolet to infrared wavelength range. The central wavelength, bandwidth, Q factor, and rejection ratio of the passband are numerically studied as a function of individual layer thickness and multilayer period. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

An object-oriented language-database integration model: The composition filters approach

NARCIS (Netherlands)

Aksit, Mehmet; Bergmans, Lodewijk; Vural, Sinan; Vural, S.

1991-01-01

This paper introduces a new model, based on so-called object-composition filters, that uniformly integrates database-like features into an object-oriented language. The focus is on providing persistent dynamic data structures, data sharing, transactions, multiple views and associative access,

An Object-Oriented Language-Database Integration Model: The Composition-Filters Approach

NARCIS (Netherlands)

Aksit, Mehmet; Bergmans, Lodewijk; Vural, S.; Vural, Sinan; Lehrmann Madsen, O.

1992-01-01

This paper introduces a new model, based on so-called object-composition filters, that uniformly integrates database-like features into an object-oriented language. The focus is on providing persistent dynamic data structures, data sharing, transactions, multiple views and associative access,

Distinct interactions of Na+ and Ca2+ ions with the selectivity filter of the bacterial sodium channel NaVAb

International Nuclear Information System (INIS)

Ke, Song; Zangerl, Eva-Maria; Stary-Weinzinger, Anna

2013-01-01

Highlights: ► Ca 2+ translocates slowly in the filter, due to lack of “loose” knock-on mechanism. ► Identification of a high affinity binding site in Na V Ab selectivity filter. ► Changes of EEEE locus triggered by electrostatic interactions with Ca 2+ ions. -- Abstract: Rapid and selective ion transport is essential for the generation and regulation of electrical signaling pathways in living organisms. In this study, we use molecular dynamics simulations and free energy calculations to investigate how the bacterial sodium channel Na V Ab (Arcobacter butzleri) differentiates between Na + and Ca 2+ ions. Multiple nanosecond molecular dynamics simulations revealed distinct binding patterns for these two cations in the selectivity filter and suggested a high affinity calcium binding site formed by backbone atoms of residues Leu-176 and Thr-175 (S CEN ) in the sodium channel selectivity filter

Kalman filtering techniques for reducing variance of digital speckle displacement measurement noise

Institute of Scientific and Technical Information of China (English)

Donghui Li; Li Guo

2006-01-01

@@ Target dynamics are assumed to be known in measuring digital speckle displacement. Use is made of a simple measurement equation, where measurement noise represents the effect of disturbances introduced in measurement process. From these assumptions, Kalman filter can be designed to reduce variance of measurement noise. An optical and analysis system was set up, by which object motion with constant displacement and constant velocity is experimented with to verify validity of Kalman filtering techniques for reduction of measurement noise variance.

State and parameter estimation of the heat shock response system using Kalman and particle filters.

Science.gov (United States)

Liu, Xin; Niranjan, Mahesan

2012-06-01

Traditional models of systems biology describe dynamic biological phenomena as solutions to ordinary differential equations, which, when parameters in them are set to correct values, faithfully mimic observations. Often parameter values are tweaked by hand until desired results are achieved, or computed from biochemical experiments carried out in vitro. Of interest in this article, is the use of probabilistic modelling tools with which parameters and unobserved variables, modelled as hidden states, can be estimated from limited noisy observations of parts of a dynamical system. Here we focus on sequential filtering methods and take a detailed look at the capabilities of three members of this family: (i) extended Kalman filter (EKF), (ii) unscented Kalman filter (UKF) and (iii) the particle filter, in estimating parameters and unobserved states of cellular response to sudden temperature elevation of the bacterium Escherichia coli. While previous literature has studied this system with the EKF, we show that parameter estimation is only possible with this method when the initial guesses are sufficiently close to the true values. The same turns out to be true for the UKF. In this thorough empirical exploration, we show that the non-parametric method of particle filtering is able to reliably estimate parameters and states, converging from initial distributions relatively far away from the underlying true values. Software implementation of the three filters on this problem can be freely downloaded from http://users.ecs.soton.ac.uk/mn/HeatShock

Application of Kalman Filter for Estimating a Process Disturbance in a Building Space

Directory of Open Access Journals (Sweden)

Deuk-Woo Kim

2017-10-01

Full Text Available This paper addresses an application of the Kalman filter for estimating a time-varying process disturbance in a building space. The process disturbance means a synthetic composite of heat gains and losses caused by internal heat sources e.g., people, lights, equipment, and airflows. It is difficult to measure and quantify the internal heat sources and airflows due to their dynamic nature and time-lag impact on indoor environment. To address this issue, a Kalman filter estimation method was used in this study. The Kalman filtering is well suited for situations when state variables of interest cannot be measured. Based on virtual and real experiments conducted in this study, it was found that the Kalman filter can be used to estimate the time-varying process disturbance in a building space.

Balanced microwave filters

CERN Document Server

Hong, Jiasheng; Medina, Francisco; Martiacuten, Ferran

2018-01-01

This book presents and discusses strategies for the design and implementation of common-mode suppressed balanced microwave filters, including, narrowband, wideband, and ultra-wideband filters This book examines differential-mode, or balanced, microwave filters by discussing several implementations of practical realizations of these passive components. Topics covered include selective mode suppression, designs based on distributed and semi-lumped approaches, multilayer technologies, defect ground structures, coupled resonators, metamaterials, interference techniques, and substrate integrated waveguides, among others. Divided into five parts, Balanced Microwave Filters begins with an introduction that presents the fundamentals of balanced lines, circuits, and networks. Part 2 covers balanced transmission lines with common-mode noise suppression, including several types of common-mode filters and the application of such filters to enhance common-mode suppression in balanced bandpass filters. Next, Part 3 exa...

Backflushable filter insert

International Nuclear Information System (INIS)

Keith, R.C.; Vandenberg, T.; Randolph, M.C.; Lewis, T.B.; Gillis, P.J. Jr.

1988-01-01

Filter elements are mounted on a tube plate beneath an accumulator chamber whose wall is extended by skirt and flange to form a closure for the top of pressure vessel. The accumulator chamber is annular around a central pipe which serves as the outlet for filtered water passing from the filter elements. The chamber contains filtered compressed air from supply. Periodically the filtration of water is stopped and vessel is drained. Then a valve is opened, allowing the accumulated air to flow from chamber up a pipe and down pipe, pushing the filtered water from pipe back through the filter elements to clean them. The accumulator chamber is so proportioned, relative to the volume of the system communicating therewith during backflushing, that the equilibrium pressure during backflushing cannot exceed the pressure rating of the vessel. However a line monitors the pressure at the top of the vessel, and if it rises too far a bleed valve is automatically opened to depressurise the system. The chamber is intended to replace the lid of an existing vessel to convert a filter using filter aid to one using permanent filter elements. (author)

Filter replacement lifetime prediction

Science.gov (United States)

Hamann, Hendrik F.; Klein, Levente I.; Manzer, Dennis G.; Marianno, Fernando J.

2017-10-25

Methods and systems for predicting a filter lifetime include building a filter effectiveness history based on contaminant sensor information associated with a filter; determining a rate of filter consumption with a processor based on the filter effectiveness history; and determining a remaining filter lifetime based on the determined rate of filter consumption. Methods and systems for increasing filter economy include measuring contaminants in an internal and an external environment; determining a cost of a corrosion rate increase if unfiltered external air intake is increased for cooling; determining a cost of increased air pressure to filter external air; and if the cost of filtering external air exceeds the cost of the corrosion rate increase, increasing an intake of unfiltered external air.

Anti-clogging filter system

Science.gov (United States)

Brown, Erik P.

2015-05-19

An anti-clogging filter system for filtering a fluid containing large particles and small particles includes an enclosure with at least one individual elongated tubular filter element in the enclosure. The individual elongated tubular filter element has an internal passage, a closed end, an open end, and a filtering material in or on the individual elongated tubular filter element. The fluid travels through the open end of the elongated tubular element and through the internal passage and through the filtering material. An anti-clogging element is positioned on or adjacent the individual elongated tubular filter element and provides a fluid curtain that preferentially directs the larger particulates to one area of the filter material allowing the remainder of the filter material to remain more efficient.

Selection vector filter framework

Science.gov (United States)

Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.

2003-10-01

We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.

Performance Analysis of Local Ensemble Kalman Filter

Science.gov (United States)

Tong, Xin T.

2018-03-01

Ensemble Kalman filter (EnKF) is an important data assimilation method for high-dimensional geophysical systems. Efficient implementation of EnKF in practice often involves the localization technique, which updates each component using only information within a local radius. This paper rigorously analyzes the local EnKF (LEnKF) for linear systems and shows that the filter error can be dominated by the ensemble covariance, as long as (1) the sample size exceeds the logarithmic of state dimension and a constant that depends only on the local radius; (2) the forecast covariance matrix admits a stable localized structure. In particular, this indicates that with small system and observation noises, the filter error will be accurate in long time even if the initialization is not. The analysis also reveals an intrinsic inconsistency caused by the localization technique, and a stable localized structure is necessary to control this inconsistency. While this structure is usually taken for granted for the operation of LEnKF, it can also be rigorously proved for linear systems with sparse local observations and weak local interactions. These theoretical results are also validated by numerical implementation of LEnKF on a simple stochastic turbulence in two dynamical regimes.

Development of an optimal automatic control law and filter algorithm for steep glideslope capture and glideslope tracking

Science.gov (United States)

Halyo, N.

1976-01-01

A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.

Nonlinear Vibration Signal Tracking of Large Offshore Bridge Stayed Cable Based on Particle Filter

Directory of Open Access Journals (Sweden)

Ye Qingwei

2015-12-01

Full Text Available The stayed cables are key stress components of large offshore bridge. The fault detection of stayed cable is very important for safe of large offshore bridge. A particle filter model and algorithm of nonlinear vibration signal are used in this paper. Firstly, the particle filter model of stayed cable of large offshore bridge is created. Nonlinear dynamic model of the stayed-cable and beam coupling system is dispersed in temporal dimension by using the finite difference method. The discrete nonlinear vibration equations of any cable element are worked out. Secondly, a state equation of particle filter is fitted by least square algorithm from the discrete nonlinear vibration equations. So the particle filter algorithm can use the accurate state equations. Finally, the particle filter algorithm is used to filter the vibration signal of bridge stayed cable. According to the particle filter, the de-noised vibration signal can be tracked and be predicted for a short time accurately. Many experiments are done at some actual bridges. The simulation experiments and the actual experiments on the bridge stayed cables are all indicating that the particle filter algorithm in this paper has good performance and works stably.

Changing ventilation filters

International Nuclear Information System (INIS)

Hackney, S.

1980-01-01

A filter changing unit has a door which interlocks with the door of a filter chamber so as to prevent contamination of the outer surfaces of the doors by radioactive material collected on the filter element and a movable support which enables a filter chamber thereonto to be stored within the unit in such a way that the doors of the unit and the filter chamber can be replaced. The door pivots and interlocks with another door by means of a bolt, a seal around the periphery lip of the first door engages the periphery of the second door to seal the gap. A support pivots into a lower filter element storage position. Inspection windows and glove ports are provided. The unit is releasably connected to the filter chamber by bolts engaging in a flange provided around an opening. (author)

Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter

Directory of Open Access Journals (Sweden)

Ming Liu

2015-01-01

Full Text Available This paper is concerned with the topic of gravity matching aided inertial navigation technology using Kalman filter. The dynamic state space model for Kalman filter is constructed as follows: the error equation of the inertial navigation system is employed as the process equation while the local gravity model based on 9-point surface interpolation is employed as the observation equation. The unscented Kalman filter is employed to address the nonlinearity of the observation equation. The filter is refined in two ways as follows. The marginalization technique is employed to explore the conditionally linear substructure to reduce the computational load; specifically, the number of the needed sigma points is reduced from 15 to 5 after this technique is used. A robust technique based on Chi-square test is employed to make the filter insensitive to the uncertainties in the above constructed observation model. Numerical simulation is carried out, and the efficacy of the proposed method is validated by the simulation results.

Analysis of commodity prices with the particle filter

International Nuclear Information System (INIS)

Aiube, Fernando Antonio Lucena; Baidya, Tara Keshar Nanda; Tito, Edison Americo Huarsaya

2008-01-01

The behavior of commodities prices is fundamental to real-asset investment decisions, hedging, and pricing financial derivatives. Schwartz and Smith [Schwartz, E.S., Smith, J.E. (2000). Short term-variations and long-term dynamics in commodity prices. Management Science, 46, 893-911.] proposed a two-factor model for describing the stochastic processes of commodity prices, in which the two factors are short-term variations and equilibrium prices. These are both unobserved state variables that are estimated using the Kalman filter. The estimation is based on the observation of future prices for different maturities. The authors have carried out this process without incorporating jumps in the short-term variation of prices. Here we aim to demonstrate that the inclusion of jumps better explains the behavior of oil prices, and in fact creates difficulties in the estimation of state variables. This is because the variables become non-Gaussian so the Kalman filter is not recommended. Another methodology, called the particle filter, is more suitable in this case, and we describe its application in this article

Dynamic range meter for radiofrequency amplifiers

Directory of Open Access Journals (Sweden)

Drozd S. S.

2009-04-01

Full Text Available The new measurement setup having increased on 20…30 dB the own dynamic range in comparison with the standard circuit of the dynamic range meter is offered and the rated value of an error bringing by setup in the worst case does not exceed ± 2,8 dB. The measurement setup can be applied also to determinate levels of intermodulation components average power amplifiers and powerful amplifiers of a low-frequency at replacement of the quartz filter on meeting low-frequency the LC-filter and the spectrum analyzer.

A high dynamic range programmable CMOS front-end filter with a tuning range from 1850 to 2400 MHz

DEFF Research Database (Denmark)

Christensen, Kåre Tais; Lee, Thomas H.; Bruun, Erik

2005-01-01

This paper presents a highly programmable front-end filter and amplifier intended to replace SAW filters and low noise amplifiers (LNA) in multi-mode direct conversion radio receivers. The filter has a 42 MHz bandwidth, is tunable from 1850 to 2400 MHz, achieves a 5.8 dB NF, -25 dBm in-band 1-d...

Effect of Post-Reconstruction Gaussian Filtering on Image Quality and Myocardial Blood Flow Measurement with N-13 Ammonia PET

Directory of Open Access Journals (Sweden)

Hyeon Sik Kim

2014-10-01

Full Text Available Objective(s: In order to evaluate the effect of post-reconstruction Gaussian filtering on image quality and myocardial blood flow (MBF measurement by dynamic N-13 ammonia positron emission tomography (PET, we compared various reconstruction and filtering methods with image characteristics. Methods: Dynamic PET images of three patients with coronary artery disease (male-female ratio of 2:1; age: 57, 53, and 76 years were reconstructed, using filtered back projection (FBP and ordered subset expectation maximization (OSEM methods. OSEM reconstruction consisted of OSEM_2I, OSEM_4I, and OSEM_6I with 2, 4, and 6 iterations, respectively. The images, reconstructed and filtered by Gaussian filters of 5, 10, and 15 mm, were obtained, as well as non-filtered images. Visual analysis of image quality (IQ was performed using a 3-grade scoring system by 2 independent readers, blinded to the reconstruction and filtering methods of stress images. Then, signal-to-noise ratio (SNR was calculated by noise and contrast recovery (CR. Stress and rest MBF and coronary flow reserve (CFR were obtained for each method. IQ scores, stress and rest MBF, and CFR were compared between the methods, using Chi-square and Kruskal-Wallis tests. Results: In the visual analysis, IQ was significantly higher by 10 mm Gaussian filtering, compared to other sizes of filter (PP=0.923 and 0.855 for readers 1 and 2, respectively. SNR was significantly higher in 10 mm Gaussian filter. There was a significant difference in stress and rest MBF between several vascular territories. However CFR was not significantly different according to various filtering methods. Conclusion: Post-reconstruction Gaussian filtering with a filter size of 10 mm significantly enhances the IQ of N-13 ammonia PET-CT, without changing the results of CFR calculation. .

Effect of Post-Reconstruction Gaussian Filtering on Image Quality and Myocardial Blood Flow Measurement with N-13 Ammonia PET

International Nuclear Information System (INIS)

Kim, Hyeon Sik; Cho, Sang-Geon; Kim, Ju Han; Kwon, Seong Young; Lee, Byeong-il; Bom, Hee-Seung

2014-01-01

In order to evaluate the effect of post-reconstruction Gaussian filtering on image quality and myocardial blood flow (MBF) measurement by dynamic N-13 ammonia positron emission tomography (PET), we compared various reconstruction and filtering methods with image characteristics. Dynamic PET images of three patients with coronary artery disease (male-female ratio of 2:1; age: 57, 53, and 76 years) were reconstructed, using filtered back projection (FBP) and ordered subset expectation maximization (OSEM) methods. OSEM reconstruction consisted of OSEM-2I, OSEM-4I, and OSEM-6I with 2, 4, and 6 iterations, respectively. The images, reconstructed and filtered by Gaussian filters of 5, 10, and 15 mm, were obtained, as well as non-filtered images. Visual analysis of image quality (IQ) was performed using a 3-grade scoring system by 2 independent readers, blinded to the reconstruction and filtering methods of stress images. Then, signal-to-noise ratio (SNR) was calculated by noise and contrast recovery (CR). Stress and rest MBF and coronary flow reserve (CFR) were obtained for each method. IQ scores, stress and rest MBF, and CFR were compared between the methods, using Chi-square and Kruskal-Wallis tests. In the visual analysis, IQ was significantly higher by 10 mm Gaussian filtering, compared to other sizes of filter (P<0.001 for both readers). However, no significant difference of IQ was found between FBP and various numbers of iteration in OSEM (P=0.923 and 0.855 for readers 1 and 2, respectively). SNR was significantly higher in 10 mm Gaussian filter. There was a significant difference in stress and rest MBF between several vascular territories. However CFR was not significantly different according to various filtering methods. Post-reconstruction Gaussian filtering with a filter size of 10 mm significantly enhances the IQ of N-13 ammonia PET-CT, without changing the results of CFR calculation

Device for automatic filter changing. Einrichtung zum selbsttaetigen Wechseln eines Filters

Energy Technology Data Exchange (ETDEWEB)

Matschoss, V; Naschwitz, A; Wild, H

1984-01-05

A filter is moved from a store to an aerosol pipe by a lifting device and is clamped there. At the end of the operating period, the lifting device moves a new filter to a parking place. Control is from limit switches of the lifting, clamping and thrust devices and the position control of the store is by the limit switches. The filter changing device is enclosed in a gastight case, prevents blockage of a filter and makes it possible to set a certain operating period, to change the filter without interrupting the aerosol flow and to measure each filter in the sequence of operation outside the aerosol flow.

A generalized model via random walks for information filtering

Science.gov (United States)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-08-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation.

Interaction of Lyapunov vectors in the formulation of the nonlinear extension of the Kalman filter.

Science.gov (United States)

Palatella, Luigi; Trevisan, Anna

2015-04-01

When applied to strongly nonlinear chaotic dynamics the extended Kalman filter (EKF) is prone to divergence due to the difficulty of correctly forecasting the forecast error probability density function. In operational forecasting applications ensemble Kalman filters circumvent this problem with empirical procedures such as covariance inflation. This paper presents an extension of the EKF that includes nonlinear terms in the evolution of the forecast error estimate. This is achieved starting from a particular square-root implementation of the EKF with assimilation confined in the unstable subspace (EKF-AUS), that is, the span of the Lyapunov vectors with non-negative exponents. When the error evolution is nonlinear, the space where it is confined is no more restricted to the unstable and neutral subspace causing filter divergence. The algorithm presented here, denominated EKF-AUS-NL, includes the nonlinear terms in the error dynamics: These result from the nonlinear interaction among the leading Lyapunov vectors and account for all directions where the error growth may take place. Numerical results show that with the nonlinear terms included, filter divergence can be avoided. We test the algorithm on the Lorenz96 model, showing very promising results.

Sensory pollution from bag-type fiberglass ventilation filters: Conventional filter compared with filters containing various amounts of activated carbon

DEFF Research Database (Denmark)

Bekö, Gabriel; Fadeyi, M.O.; Clausen, Geo

2009-01-01

filter and three modifications of a bag-type fiberglass combination filter: the "Heavy" corresponded to a commercially available filter containing 400 g of carbon per square meter of filter area, the "Medium" contained half as much carbon (200 g/m(2)), and the "Light" contained a quarter as much carbon...

A Differential Geometric Approach to Nonlinear Filtering: The Projection Filter

NARCIS (Netherlands)

Brigo, D.; Hanzon, B.; LeGland, F.

1998-01-01

This paper presents a new and systematic method of approximating exact nonlinear filters with finite dimensional filters, using the differential geometric approach to statistics. The projection filter is defined rigorously in the case of exponential families. A convenient exponential family is

Filter and Filter Bank Design for Image Texture Recognition

Energy Technology Data Exchange (ETDEWEB)

Randen, Trygve

1997-12-31

The relevance of this thesis to energy and environment lies in its application to remote sensing such as for instance sea floor mapping and seismic pattern recognition. The focus is on the design of two-dimensional filters for feature extraction, segmentation, and classification of digital images with textural content. The features are extracted by filtering with a linear filter and estimating the local energy in the filter response. The thesis gives a review covering broadly most previous approaches to texture feature extraction and continues with proposals of some new techniques. 143 refs., 59 figs., 7 tabs.

HEPA Filter Vulnerability Assessment

International Nuclear Information System (INIS)

GUSTAVSON, R.D.

2000-01-01

This assessment of High Efficiency Particulate Air (HEPA) filter vulnerability was requested by the USDOE Office of River Protection (ORP) to satisfy a DOE-HQ directive to evaluate the effect of filter degradation on the facility authorization basis assumptions. Within the scope of this assessment are ventilation system HEPA filters that are classified as Safety-Class (SC) or Safety-Significant (SS) components that perform an accident mitigation function. The objective of the assessment is to verify whether HEPA filters that perform a safety function during an accident are likely to perform as intended to limit release of hazardous or radioactive materials, considering factors that could degrade the filters. Filter degradation factors considered include aging, wetting of filters, exposure to high temperature, exposure to corrosive or reactive chemicals, and exposure to radiation. Screening and evaluation criteria were developed by a site-wide group of HVAC engineers and HEPA filter experts from published empirical data. For River Protection Project (RPP) filters, the only degradation factor that exceeded the screening threshold was for filter aging. Subsequent evaluation of the effect of filter aging on the filter strength was conducted, and the results were compared with required performance to meet the conditions assumed in the RPP Authorization Basis (AB). It was found that the reduction in filter strength due to aging does not affect the filter performance requirements as specified in the AB. A portion of the HEPA filter vulnerability assessment is being conducted by the ORP and is not part of the scope of this study. The ORP is conducting an assessment of the existing policies and programs relating to maintenance, testing, and change-out of HEPA filters used for SC/SS service. This document presents the results of a HEPA filter vulnerability assessment conducted for the River protection project as requested by the DOE Office of River Protection

Potential for HEPA filter damage from water spray systems in filter plenums

Energy Technology Data Exchange (ETDEWEB)

Bergman, W. [Lawrence Livermore National Lab., CA (United States); Fretthold, J.K. [Rocky Flats Safe Sites of Colorado, Golden, CO (United States); Slawski, J.W. [Department of Energy, Germantown, MD (United States)

1997-08-01

The water spray systems in high efficiency particulate air (HEPA) filter plenums that are used in nearly all Department of Energy (DOE) facilities for protection against fire was designed under the assumption that the HEPA filters would not be damaged by the water sprays. The most likely scenario for filter damage involves filter plugging by the water spray, followed by the fan blowing out the filter medium. A number of controlled laboratory tests that were previously conducted in the late 1980s are reviewed in this paper to provide a technical basis for the potential HEPA filter damage by the water spray system in HEPA filter plenums. In addition to the laboratory tests, the scenario for BEPA filter damage during fires has also occurred in the field. A fire in a four-stage, BEPA filter plenum at Rocky Flats in 1980 caused the first three stages of BEPA filters to blow out of their housing and the fourth stage to severely bow. Details of this recently declassified fire are presented in this paper. Although these previous findings suggest serious potential problems exist with the current water spray system in filter plenums, additional studies are required to confirm unequivocally that DOE`s critical facilities are at risk. 22 refs., 15 figs.

Neutron Beam Filters

International Nuclear Information System (INIS)

Adib, M.

2011-01-01

The purpose of filters is to transmit neutrons with selected energy, while remove unwanted ones from the incident neutron beam. This reduces the background, and the number of spurious. The types of commonly used now-a-day neutron filters and their properties are discussed in the present work. There are three major types of neutron filters. The first type is filter of selective thermal neutron. It transmits the main reflected neutrons from a crystal monochromate, while reject the higher order contaminations accompanying the main one. Beams coming from the moderator always contain unwanted radiation like fast neutrons and gamma-rays which contribute to experimental background and to the biological hazard potential. Such filter type is called filter of whole thermal neutron spectrum. The third filter type is it transmits neutrons with energies in the resonance energy range (En . 1 KeV). The main idea of such neutron filter technique is the use of large quantities of a certain material which have the deep interference minima in its total neutron cross-section. By transmitting reactor neutrons through bulk layer of such material, one can obtain the quasimonochromatic neutron lines instead of white reactor spectrum.

Miniaturized dielectric waveguide filters

OpenAIRE

Sandhu, MY; Hunter, IC

2016-01-01

Design techniques for a new class of integrated monolithic high-permittivity ceramic waveguide filters are presented. These filters enable a size reduction of 50% compared to air-filled transverse electromagnetic filters with the same unloaded Q-factor. Designs for Chebyshev and asymmetric generalised Chebyshev filter and a diplexer are presented with experimental results for an 1800 MHz Chebyshev filter and a 1700 MHz generalised Chebyshev filter showing excellent agreement with theory.

Hybrid Filter Membrane

Science.gov (United States)

Laicer, Castro; Rasimick, Brian; Green, Zachary

2012-01-01

Cabin environmental control is an important issue for a successful Moon mission. Due to the unique environment of the Moon, lunar dust control is one of the main problems that significantly diminishes the air quality inside spacecraft cabins. Therefore, this innovation was motivated by NASA s need to minimize the negative health impact that air-suspended lunar dust particles have on astronauts in spacecraft cabins. It is based on fabrication of a hybrid filter comprising nanofiber nonwoven layers coated on porous polymer membranes with uniform cylindrical pores. This design results in a high-efficiency gas particulate filter with low pressure drop and the ability to be easily regenerated to restore filtration performance. A hybrid filter was developed consisting of a porous membrane with uniform, micron-sized, cylindrical pore channels coated with a thin nanofiber layer. Compared to conventional filter media such as a high-efficiency particulate air (HEPA) filter, this filter is designed to provide high particle efficiency, low pressure drop, and the ability to be regenerated. These membranes have well-defined micron-sized pores and can be used independently as air filters with discreet particle size cut-off, or coated with nanofiber layers for filtration of ultrafine nanoscale particles. The filter consists of a thin design intended to facilitate filter regeneration by localized air pulsing. The two main features of this invention are the concept of combining a micro-engineered straight-pore membrane with nanofibers. The micro-engineered straight pore membrane can be prepared with extremely high precision. Because the resulting membrane pores are straight and not tortuous like those found in conventional filters, the pressure drop across the filter is significantly reduced. The nanofiber layer is applied as a very thin coating to enhance filtration efficiency for fine nanoscale particles. Additionally, the thin nanofiber coating is designed to promote capture of

Estimating ice-affected streamflow by extended Kalman filtering

Science.gov (United States)

Holtschlag, D.J.; Grewal, M.S.

1998-01-01

An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

Study on the structure of bridge surface of the micro Fabry-Perot cavity tunable filter

International Nuclear Information System (INIS)

Meng Qinghua; Luo Huan; Bao Shiwei; Zhou Yifan; Chen Sihai

2011-01-01

Micro Fabry-Perot cavity tunable filters are widely applied in the area of Pushbroom Hyperspectral imaging, DWDM optical communication system and self-adaptive optics. With small volume, lower consumption and cost, the Micro Fabry-Perot cavity tunable filter can realize superior response speed, large spectral range, high definition and high reliability. By deposition metal membrane on silicon chip by MEMS technology, the micro Fabry-Perot cavity has been achieved, which is actuated by electrostatic force and can realize the function of an optical filter. In this paper, the micro-bridge structure of the micro Fabry-Perot cavity tunable filter has been studied. Finite element analysis software COMSOL Multiphysics has been adopted to design the structure of the micro-bridge of the micro filter. In order to simulate the working mechanism of the micro Fabry-Perot cavity and study the electrical and mechanical characteristics of the micro tunable filter,the static and dynamic characteriastics are analyzed, such as stress, displacement, transient response, etc. The corresponding parameters of the structure are considered as well by optimizition the filter's sustain structure.

Kalman Filter for Estimation of Sensor Acceleration Using Six - axis Inertial Sensor

International Nuclear Information System (INIS)

Lee, Jung Keun

2015-01-01

Although an accelerometer is a sensor that measures acceleration, it cannot be used by itself to measure the acceleration when the orientation of the sensor changes. This paper introduces a Kalman filter for the estimation of a sensor acceleration based on a six-axis inertial sensor (i.e., a three-axis accelerometer and three-axis gyroscope). The novelty of the proposed Kalman filter lies in the fact that its state vector includes not only the tilt angle variable but also the sensor acceleration. Thus, the filter can explicitly estimate the latter with a high accuracy. The accuracy of acceleration estimates were validated experimentally under three different dynamic conditions, using an optical motion capture system. It could be concluded that the performance of the proposed Kalman filter was comparable to that of the state-of-the-art estimation algorithm employed by the Xsens MTw. The proposed algorithm may be more suitable than inertial/magnetic sensor-based algorithms for various applications adopting six-axis inertial sensors

Software filtering method to suppress spike pulse interference in multi-channel scaler

International Nuclear Information System (INIS)

Huang Shun; Zhao Xiuliang; Li Zhiqiang; Zhao Yanhui

2008-01-01

In the test on anti-jamming function of a multi-channel scaler, we found that the spike pulse interference on the second level counter caused by the motor start-stop operations brings a major count error. There are resolvable characteristics between effective signal and spike pulse interference, and multi-channel hardware filtering circuit is too huge and can't filter thoroughly, therefore we designed a software filtering method. In this method based on C8051F020 MCU, we dynamically store sampling values of one channel in only a one-byte variable and distinguish the rise-trail edge of a signal and spike pulse interference because of value changes of the variable. Test showed that the filtering software method can solve the error counting problem of the multi-channel scaler caused by the motor start-stop operations. The flow chart and source codes of the method were detailed in this paper. (authors)

Original article Multidimensional versus unidimensional models of emotional contagion: the Emotional Contagion Scale in a Polish sample

Directory of Open Access Journals (Sweden)

Monika Wróbel

2014-07-01

Full Text Available Background The Emotional Contagion Scale (ECS measures individual differences in susceptibility to catching emotions expressed by others. Although initially the scale was reported to have a unidimensional structure, recent validation studies have suggested that the concept of emotional contagion is multidimensional. The aim of the study was therefore to test whether the structure of the ECS in a Polish sample corresponds with that observed for other non-English speaking populations. Participants and procedure The scale, translated into Polish, was completed by 633 university students in four independent samples. To investigate the factor structure of the ECS, confirmatory factor analyses of five alternative models were conducted. Results The results supported a multifaceted solution, which confirmed that susceptibility to emotional contagion may be differentiated not only across positive vs. negative states but also across discrete emotions. Moreover, the verification of internal consistency, test-retest reliability and construct validity of the Polish version indicated that its parameters are acceptable and comparable with the characteristics of other adaptations. Conclusions The Polish ECS, together with other adaptations of the scale, shows that the construct developed in the United States can be successfully measured in other cultural contexts. Thus, the Polish version can be treated as a useful tool for measuring individual differences in susceptibility to emotional contagion.

Sampled data CT system including analog filter and compensating digital filter

International Nuclear Information System (INIS)

Glover, G. H.; DallaPiazza, D. G.; Pelc, N. J.

1985-01-01

A CT scanner in which the amount of x-ray information acquired per unit time is substantially increased by using a continuous-on x-ray source and a sampled data system with the detector. An analog filter is used in the sampling system for band limiting the detector signal below the highest frequency of interest, but is a practically realizable filter and is therefore non-ideal. A digital filter is applied to the detector data after digitization to compensate for the characteristics of the analog filter, and to provide an overall filter characteristic more nearly like the ideal

Magneto-Optic Fiber Gratings Useful for Dynamic Dispersion Management and Tunable Comb Filtering

International Nuclear Information System (INIS)

Bao-Jian, Wu; Xin, Lu; Kun, Qiu

2010-01-01

Intelligent control of dispersion management and tunable comb filtering in optical network applications can be performed by using magneto-optic fiber Bragg gratings (MFBGs). When a nonuniform magnetic field is applied to the MFBG with a constant grating period, the resulting grating response is equivalent to that of a conventional chirped grating. Under a linearly nonuniform magnetic field along the grating, a linear dispersion is achieved in the grating bandgap and the maximal dispersion slope can come to 1260 ps/nm 2 for a 10-mm-long fiber grating at 1550 nm window. Similarly, a Gaussian-apodizing sampled MFBG is also useful for magnetically tunable comb filtering, with potential application to clock recovery from return-to-zero optical signals and optical carrier tracking. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Quick-change filter cartridge

Science.gov (United States)

Rodgers, John C.; McFarland, Andrew R.; Ortiz, Carlos A.

1995-01-01

A quick-change filter cartridge. In sampling systems for measurement of airborne materials, a filter element is introduced into the sampled airstream such that the aerosol constituents are removed and deposited on the filter. Fragile sampling media often require support in order to prevent rupture during sampling, and careful mounting and sealing to prevent misalignment, tearing, or creasing which would allow the sampled air to bypass the filter. Additionally, handling of filter elements may introduce cross-contamination or exposure of operators to toxic materials. Moreover, it is desirable to enable the preloading of filter media into quick-change cartridges in clean laboratory environments, thereby simplifying and expediting the filter-changing process in the field. The quick-change filter cartridge of the present invention permits the application of a variety of filter media in many types of instruments and may also be used in automated systems. The cartridge includes a base through which a vacuum can be applied to draw air through the filter medium which is located on a porous filter support and held there by means of a cap which forms an airtight seal with the base. The base is also adapted for receiving absorbing media so that both particulates and gas-phase samples may be trapped for investigation, the latter downstream of the aerosol filter.

Data assimilation with an extended Kalman filter for impact-produced shock-wave dynamics

International Nuclear Information System (INIS)

Kao, Jim; Flicker, Dawn; Henninger, Rudy; Frey, Sarah; Ghil, Michael; Ide, Kayo

2004-01-01

Model assimilation of data strives to determine optimally the state of an evolving physical system from a limited number of observations. The present study represents the first attempt of applying the extended Kalman filter (EKF) method of data assimilation to shock-wave dynamics induced by a high-speed impact. EKF solves the full nonlinear state evolution and estimates its associated error-covariance matrix in time. The state variables obtained by the blending of past model evolution with currently available data, along with their associated minimized errors (or uncertainties), are then used as initial conditions for further prediction until the next time at which data becomes available. In this study, a one-dimensional (1D) finite-difference code is used along with data measured from a 1D flyer plate experiment. An ensemble simulation suggests that the nonlinearity of the modeled system can be reasonably tracked by EKF. The results demonstrate that the EKF assimilation of a limited amount of pressure data, measured at the middle of the target plate alone, helps track the evolution of all the state variables. The fidelity of EKF is further investigated with numerically generated synthetic data from so-called 'identical-twin experiments', in which the true state is known and various measurement techniques and strategies can be made easily simulated. We find that the EKF method can effectively assimilate the density fields, which are distributed sparsely in time to mimic radiographic data, into the modeled system

Improved Kalman Filter-Based Speech Enhancement with Perceptual Post-Filtering

Institute of Scientific and Technical Information of China (English)

WEIJianqiang; DULimin; YANZhaoli; ZENGHui

2004-01-01

In this paper, a Kalman filter-based speech enhancement algorithm with some improvements of previous work is presented. A new technique based on spectral subtraction is used for separation speech and noise characteristics from noisy speech and for the computation of speech and noise Autoregressive (AR) parameters. In order to obtain a Kalman filter output with high audible quality, a perceptual post-filter is placed at the output of the Kalman filter to smooth the enhanced speech spectra.Extensive experiments indicate that this newly proposed method works well.

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Science.gov (United States)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated

Method for cleaning the filter pockets of dust gas filter systems

Energy Technology Data Exchange (ETDEWEB)

Margraf, A

1975-05-07

The invention deals with a method to clean filter pockets filled with dust gas. By a periodic to and fro air jet attached to a scavenging blower, a pulsed fluttering movement of the filter surface is obtained which releases the outer layers of dust. The charging of the filter pockets with scavenging air to clean the filter material can be carried out immediately on the pulsed admission with suitable time control.

Frame Filtering and Skipping for Point Cloud Data Video Transmission

Directory of Open Access Journals (Sweden)

Carlos Moreno

2017-01-01

Full Text Available Sensors for collecting 3D spatial data from the real world are becoming more important. They are a prime research area topic and have applications in consumer markets, such as medical, entertainment, and robotics. However, a primary concern with collecting this data is the vast amount of information being generated, and thus, needing to be processed before being transmitted. To address the issue, we propose the use of filtering methods and frame skipping. To collect the 3D spatial data, called point clouds, we used the Microsoft Kinect sensor. In addition, we utilized the Point Cloud Library to process and filter the data being generated by the Kinect. Two different computers were used: a client which collects, filters, and transmits the point clouds; and a server that receives and visualizes the point clouds. The client is also checking for similarity in consecutive frames, skipping those that reach a similarity threshold. In order to compare the filtering methods and test the effectiveness of the frame skipping technique, quality of service (QoS metrics such as frame rate and percentage of filter were introduced. These metrics indicate how well a certain combination of filtering method and frame skipping accomplishes the goal of transmitting point clouds from one location to another. We found that the pass through filter in conjunction with frame skipping provides the best relative QoS. However, results also show that there is still too much data for a satisfactory QoS. For a real-time system to provide reasonable end-to-end quality, dynamic compression and progressive transmission need to be utilized.

An Empirical Comparison between Two Recursive Filters for Attitude and Rate Estimation of Spinning Spacecraft

Science.gov (United States)

Harman, Richard R.

2006-01-01

The advantages of inducing a constant spin rate on a spacecraft are well known. A variety of science missions have used this technique as a relatively low cost method for conducting science. Starting in the late 1970s, NASA focused on building spacecraft using 3-axis control as opposed to the single-axis control mentioned above. Considerable effort was expended toward sensor and control system development, as well as the development of ground systems to independently process the data. As a result, spinning spacecraft development and their resulting ground system development stagnated. In the 1990s, shrinking budgets made spinning spacecraft an attractive option for science. The attitude requirements for recent spinning spacecraft are more stringent and the ground systems must be enhanced in order to provide the necessary attitude estimation accuracy. Since spinning spacecraft (SC) typically have no gyroscopes for measuring attitude rate, any new estimator would need to rely on the spacecraft dynamics equations. One estimation technique that utilized the SC dynamics and has been used successfully in 3-axis gyro-less spacecraft ground systems is the pseudo-linear Kalman filter algorithm. Consequently, a pseudo-linear Kalman filter has been developed which directly estimates the spacecraft attitude quaternion and rate for a spinning SC. Recently, a filter using Markley variables was developed specifically for spinning spacecraft. The pseudo-linear Kalman filter has the advantage of being easier to implement but estimates the quaternion which, due to the relatively high spinning rate, changes rapidly for a spinning spacecraft. The Markley variable filter is more complicated to implement but, being based on the SC angular momentum, estimates parameters which vary slowly. This paper presents a comparison of the performance of these two filters. Monte-Carlo simulation runs will be presented which demonstrate the advantages and disadvantages of both filters.

A Digital Image Denoising Algorithm Based on Gaussian Filtering and Bilateral Filtering

Directory of Open Access Journals (Sweden)

Piao Weiying

2018-01-01

Full Text Available Bilateral filtering has been applied in the area of digital image processing widely, but in the high gradient region of the image, bilateral filtering may generate staircase effect. Bilateral filtering can be regarded as one particular form of local mode filtering, according to above analysis, an mixed image de-noising algorithm is proposed based on Gaussian filter and bilateral filtering. First of all, it uses Gaussian filter to filtrate the noise image and get the reference image, then to take both the reference image and noise image as the input for range kernel function of bilateral filter. The reference image can provide the image’s low frequency information, and noise image can provide image’s high frequency information. Through the competitive experiment on both the method in this paper and traditional bilateral filtering, the experimental result showed that the mixed de-noising algorithm can effectively overcome staircase effect, and the filtrated image was more smooth, its textural features was also more close to the original image, and it can achieve higher PSNR value, but the amount of calculation of above two algorithms are basically the same.

Evaluation of the effect of media velocity on HEPA filter performance

International Nuclear Information System (INIS)

Alderman, Steven; Parsons, Michael; Hogancamp, Kristina; Norton, O. Perry; Waggoner, Charles

2007-01-01

Section FC of the ASME AG-1 Code addresses glass fiber HEPA filters and restricts the media velocity to a maximum of 2.54 cm/s (5 ft/min). Advances in filter media technology allow glass fiber HEPA filters to function at significantly higher velocities and still achieve HEPA performance. However, diffusional capture of particles < 100 nm is reduced at higher media velocities due to shorter residence times within the media matrix. Therefore, it is unlikely that higher media velocities for HEPA filters will be allowed without data to demonstrate the effect of media velocity on removal of particles in the smaller size classes. In order to address this issue, static testing has been conducted to generate performance related data and a range of dynamic testing has provided data regarding filter lifetimes, loading characteristics, changes in filter efficiency and the most penetrating particle size over time. Testing was conducted using 31 cm x 31 cm x 29 cm deep pleat HEPA filters supplied from two manufacturers. Testing was conducted at media velocities ranging from 2.0-4.5 cm/s with a solid aerosol challenge composed of potassium chloride. Two set of media velocity data were obtained for each filter type. In one set of evaluations, the maximum aerosol challenge particle size was limited to 3 μm, while particles above 3 μm were not constrained in the second set. This provided for considerable variability in the challenge mass mean diameter and overall mass loading rate. Results of this testing will be provided to the ASME AG-1 FC Committee for consideration in future versions of the HEPA standard. In general, the initial filter efficiency decreased with increasing media velocity. However, initial filter efficiencies were generally good in all cases. Filter efficiency values averaged over the first ten minute of the loading cycle ranged from 99.970 to 99.996 %. Additionally, the most penetrating particle size was observed to decrease with increasing media velocity

An in-flight investigation of pilot-induced oscillation suppression filters during the fighter approach and landing task

Science.gov (United States)

Bailey, R. E.; Smith, R. E.

1982-01-01

An investigation of pilot-induced oscillation suppression (PIOS) filters was performed using the USAF/Flight Dynamics Laboratory variable stability NT-33 aircraft, modified and operated by Calspan. This program examined the effects of PIOS filtering on the longitudinal flying qualities of fighter aircraft during the visual approach and landing task. Forty evaluations were flown to test the effects of different PIOS filters. Although detailed analyses were not undertaken, the results indicate that PIOS filtering can improve the flying qualities of an otherwise unacceptable aircraft configuration (Level 3 flying qualities). However, the ability of the filters to suppress pilot-induced oscillations appears to be dependent upon the aircraft configuration characteristics. Further, the data show that the filters can adversely affect landing flying qualities if improperly designed. The data provide an excellent foundation from which detail analyses can be performed.

A Framework for Similarity Search with Space-Time Tradeoffs using Locality Sensitive Filtering

DEFF Research Database (Denmark)

Christiani, Tobias Lybecker

2017-01-01

that satisfies certain locality-sensitivity properties, we can construct a dynamic data structure that solves the approximate near neighbor problem in $d$-dimensional space with query time $dn^{\\rho_q + o(1)}$, update time $dn^{\\rho_u + o(1)}$, and space usage $dn + n^{1 + \\rho_u + o(1)}$ where $n$ denotes......We present a framework for similarity search based on Locality-Sensitive Filtering~(LSF),generalizing the Indyk-Motwani (STOC 1998) Locality-Sensitive Hashing~(LSH) framework to support space-time tradeoffs. Given a family of filters, defined as a distribution over pairs of subsets of space...... the number of points in the data structure.The space-time tradeoff is tied to the tradeoff between query time and update time (insertions/deletions), controlled by the exponents $\\rho_q, \\rho_u$ that are determined by the filter family. \\\\ Locality-sensitive filtering was introduced by Becker et al. (SODA...

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

Science.gov (United States)

Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil

2011-01-01

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

Filtering Photogrammetric Point Clouds Using Standard LIDAR Filters Towards DTM Generation

Science.gov (United States)

Zhang, Z.; Gerke, M.; Vosselman, G.; Yang, M. Y.

2018-05-01

Digital Terrain Models (DTMs) can be generated from point clouds acquired by laser scanning or photogrammetric dense matching. During the last two decades, much effort has been paid to developing robust filtering algorithms for the airborne laser scanning (ALS) data. With the point cloud quality from dense image matching (DIM) getting better and better, the research question that arises is whether those standard Lidar filters can be used to filter photogrammetric point clouds as well. Experiments are implemented to filter two dense matching point clouds with different noise levels. Results show that the standard Lidar filter is robust to random noise. However, artefacts and blunders in the DIM points often appear due to low contrast or poor texture in the images. Filtering will be erroneous in these locations. Filtering the DIM points pre-processed by a ranking filter will bring higher Type II error (i.e. non-ground points actually labelled as ground points) but much lower Type I error (i.e. bare ground points labelled as non-ground points). Finally, the potential DTM accuracy that can be achieved by DIM points is evaluated. Two DIM point clouds derived by Pix4Dmapper and SURE are compared. On grassland dense matching generates points higher than the true terrain surface, which will result in incorrectly elevated DTMs. The application of the ranking filter leads to a reduced bias in the DTM height, but a slightly increased noise level.

Second Order Washout filter based Power Sharing Strategy for Uninterruptible Power Supply

DEFF Research Database (Denmark)

Lu, Jinghang; Savaghebi, Mehdi; Guerrero, Josep M.

2017-01-01

In this paper, first, the existing frequency and voltage amplitude restoration control strategies are reviewed. Moreover, the proposed second order washout filter control strategy is proposed to enhance the dynamic response under load disturbance. The physical parameter of the proposed method is ...

Recursive inverse kinematics for robot arms via Kalman filtering and Bryson-Frazier smoothing

Science.gov (United States)

Rodriguez, G.; Scheid, R. E., Jr.

1987-01-01

This paper applies linear filtering and smoothing theory to solve recursively the inverse kinematics problem for serial multilink manipulators. This problem is to find a set of joint angles that achieve a prescribed tip position and/or orientation. A widely applicable numerical search solution is presented. The approach finds the minimum of a generalized distance between the desired and the actual manipulator tip position and/or orientation. Both a first-order steepest-descent gradient search and a second-order Newton-Raphson search are developed. The optimal relaxation factor required for the steepest descent method is computed recursively using an outward/inward procedure similar to those used typically for recursive inverse dynamics calculations. The second-order search requires evaluation of a gradient and an approximate Hessian. A Gauss-Markov approach is used to approximate the Hessian matrix in terms of products of first-order derivatives. This matrix is inverted recursively using a two-stage process of inward Kalman filtering followed by outward smoothing. This two-stage process is analogous to that recently developed by the author to solve by means of spatial filtering and smoothing the forward dynamics problem for serial manipulators.

Filter assessment applied to analytical reconstruction for industrial third-generation tomography

Energy Technology Data Exchange (ETDEWEB)

Velo, Alexandre F.; Martins, Joao F.T.; Oliveira, Adriano S.; Carvalho, Diego V.S.; Faria, Fernando S.; Hamada, Margarida M.; Mesquita, Carlos H., E-mail: afvelo@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2015-07-01

Multiphase systems are structures that contain a mixture of solids, liquids and gases inside a chemical reactor or pipes in a dynamic process. These systems are found in chemical, food, pharmaceutical and petrochemical industries. The gamma ray computed tomography (CT) system has been applied to visualize the distribution of multiphase systems without interrupting production. CT systems have been used to improve design, operation and troubleshooting of industrial processes. Computer tomography for multiphase processes is being developed at several laboratories. It is well known that scanning systems demand high processing time, limited set of data projections and views to obtain an image. Because of it, the image quality is dependent on the number of projection, number of detectors, acquisition time and reconstruction time. A phantom containing air, iron and aluminum was used on the third generation industrial tomography with 662 keV ({sup 137}Cs) radioactive source. It was applied the Filtered Back Projection algorithm to reconstruct the images. An efficient tomography is dependent of the image quality, thus the objective of this research was to apply different types of filters on the analytical algorithm and compare each other using the figure of merit denominated root mean squared error (RMSE), the filter that presents lower value of RMSE has better quality. On this research, five types of filters were used: Ram-Lak, Shepp-Logan, Cosine, Hamming and Hann filters. As results, all filters presented lower values of RMSE, that means the filters used have low stand deviation compared to the mass absorption coefficient, however, the Hann filter presented better RMSE and CNR compared to the others. (author)

Filter assessment applied to analytical reconstruction for industrial third-generation tomography

International Nuclear Information System (INIS)

Velo, Alexandre F.; Martins, Joao F.T.; Oliveira, Adriano S.; Carvalho, Diego V.S.; Faria, Fernando S.; Hamada, Margarida M.; Mesquita, Carlos H.

2015-01-01

Multiphase systems are structures that contain a mixture of solids, liquids and gases inside a chemical reactor or pipes in a dynamic process. These systems are found in chemical, food, pharmaceutical and petrochemical industries. The gamma ray computed tomography (CT) system has been applied to visualize the distribution of multiphase systems without interrupting production. CT systems have been used to improve design, operation and troubleshooting of industrial processes. Computer tomography for multiphase processes is being developed at several laboratories. It is well known that scanning systems demand high processing time, limited set of data projections and views to obtain an image. Because of it, the image quality is dependent on the number of projection, number of detectors, acquisition time and reconstruction time. A phantom containing air, iron and aluminum was used on the third generation industrial tomography with 662 keV ( 137 Cs) radioactive source. It was applied the Filtered Back Projection algorithm to reconstruct the images. An efficient tomography is dependent of the image quality, thus the objective of this research was to apply different types of filters on the analytical algorithm and compare each other using the figure of merit denominated root mean squared error (RMSE), the filter that presents lower value of RMSE has better quality. On this research, five types of filters were used: Ram-Lak, Shepp-Logan, Cosine, Hamming and Hann filters. As results, all filters presented lower values of RMSE, that means the filters used have low stand deviation compared to the mass absorption coefficient, however, the Hann filter presented better RMSE and CNR compared to the others. (author)

Selectivity and balance of spatial filtering velocimetry of objective speckles for measuring out-of-plane motion

DEFF Research Database (Denmark)

Jakobsen, Michael Linde; Yura, Hal T.; Hanson, Steen Grüner

2015-01-01

We probe the dynamics of objective laser speckles as the axial distance between the object and the observation plane changes. With the purpose of measuring out-of-plane motion in real time, we apply optical spatial filtering velocimetry to the speckle dynamics. To achieve this, a rotationally sym...

Bias aware Kalman filters

DEFF Research Database (Denmark)

Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan

2006-01-01

This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....

Study of different filters

International Nuclear Information System (INIS)

Cochinal, R.; Rouby, R.

1959-01-01

This note first contains a terminology related to filters and to their operation, and then proposes an overview of general characteristics of filters such as load loss with respect to gas rate, efficiency, and clogging with respect to filter pollution. It also indicates standard aerosols which are generally used, how they are dosed, and how efficiency is determined with a standard aerosol. Then, after a presentation of the filtration principle, this note reports the study of several filters: glass wool, filter papers provided by different companies, Teflon foam, English filters, Teflon wool, sintered Teflonite, quartz wool, polyvinyl chloride foam, synthetic filter, sintered bronze. The third part reports the study of some aerosol and dust separators

Laboratory for filter testing

Energy Technology Data Exchange (ETDEWEB)

Paluch, W.

1987-07-01

Filters used for mine draining in brown coal surface mines are tested by the Mine Draining Department of Poltegor. Laboratory tests of new types of filters developed by Poltegor are analyzed. Two types of tests are used: tests of scale filter models and tests of experimental units of new filters. Design and operation of the test stands used for testing mechanical properties and hydraulic properties of filters for coal mines are described: dimensions, pressure fluctuations, hydraulic equipment. Examples of testing large-diameter filters for brown coal mines are discussed.

Research on Discretization PI Control Technology of Single-Phase Grid-Connected Inverter with LCL Filter

Directory of Open Access Journals (Sweden)

Jianke Li

2014-01-01

Full Text Available Compared with L-type filter, LCL-type filter is more suitable for high-power low-switching frequency applications with reducing the inductance, improving dynamic performance. However, the parameter design for the LCL filter is more complex due to the influence of the controller response performance of the converter. If the harmonic current around switching frequency can be fully suppressed, it is possible for inverter to decrease the total inductance as well as the size and the cost. In this paper, the model of the LCL filter is analyzed and numerical algorithms are adopted to analyze the stability of the closed-loop control system and stable regions are deduced with different parameters of LCL filter. Then, the minimum sampling frequencies are deduced with different conditions. Simulation and experimental results are provided to validate the research on the generating mechanism for the unstable region of sampling frequency.

Broken symmetry within crystallographic super-spaces: structural and dynamical aspects

International Nuclear Information System (INIS)

Mariette, Celine

2013-01-01

Aperiodic crystals have the property to possess long range order without translational symmetry. These crystals are described within the formalism of super-space crystallography. In this manuscript, we will focus on symmetry breaking which take place in such crystallographic super-space groups, considering the prototype family of n-alkane/urea. Studies performed by X-ray diffraction using synchrotron sources reveal multiple structural solutions implying or not changes of the dimension of the super-space. Once the characterization of the order parameter and of the symmetry breaking is done, we present the critical pre-transitional phenomena associated to phase transitions of group/subgroup types. Coherent neutron scattering and inelastic X-ray scattering allow a dynamical analysis of different kind of excitations in these materials (phonons, phasons). The inclusion compounds with short guest molecules (alkane C n H 2n+2 , n varying from 7 to 13) show at room temperature unidimensional 'liquid-like' phases. The dynamical disorder along the incommensurate direction of these materials generates new structural solutions at low temperature (inter-modulated monoclinic composite, commensurate lock-in). (author) [fr

Simulasi Filter Pasif Dan Perbandingan Unjuk Kerjanya Dengan Filter Aktif Dan Filter Aktif Hibrid Dalam Meredam Harmonisa Pada Induction Furnace

OpenAIRE

Tanoto, Yusak; Limantara, Limboto; Khandy Lestanto, Khristian

2005-01-01

This paper describe about simulation of Passive Filter in analysis to reduce harmonics that happened in a load such as vacuum casting induction furnace 9 kW, 13.8 kVA, 200V, 3 Ph, 50/60 Hz, also gives comparison with Hybrid Active Filter and Active Filter which made satisfaction result on the previous research. The best result achieved on the use of Hybrid Active Filter on %ITHD for 4.27 % and %VTHD for 3.83%, while Active Filter gave on %ITHD for 5.14 % and %VTHD for 3.82%. There ...

Precomputing Process Noise Covariance for Onboard Sequential Filters

Science.gov (United States)

Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell

2017-01-01

Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.

Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

Directory of Open Access Journals (Sweden)

Jing Liu

2012-01-01

Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

The Reduced Rank of Ensemble Kalman Filter to Estimate the Temperature of Non Isothermal Continue Stirred Tank Reactor

Directory of Open Access Journals (Sweden)

Erna Apriliani

2011-01-01

Full Text Available Kalman filter is an algorithm to estimate the state variable of dynamical stochastic system. The square root ensemble Kalman filter is an modification of Kalman filter. The square root ensemble Kalman filter is proposed to keep the computational stability and reduce the computational time. In this paper we study the efficiency of the reduced rank ensemble Kalman filter. We apply this algorithm to the non isothermal continue stirred tank reactor problem. We decompose the covariance of the ensemble estimation by using the singular value decomposition (the SVD, and then we reduced the rank of the diagonal matrix of those singular values. We make a simulation by using Matlab program. We took some the number of ensemble such as 100, 200 and 500. We compared the computational time and the accuracy between the square root ensemble Kalman filter and the ensemble Kalman filter. The reduced rank ensemble Kalman filter can’t be applied in this problem because the dimension of state variable is too less.

Well-posedness and accuracy of the ensemble Kalman filter in discrete and continuous time

KAUST Repository

Kelly, D. T B

2014-09-22

The ensemble Kalman filter (EnKF) is a method for combining a dynamical model with data in a sequential fashion. Despite its widespread use, there has been little analysis of its theoretical properties. Many of the algorithmic innovations associated with the filter, which are required to make a useable algorithm in practice, are derived in an ad hoc fashion. The aim of this paper is to initiate the development of a systematic analysis of the EnKF, in particular to do so for small ensemble size. The perspective is to view the method as a state estimator, and not as an algorithm which approximates the true filtering distribution. The perturbed observation version of the algorithm is studied, without and with variance inflation. Without variance inflation well-posedness of the filter is established; with variance inflation accuracy of the filter, with respect to the true signal underlying the data, is established. The algorithm is considered in discrete time, and also for a continuous time limit arising when observations are frequent and subject to large noise. The underlying dynamical model, and assumptions about it, is sufficiently general to include the Lorenz \\'63 and \\'96 models, together with the incompressible Navier-Stokes equation on a two-dimensional torus. The analysis is limited to the case of complete observation of the signal with additive white noise. Numerical results are presented for the Navier-Stokes equation on a two-dimensional torus for both complete and partial observations of the signal with additive white noise.

Well-posedness and accuracy of the ensemble Kalman filter in discrete and continuous time

International Nuclear Information System (INIS)

Kelly, D T B; Stuart, A M; Law, K J H

2014-01-01

The ensemble Kalman filter (EnKF) is a method for combining a dynamical model with data in a sequential fashion. Despite its widespread use, there has been little analysis of its theoretical properties. Many of the algorithmic innovations associated with the filter, which are required to make a useable algorithm in practice, are derived in an ad hoc fashion. The aim of this paper is to initiate the development of a systematic analysis of the EnKF, in particular to do so for small ensemble size. The perspective is to view the method as a state estimator, and not as an algorithm which approximates the true filtering distribution. The perturbed observation version of the algorithm is studied, without and with variance inflation. Without variance inflation well-posedness of the filter is established; with variance inflation accuracy of the filter, with respect to the true signal underlying the data, is established. The algorithm is considered in discrete time, and also for a continuous time limit arising when observations are frequent and subject to large noise. The underlying dynamical model, and assumptions about it, is sufficiently general to include the Lorenz '63 and '96 models, together with the incompressible Navier–Stokes equation on a two-dimensional torus. The analysis is limited to the case of complete observation of the signal with additive white noise. Numerical results are presented for the Navier–Stokes equation on a two-dimensional torus for both complete and partial observations of the signal with additive white noise. (paper)

Rotation speed measurement for turbine governor: torsion filtering by using Kalman filter

International Nuclear Information System (INIS)

Houry, M.P.; Bourles, H.

1996-01-01

The rotation speed of a turbogenerator is disturbed by its shaft torsion. Obtaining a filtered measure of this speed is a problem of a great practical importance for turbine governor. A good filtering of this speed must meet two requirements: it must cut frequencies of the shaft torsion oscillation and it must not reduce or delay the signal in the pass-band, i.e. at lower frequencies. At Electricite de France, the speed measure is used to set in motion the fast valving system as quickly as possible, after a short circuit close to the unit or rather an islanding. It is difficult to satisfy these two requirements by using conventional filtering methods. The standard solution consists in a first order filter: at Electricite de France, its time constant is equal to 80 ms. We have decided to improve this filtering by designing a new filter which cuts the frequencies of the shaft torsion oscillation without reducing the bandwidth to the speed measure. If one uses conventional methods to obtain a band stop filter, it is easy to obtain the desired magnitude but not a phase near zero in the whole pass-band. Therefore, we have chosen to design the filter by using Kalman'a theory. The measurement noise is modeled as a colored one, generated by a very lightly damped system driven by a while noise. The resulting Kalman filter is an effective band stop filter, whose phase nicely remains near zero in the whole pass-band. The digital simulations we made and the tests we carried out with the Electricite de France Micro Network laboratory show the advantages of the rotation speed filter we designed using Kalman's theory. With the proposed filter, the speed measure filtering is better in terms of reduction and phase shift. the result is that there are less untimely solicitations of the fast valving system. Consequently, this device improves the power systems stability by minimizing the risks of deep perturbations due to a temporary lack of generation and the risks of under-speed loss

The dry filter method for passive filtered venting of the containment

International Nuclear Information System (INIS)

Freis, Daniel; Tietsch, Wolfgang; Obenland, Ralf; Kroes, Bert; Martinsteg, Hans

2013-01-01

Filtered Venting is a mitigative emergency measure to protect the containment from pressure failure in case of a severe accident. Filtered vent systems which are based on the Dry Filter Method (DFM) are proven technology, work completely passive, meet all functional requirements and show excellent performance with respect to filter efficiency. With such a system the release of radioactive fission products to the environment can be effectively minimized. Short and long term land contaminations can be avoided. (orig.)

Biotrickling filter modeling for styrene abatement. Part 1: Model development, calibration and validation on an industrial scale.

Science.gov (United States)

San-Valero, Pau; Dorado, Antonio D; Martínez-Soria, Vicente; Gabaldón, Carmen

2018-01-01

A three-phase dynamic mathematical model based on mass balances describing the main processes in biotrickling filtration: convection, mass transfer, diffusion, and biodegradation was calibrated and validated for the simulation of an industrial styrene-degrading biotrickling filter. The model considered the key features of the industrial operation of biotrickling filters: variable conditions of loading and intermittent irrigation. These features were included in the model switching from the mathematical description of periods with and without irrigation. Model equations were based on the mass balances describing the main processes in biotrickling filtration: convection, mass transfer, diffusion, and biodegradation. The model was calibrated with steady-state data from a laboratory biotrickling filter treating inlet loads at 13-74 g C m -3 h -1 and at empty bed residence time of 30-15 s. The model predicted the dynamic emission in the outlet of the biotrickling filter, simulating the small peaks of concentration occurring during irrigation. The validation of the model was performed using data from a pilot on-site biotrickling filter treating styrene installed in a fiber-reinforced facility. The model predicted the performance of the biotrickling filter working under high-oscillating emissions at an inlet load in a range of 5-23 g C m -3 h -1 and at an empty bed residence time of 31 s for more than 50 days, with a goodness of fit of 0.84. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing Cost of Continuous Overlapping Queries over Data Streams by Filter Adaption

KAUST Repository

Xie, Qing

2016-01-12

The problem we aim to address is the optimization of cost management for executing multiple continuous queries on data streams, where each query is defined by several filters, each of which monitors certain status of the data stream. Specially the filter can be shared by different queries and expensive to evaluate. The conventional objective for such a problem is to minimize the overall execution cost to solve all queries, by planning the order of filter evaluation in shared strategy. However, in streaming scenario, the characteristics of data items may change in process, which can bring some uncertainty to the outcome of individual filter evaluation, and affect the plan of query execution as well as the overall execution cost. In our work, considering the influence of the uncertain variation of data characteristics, we propose a framework to deal with the dynamic adjustment of filter ordering for query execution on data stream, and focus on the issues of cost management. By incrementally monitoring and analyzing the results of filter evaluation, our proposed approach can be effectively adaptive to the varied stream behavior and adjust the optimal ordering of filter evaluation, so as to optimize the execution cost. In order to achieve satisfactory performance and efficiency, we also discuss the trade-off between the adaptivity of our framework and the overhead incurred by filter adaption. The experimental results on synthetic and two real data sets (traffic and multimedia) show that our framework can effectively reduce and balance the overall query execution cost and keep high adaptivity in streaming scenario.

Generalized Selection Weighted Vector Filters

Directory of Open Access Journals (Sweden)

Rastislav Lukac

2004-09-01

Full Text Available This paper introduces a class of nonlinear multichannel filters capable of removing impulsive noise in color images. The here-proposed generalized selection weighted vector filter class constitutes a powerful filtering framework for multichannel signal processing. Previously defined multichannel filters such as vector median filter, basic vector directional filter, directional-distance filter, weighted vector median filters, and weighted vector directional filters are treated from a global viewpoint using the proposed framework. Robust order-statistic concepts and increased degree of freedom in filter design make the proposed method attractive for a variety of applications. Introduced multichannel sigmoidal adaptation of the filter parameters and its modifications allow to accommodate the filter parameters to varying signal and noise statistics. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, yields excellent performance, and is able to preserve fine details and color information while efficiently suppressing impulsive noise. This paper is an extended version of the paper by Lukac et al. presented at the 2003 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03 in Grado, Italy.

Rotation speed measurement for turbine governor: torsion filtering by using Kalman filter

International Nuclear Information System (INIS)

Houry, M.P.; Bourles, H.

1995-11-01

The rotation speed of a turbogenerator is disturbed by its shaft torsion. Obtaining a filtered measure of this sped a problem of a great practical importance for turbine governor. A good filtering of this speed must meet two requirements: it must cut frequencies of the shaft torsion oscillation and it must not reduce or delay the signal in the pass-band. i.e. at lower frequencies. At Electricite de France, the speed measure is used to set in motion the fast valving system as quickly as possible, after a short circuit close to the unit (to contribute to the stability) or after an islanding (to quickly reach a balance with the house load). It is difficult to satisfy these two requirements by using conventional filtering methods. The standard solution consists in a first order filter: at Electricite de France, its time constant is equal to 80 ms; We have decided to improve this filtering by designing a new filter which cuts the frequencies of the shaft torsion oscillation without reducing the bandwidth of the speed measure. If one uses conventional methods to obtain a band-stop filter (for instance a Butterworth, a Chebyshev or an elliptic band-stop filter),it is easy to obtain the desired magnitude but not a phase near zero in the whole pass-band. Therefore, we have chosen to design the filter by using Kalman's theory. The measurement noise is modeled as a colored one, generated by a very lightly damped system driven by a white noise. The resulting Kalman filter is an effective band-stop filter, whose phase nicely remains near zero in the whole pass-band. (authors). 13 refs., 12 figs

Optimization of filter loading

International Nuclear Information System (INIS)

Turney, J.H.; Gardiner, D.E.; Sacramento Municipal Utility District, Herald, CA)

1985-01-01

The introduction of 10 CFR Part 61 has created potential difficulties in the disposal of spent cartridge filters. When this report was prepared, Rancho Seco had no method of packaging and disposing of class B or C filters. This work examined methods to minimize the total operating cost of cartridge filters while maintaining them below the class A limit. It was found that by encapsulating filters in cement the filter operating costs could be minimized

Dynamic state estimation assisted power system monitoring and protection

Science.gov (United States)

Cui, Yinan

The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the

Modeling aspects of wave kinematics in offshore structures dynamics

International Nuclear Information System (INIS)

Spanos, P.D.; Ghanem, R.; Bhattacharjee, S.

1993-01-01

Magnitude and phase related issues of modeling of ocean wave kinematics are addressed. Causal and non-causal filters are examined. It is shown that if for a particular ocean engineering problem only the magnitude representation of wave spectra spatial relation is critical, analog filters can be quite useful models in conjunction with the technique of statistical linearization, for calculating dynamic analyses. This is illustrated by considering the dynamic response of a simple model of a guyed tower

DYNAMIC ESTIMATION FOR PARAMETERS OF INTERFERENCE SIGNALS BY THE SECOND ORDER EXTENDED KALMAN FILTERING

Directory of Open Access Journals (Sweden)

P. A. Ermolaev

2014-03-01

Full Text Available Data processing in the interferometer systems requires high-resolution and high-speed algorithms. Recurrence algorithms based on parametric representation of signals execute consequent processing of signal samples. In some cases recurrence algorithms make it possible to increase speed and quality of data processing as compared with classic processing methods. Dependence of the measured interferometer signal on parameters of its model and stochastic nature of noise formation in the system is, in general, nonlinear. The usage of nonlinear stochastic filtering algorithms is expedient for such signals processing. Extended Kalman filter with linearization of state and output equations by the first vector parameters derivatives is an example of these algorithms. To decrease approximation error of this method the second order extended Kalman filtering is suggested with additionally usage of the second vector parameters derivatives of model equations. Examples of algorithm implementation with the different sets of estimated parameters are described. The proposed algorithm gives the possibility to increase the quality of data processing in interferometer systems in which signals are forming according to considered models. Obtained standard deviation of estimated amplitude envelope does not exceed 4% of the maximum. It is shown that signal-to-noise ratio of reconstructed signal is increased by 60%.

Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

Directory of Open Access Journals (Sweden)

Hamza Benzerrouk

2018-03-01

Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model

KAUST Repository

Liu, Bo

2016-02-03

An ensemble-based Gaussian mixture (GM) filtering framework is studied in this paper in term of its dependence on the choice of the clustering method to construct the GM. In this approach, a number of particles sampled from the posterior distribution are first integrated forward with the dynamical model for forecasting. A GM representation of the forecast distribution is then constructed from the forecast particles. Once an observation becomes available, the forecast GM is updated according to Bayes’ rule. This leads to (i) a Kalman filter-like update of the particles, and (ii) a Particle filter-like update of their weights, generalizing the ensemble Kalman filter update to non-Gaussian distributions. We focus on investigating the impact of the clustering strategy on the behavior of the filter. Three different clustering methods for constructing the prior GM are considered: (i) a standard kernel density estimation, (ii) clustering with a specified mixture component size, and (iii) adaptive clustering (with a variable GM size). Numerical experiments are performed using a two-dimensional reactive contaminant transport model in which the contaminant concentration and the heterogenous hydraulic conductivity fields are estimated within a confined aquifer using solute concentration data. The experimental results suggest that the performance of the GM filter is sensitive to the choice of the GM model. In particular, increasing the size of the GM does not necessarily result in improved performances. In this respect, the best results are obtained with the proposed adaptive clustering scheme.

Applications of Kalman Filtering to nuclear material control. [Kalman filtering and linear smoothing for detecting nuclear material losses

Energy Technology Data Exchange (ETDEWEB)

Pike, D.H.; Morrison, G.W.; Westley, G.W.

1977-10-01

The feasibility of using modern state estimation techniques (specifically Kalman Filtering and Linear Smoothing) to detect losses of material from material balance areas is evaluated. It is shown that state estimation techniques are not only feasible but in most situations are superior to existing methods of analysis. The various techniques compared include Kalman Filtering, linear smoothing, standard control charts, and average cumulative summation (CUSUM) charts. Analysis results indicated that the standard control chart is the least effective method for detecting regularly occurring losses. An improvement in the detection capability over the standard control chart can be realized by use of the CUSUM chart. Even more sensitivity in the ability to detect losses can be realized by use of the Kalman Filter and the linear smoother. It was found that the error-covariance matrix can be used to establish limits of error for state estimates. It is shown that state estimation techniques represent a feasible and desirable method of theft detection. The technique is usually more sensitive than the CUSUM chart in detecting losses. One kind of loss which is difficult to detect using state estimation techniques is a single isolated loss. State estimation procedures are predicated on dynamic models and are well-suited for detecting losses which occur regularly over several accounting periods. A single isolated loss does not conform to this basic assumption and is more difficult to detect.

A Novel Characterization And Application Of PZT Ceramic As A Frequency Filter

International Nuclear Information System (INIS)

Fawzy, Y.H.A.; Ashry, H.A.; Soliman, F.A.S.; Swidan, A.M.; Abdelmagid, A.

2008-01-01

Nowadays, ceramic filters have become indispensable components in numerous electronic equipment for military and space applications, as well as, commercial ones. So, the present paper is devoted in a trial to shed further light on such new devices. In this concern, a wide frequency range samples, extends from 400 kHz up to 6.5 MHz, were chosen for studying the frequency response and related terminologies, dynamic characteristics, and equivalent circuits and their relation with the elemental composition of the different samples. Also, the filter circuit elements effect on the operation of such devices was investigated

Retrievable Vena Cava Filters in Major Trauma Patients: Prevalence of Thrombus Within the Filter

International Nuclear Information System (INIS)

Mahrer, Arie; Zippel, Douglas; Garniek, Alexander; Golan, Gil; Bensaid, Paul; Simon, Daniel; Rimon, Uri

2008-01-01

The purpose of this study was to report the prevalence of thrombus within a retrievable vena cava filter inserted prophylactically in major trauma patients referred for filter extraction. Between November 2002 and August 2005, 80 retrievable inferior vena cava filters (68 Optease and 12 Gunther-Tulip) were inserted into critically injured trauma patients (mean injury severity score 33.5). The filters were inserted within 1 to 6 (mean 2) days of injury. Thirty-seven patients were referred for filter removal (32 with Optease and 5 with Gunther-Tulip). The indwelling time was 7 to 22 (mean 13) days. All patients underwent inferior vena cavography prior to filter removal. There were no insertion-related complications and all filters were successfully deployed. Forty-three (54%) of the 80 patients were not referred for filter removal, as these patients continued to have contraindications to anticoagulation. Thirty-seven patients (46%) were referred for filter removal. In eight of them (22%) a large thrombus was seen within the filters and they were left in place, all with the Optease device. The other 29 filters (36%) were removed uneventfully.We conclude that the relatively high prevalence of intrafilter thrombi with the Optease filter may be explained by either spontaneous thrombus formation or captured emboli.

Particulate removal processes and hydraulics of porous gravel media filters

Science.gov (United States)

Minto, J. M.; Phoenix, V. R.; Dorea, C. C.; Haynes, H.; Sloan, W. T.

2013-12-01

Sustainable urban Drainage Systems (SuDS) are rapidly gaining acceptance as a low-cost tool for treating urban runoff pollutants close to source. Road runoff water in particular requires treatment due to the presence of high levels of suspended particles and heavy metals adsorbed to these particles. The aim of this research is to elucidate the particle removal processes that occur within gravel filters that have so far been considered as 'black-box' systems. Based on these findings, a better understanding will be attained on what influences gravel filter removal efficiency and how this changes throughout their design life; leading to a more rational design of this useful technology. This has been achieved by tying together three disparate research elements: tracer residence time distribution curves of filters during clogging; 3D magnetic resonance imaging (MRI) of clogging filters and computational fluid dynamics (CFD) modelling of complex filter pore networks. This research relates column average changes in particle removal efficiency and tracer residence time distributions (RTDs) due to clogging with non-invasive measurement of the spatial variability in particle deposition. The CFD modelling provides a link between observed deposition patterns, flow velocities and wall shear stresses as well as the explanations for the change in RTD with clogging and the effect on particle transport. Results show that, as a filter clogs, particles take a longer, more tortuous path through the filter. This is offset by a reduction in filter volume resulting in higher flow velocities and more rapid particle transport. Higher velocities result in higher shear stresses and the development of preferential pathways in which the velocity exceeds the deposition threshold and the overall efficiency of the filter decreases. Initial pore geometry is linked to the pattern of deposition and subsequent formation of preferential pathways. These results shed light on the 'black-box' internal

Ultra scaledown to predict filtering centrifugation of secreted antibody fragments from fungal broth.

Science.gov (United States)

Boulding, N; Yim, S S S; Keshavarz-Moore, E; Ayazi Shamlou, P; Berry, M

2002-08-20

Extracellularly expressed anti-hen egg lysozyme single-chain antibody fragments (scFv) produced by Aspergillus awamori were recovered using filtering centrifugation. Two filtering centrifuges with 0.5- and 30-L capacities were used to represent laboratory- and pilot-scale equipment, respectively. Critical regime analysis using the computational fluid dynamics (CFD) technique provided information about the local energy dissipation rates in both units. Experimental data indicated loss of scFv activity for energy dissipation rates above about 2.0 x 10(4) W kg(-1). This loss of activity increased in the presence of gas-liquid interfaces during filtering centrifugation. An ultra scaledown filtering centrifuge with a maximum working volume of 35 mL was designed to mimic the operating conditions identified by the critical regime analysis for the laboratory- and pilot-plant-scale units. The recovered scFv activity levels and the separation performance of the three units were comparable when operated at equal maximum energy dissipation rates. Copyright 2002 Wiley Periodicals, Inc.

Hybrid extended particle filter (HEPF) for integrated inertial navigation and global positioning systems

International Nuclear Information System (INIS)

Aggarwal, Priyanka; Syed, Zainab; El-Sheimy, Naser

2009-01-01

Navigation includes the integration of methodologies and systems for estimating time-varying position, velocity and attitude of moving objects. Navigation incorporating the integrated inertial navigation system (INS) and global positioning system (GPS) generally requires extensive evaluations of nonlinear equations involving double integration. Currently, integrated navigation systems are commonly implemented using the extended Kalman filter (EKF). The EKF assumes a linearized process, measurement models and Gaussian noise distributions. These assumptions are unrealistic for highly nonlinear systems like land vehicle navigation and may cause filter divergence. A particle filter (PF) is developed to enhance integrated INS/GPS system performance as it can easily deal with nonlinearity and non-Gaussian noises. In this paper, a hybrid extended particle filter (HEPF) is developed as an alternative to the well-known EKF to achieve better navigation data accuracy for low-cost microelectromechanical system sensors. The results show that the HEPF performs better than the EKF during GPS outages, especially when simulated outages are located in periods with high vehicle dynamics

Physical characteristics of the paper filter and low cafestol content filter coffee brews.

Science.gov (United States)

Rendón, Mery Yovana; Dos Santos Scholz, Maria Brígida; Bragagnolo, Neura

2018-06-01

The results found in the literature concerning the effect of consuming filter coffee brews on increasing the blood cholesterol levels due to the presence of diterpenes, are divergent. Thus the present research evaluated the diterpene (cafestol and kahweol) concentrations in filter coffee brews prepared with paper filters of different sizes, colors and origins (Brazil, Japan, The United States of America, Germany, France and the Netherlands), with and without micro perforations. This is the first study that reports the physical characteristics of paper filter and its importance to obtain filter coffee brew with low cafestol content. Thus, a sample of Catuai cultivar coffee with high cafestol content was roasted to a medium-light degree and used to prepare the brews in a 1:10 ratio (coffee powder to water). The diterpenes were extracted by direct saponification and quantified and identified by HPLC-DAD-MS/MS. The paper filters were physically characterized by measuring their grammage, and the fat permeation rate calculated in order to better understand the differences between the filters which allow one to obtain higher or lower diterpene contents. The cafestol and kahweol concentrations in the brews varied from 1.62 to 2.98 mg/L and from 0.73 to 1.96 mg/L, respectively. The highest cafestol and kahweol concentrations were obtained using paper filters with micro perforations, considering similar sized paper filters. The paper filters showed high fat permeability and grammages between 50.46 and 67.48 g/m 2 . The diterpene retention capacities of the filters produced in the different countries were similar. The results showed that the porosity of the paper filter and the particle size of the ground roasted coffee were determinant factors in obtaining filter coffee brews with lower cafestol contents. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

Science.gov (United States)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

Modeling the Performance of Biological Rapid Sand Filters Used to Remove Ammonium, Iron, and Manganese From Drinking Water

DEFF Research Database (Denmark)

Lee, Carson; Albrechtsen, Hans-Jørgen; Smets, Barth F.

activated carbon and are often used following ozonation to remove additional biodegradable organics created during ozonation. In Europe, biological filters are also used to remove ammonium and reduced forms of iron and manganese. These compounds can cause biological instability in the distribution system...... tracer, are performed during an operational cycle of a filter to examine how the filter flow changes with time. The data is used to validate a mathematical model that can both predict process performance and to gain an understanding of how dynamic conditions can influence filter performance....... The mathematical model developed is intended to assist in the design of new filters, set up of pilot plant studies, and as a tool to troubleshoot existing problems in full scale filters. Unlike previous models, the model developed accounts for the effects of particle/precipitate accumulation and its effects...

Design, control, and implementation of LCL-filter-based shunt active power filters

DEFF Research Database (Denmark)

Tang, Yi; Loh, Poh Chiang; Wang, Peng

2011-01-01

This paper concentrates on the design, control and implementation of an LCL-filter-based shunt active power filter (SAPF), which can effectively compensate harmonic currents produced by nonlinear loads in a three-phase three-wire power system. The use of LCL-filter at the output end of SAPF offer......-loop control system, and active damping implemented with fewer current sensors are all addressed here. An analytical design example is finally presented, being supported with experimental results, to verify its effectiveness and practicality.......This paper concentrates on the design, control and implementation of an LCL-filter-based shunt active power filter (SAPF), which can effectively compensate harmonic currents produced by nonlinear loads in a three-phase three-wire power system. The use of LCL-filter at the output end of SAPF offers...

Inorganic UV filters

Directory of Open Access Journals (Sweden)

Eloísa Berbel Manaia

2013-06-01

Full Text Available Nowadays, concern over skin cancer has been growing more and more, especially in tropical countries where the incidence of UVA/B radiation is higher. The correct use of sunscreen is the most efficient way to prevent the development of this disease. The ingredients of sunscreen can be organic and/or inorganic sun filters. Inorganic filters present some advantages over organic filters, such as photostability, non-irritability and broad spectrum protection. Nevertheless, inorganic filters have a whitening effect in sunscreen formulations owing to the high refractive index, decreasing their esthetic appeal. Many techniques have been developed to overcome this problem and among them, the use of nanotechnology stands out. The estimated amount of nanomaterial in use must increase from 2000 tons in 2004 to a projected 58000 tons in 2020. In this context, this article aims to analyze critically both the different features of the production of inorganic filters (synthesis routes proposed in recent years and the permeability, the safety and other characteristics of the new generation of inorganic filters.

Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter

DEFF Research Database (Denmark)

Mohd. Azam, Sazuan Nazrah

2017-01-01

In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing...... part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations....

PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

Science.gov (United States)

Xia, Jing; Wang, Michelle Yongmei

Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.

HOKF: High Order Kalman Filter for Epilepsy Forecasting Modeling.

Science.gov (United States)

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2017-08-01

Epilepsy forecasting has been extensively studied using high-order time series obtained from scalp-recorded electroencephalography (EEG). An accurate seizure prediction system would not only help significantly improve patients' quality of life, but would also facilitate new therapeutic strategies to manage epilepsy. This paper thus proposes an improved Kalman Filter (KF) algorithm to mine seizure forecasts from neural activity by modeling three properties in the high-order EEG time series: noise, temporal smoothness, and tensor structure. The proposed High-Order Kalman Filter (HOKF) is an extension of the standard Kalman filter, for which higher-order modeling is limited. The efficient dynamic of HOKF system preserves the tensor structure of the observations and latent states. As such, the proposed method offers two main advantages: (i) effectiveness with HOKF results in hidden variables that capture major evolving trends suitable to predict neural activity, even in the presence of missing values; and (ii) scalability in that the wall clock time of the HOKF is linear with respect to the number of time-slices of the sequence. The HOKF algorithm is examined in terms of its effectiveness and scalability by conducting forecasting and scalability experiments with a real epilepsy EEG dataset. The results of the simulation demonstrate the superiority of the proposed method over the original Kalman Filter and other existing methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Conduction velocity of action potentials measured from unidimensional latency-topography in human and frog skeletal muscle fibers.

Science.gov (United States)

Homma, S; Nakajima, Y; Hayashi, K; Toma, S

1986-01-01

Conduction of an action potential along skeletal muscle fibers was graphically displayed by unidimensional latency-topography, UDLT. Since the slopes of the equipotential line were linear and the width of the line was constant, it was possible to calculate conduction velocity from the slope. To determine conduction direction of the muscle action potential elicited by electric stimulation applied directly to the muscle, surface recording electrodes were placed on a two-dimensional plane over a human muscle. Thus a bi-dimensional topography was obtained. Then, twelve or sixteen surface electrodes were placed linearly along the longitudinal direction of the action potential conduction which was disclosed by the bi-dimensional topography. Thus conduction velocity of muscle action potential in man, calculated from the slope, was for m. brachioradialis, 3.9 +/- 0.4 m/s; for m. biceps brachii, 3.6 +/- 0.2 m/s; for m. sternocleidomastoideus, 3.6 +/- 0.4 m/s. By using a tungsten microelectrode to stimulate the motor axons, a convex-like equipotential line of an action potential in UDLT was obtained from human muscle fibers. Since a similar pattern of UDLT was obtained from experiments on isolated frog muscles, in which the muscle action potential was elicited by stimulating the motor axon, it was assumed that the maximum of the curve corresponds to the end-plate region, and that the slopes on both sides indicate bi-directional conduction of the action potential.

An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model

International Nuclear Information System (INIS)

Zhang, Xu; Wang, Yujie; Yang, Duo; Chen, Zonghai

2016-01-01

Accurate estimation of battery pack state-of-charge plays a very important role for electric vehicles, which directly reflects the behavior of battery pack usage. However, the inconsistency of battery makes the estimation of battery pack state-of-charge different from single cell. In this paper, to estimate the battery pack state-of-charge on-line, the definition of battery pack is proposed, and the relationship between the total available capacity of battery pack and single cell is put forward to analyze the energy efficiency influenced by battery inconsistency, then a lumped parameter battery model is built up to describe the dynamic behavior of battery pack. Furthermore, the extend Kalman filter-unscented Kalman filter algorithm is developed to identify the parameters of battery pack and forecast state-of-charge concurrently. The extend Kalman filter is applied to update the battery pack parameters by real-time measured data, while the unscented Kalman filter is employed to estimate the battery pack state-of-charge. Finally, the proposed approach is verified by experiments operated on the lithium-ion battery under constant current condition and the dynamic stress test profiles. Experimental results indicate that the proposed method can estimate the battery pack state-of-charge with high accuracy. - Highlights: • A novel space state equation is built to describe the pack dynamic behavior. • The dual filters method is used to estimate the pack state-of-charge. • Battery inconsistency is considered to analyze the pack usage efficiency. • The accuracy of the proposed method is verified under different conditions.

Evidence-Based Evaluation of Inferior Vena Cava Filter Complications Based on Filter Type

Science.gov (United States)

Deso, Steven E.; Idakoji, Ibrahim A.; Kuo, William T.

2016-01-01

Many inferior vena cava (IVC) filter types, along with their specific risks and complications, are not recognized. The purpose of this study was to evaluate the various FDA-approved IVC filter types to determine device-specific risks, as a way to help identify patients who may benefit from ongoing follow-up versus prompt filter retrieval. An evidence-based electronic search (FDA Premarket Notification, MEDLINE, FDA MAUDE) was performed to identify all IVC filter types and device-specific complications from 1980 to 2014. Twenty-three IVC filter types (14 retrievable, 9 permanent) were identified. The devices were categorized as follows: conical (n = 14), conical with umbrella (n = 1), conical with cylindrical element (n = 2), biconical with cylindrical element (n = 2), helical (n = 1), spiral (n = 1), and complex (n = 1). Purely conical filters were associated with the highest reported risks of penetration (90–100%). Filters with cylindrical or umbrella elements were associated with the highest reported risk of IVC thrombosis (30–50%). Conical Bard filters were associated with the highest reported risks of fracture (40%). The various FDA-approved IVC filter types were evaluated for device-specific complications based on best current evidence. This information can be used to guide and optimize clinical management in patients with indwelling IVC filters. PMID:27247477

Bragg reflection transmission filters for variable resolution monochromators

International Nuclear Information System (INIS)

Chapman, D.

1989-01-01

There are various methods for improving the angular and spectral resolution of monochromator and analyzer systems. The novel system described here, though limited to higher x-ray energies (>20keV), is based on a dynamical effect occurring on the transmitted beam with a thin perfect crystal plate set in the Bragg reflection case. In the case of Bragg reflection from a perfect crystal, the incident beam is rapidly attenuated as it penetrates the crystal in the range of reflection. This extinction length is of the order of microns. The attenuation length, which determines the amount of normal transmission through the plate is generally much longer. Thus, in the range of the Bragg reflection the attenuation of the transmitted beam can change by several orders of magnitude with a small change in energy or angle. This thin crystal plate cuts a notch in the transmitted beam with a width equal to its Darwin width, thus acting as a transmission filter. When used in a non-dispersive mode with other monochromator crystals, the filter when set at the Bragg angle will reflect the entire Darwin width of the incident beam and transmit the wings of the incident beam distribution. When the element is offset in angle by some fraction of the Darwin width, the filter becomes useful in adjusting the angular width of the transmitted beam and removing a wing. Used in pairs with a symmetric offset, the filters can be used to continuously adjust the intrinsic angular divergence of the beam with good wing reduction. Instances where such filters may be useful are in improving the angular resolution of a small angle scattering camera. These filters may be added to a Bonse-Hart camera with one pair on the incident beam to reduce the intrinsic beam divergence and a second pair on the analyzer arm to improve the analyzer resolution. 2 refs., 3 Figs

Higher safety and saving of filter material with multi-way sorption filters

International Nuclear Information System (INIS)

Ohlmeyer, M.; Benzel, M.

1978-01-01

The multi-way filter 'Nuclear Karlsruhe' satisfies the requirements of operational safety, high utilisation of the filter material and low pressure drop. An important factor contributing to increased operational safety is due to the fact that the nearly total utilisation of the filter material eliminates the need for optimisation weighing costs against safety. The reduction in filter material consumption reduces not only the direct procurement costs but also the costs of nuclear plants, is radioactive. This contributes in several respects towards a better protection of the environment. The MWS filter can also be used, and presents the same advantages, in non-nuclear plants. (orig.) [de

Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach.

Science.gov (United States)

Wang, Qian; Molenaar, Peter; Harsh, Saurabh; Freeman, Kenneth; Xie, Jinyu; Gold, Carol; Rovine, Mike; Ulbrecht, Jan

2014-03-01

An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control. © 2014 Diabetes Technology Society.