A hybrid damping method for LLCL-filter based grid-tied inverter with a digital filter and an RC parallel passive damper

DEFF Research Database (Denmark)

Wu, Weimin; Lin, Zhe; Sun, Yunjie

2013-01-01

Grid-tied inverters have been widely used to inject the renewable energies into the distributed power generation systems. However, a large variation of the grid impedance challenges the stability of the high-order power filter based grid-tied inverter. Many passive and active damping methods have...... been proposed to overcome this issue. Recently, a composite passive damping method for a high-order power filter based grid-tied inverter with an RC parallel damper and an RL series damper was presented to eliminate this problem, but at the cost of more material and power losses. In this paper...

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.

Design of quadrature mirror filter bank using Lagrange multiplier method based on fractional derivative constraints

Directory of Open Access Journals (Sweden)

B. Kuldeep

2015-06-01

Full Text Available Fractional calculus has recently been identified as a very important mathematical tool in the field of signal processing. Digital filters designed by fractional derivatives give more accurate frequency response in the prescribed frequency region. Digital filters are most important part of multi-rate filter bank systems. In this paper, an improved method based on fractional derivative constraints is presented for the design of two-channel quadrature mirror filter (QMF bank. The design problem is formulated as minimization of L2 error of filter bank transfer function in passband, stopband interval and at quadrature frequency, and then Lagrange multiplier method with fractional derivative constraints is applied to solve it. The proposed method is then successfully applied for the design of two-channel QMF bank with higher order filter taps. Performance of the QMF bank design is then examined through study of various parameters such as passband error, stopband error, transition band error, peak reconstruction error (PRE, stopband attenuation (As. It is found that, the good design can be obtained with the change of number and value of fractional derivative constraint coefficients.

A composite passive damping method of the LLCL-filter based grid-tied inverter

DEFF Research Database (Denmark)

Wu, Weimin; Huang, Min; Sun, Yunjie

2012-01-01

This paper investigates the maximum and the minimum gain of the proportional resonant based grid current controller for a grid-tied inverter with a passive damped high-order power filter. It is found that the choice of the controller gain is limited to the local maximum amplitude determined by Q......-factor around the characteristic frequency of the filter and grid impedance. To obtain the Q-factor of a high-order system, an equivalent circuit analysis method is proposed and illustrated through several classical passive damped LCL- and LLCL-filters. It is shown that both the RC parallel damper...... that is in parallel with the capacitor of the LCL-filter or with the Lf-Cf resonant circuit of the LLCL-filter, and the RL series damper in series with the grid-side inductor have their own application limits. Thus, a composite passive damped LLCL-filter for the grid-tied inverter is proposed, which can effectively...

Damping Methods for Resonances Caused by LCL-Filter-Based Current-Controlled Grid-Tied Power Inverters

DEFF Research Database (Denmark)

Wu, Weimin; Liu, Yuan; He, Yuanbin

2017-01-01

Grid-tied voltage source inverters using LCL filter have been widely adopted in distributed power generation systems (DPGSs). As high-order LCL filters contain multiple resonant frequencies, switching harmonics generated by the inverter and current harmonics generated by the active/passive loads...... innovative damping methods have been proposed. A comprehensive overview on those contributions and their classification on the inverter- and grid-side damping measures are presented. Based on the concept of the impedance-based stability analysis, all damping methods can ensure the system stability...

Digital notch filter based active damping for LCL filters

DEFF Research Database (Denmark)

Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin

2015-01-01

. In contrast, the active damping does not require any dissipation elements, and thus has become of increasing interest. As a result, a vast of active damping solutions have been reported, among which multi-loop control systems and additional sensors are necessary, leading to increased cost and complexity....... In this paper, a notch filter based active damping without the requirement of additional sensors is proposed, where the inverter current is employed as the feedback variable. Firstly, a design method of the notch filter for active damping is presented. The entire system stability has then been investigated...... in the z-domain. Simulations and experiments are carried out to verify the proposed active damping method. Both results have confirmed that the notch filter based active damping can ensure the entire system stability in the case of resonances with a good system performance....

A method of incident angle estimation for high resolution spectral recovery in filter-array-based spectrometers

Science.gov (United States)

Kim, Cheolsun; Lee, Woong-Bi; Ju, Gun Wu; Cho, Jeonghoon; Kim, Seongmin; Oh, Jinkyung; Lim, Dongsung; Lee, Yong Tak; Lee, Heung-No

2017-02-01

In recent years, there has been an increasing interest in miniature spectrometers for research and development. Especially, filter-array-based spectrometers have advantages of low cost and portability, and can be applied in various fields such as biology, chemistry and food industry. Miniaturization in optical filters causes degradation of spectral resolution due to limitations on spectral responses and the number of filters. Nowadays, many studies have been reported that the filter-array-based spectrometers have achieved resolution improvements by using digital signal processing (DSP) techniques. The performance of the DSP-based spectral recovery highly depends on the prior information of transmission functions (TFs) of the filters. The TFs vary with respect to an incident angle of light onto the filter-array. Conventionally, it is assumed that the incident angle of light on the filters is fixed and the TFs are known to the DSP. However, the incident angle is inconstant according to various environments and applications, and thus TFs also vary, which leads to performance degradation of spectral recovery. In this paper, we propose a method of incident angle estimation (IAE) for high resolution spectral recovery in the filter-array-based spectrometers. By exploiting sparse signal reconstruction of the L1- norm minimization, IAE estimates an incident angle among all possible incident angles which minimizes the error of the reconstructed signal. Based on IAE, DSP effectively provides a high resolution spectral recovery in the filter-array-based spectrometers.

Fine-filter method for Raman lidar based on wavelength division multiplexing and fiber Bragg grating.

Science.gov (United States)

Wang, Jun; Zheng, Jiao; Lu, Hong; Yan, Qing; Wang, Li; Liu, Jingjing; Hua, Dengxin

2017-11-01

Atmospheric temperature is one of the important parameters for the description of the atmospheric state. Most of the detection approaches to atmospheric temperature monitoring are based on rotational Raman scattering for better understanding atmospheric dynamics, thermodynamics, atmospheric transmission, and radiation. In this paper, we present a fine-filter method based on wavelength division multiplexing, incorporating a fiber Bragg grating in the visible spectrum for the rotational Raman scattering spectrum. To achieve high-precision remote sensing, the strong background noise is filtered out by using the secondary cascaded light paths. Detection intensity and the signal-to-noise ratio are improved by increasing the utilization rate of return signal form atmosphere. Passive temperature compensation is employed to reduce the temperature sensitivity of fiber Bragg grating. In addition, the proposed method provides a feasible solution for the filter system with the merits of miniaturization, high anti-interference, and high stability in the space-based platform.

Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns

Science.gov (United States)

Zhou, Qiuling; Tang, Chen; Li, Biyuan; Wang, Linlin; Lei, Zhenkun; Tang, Shuwei

2018-01-01

The filtering of discontinuous optical fringe patterns is a challenging problem faced in this area. This paper is concerned with oriented partial differential equations (OPDEs)-based image filtering methods for discontinuous optical fringe patterns. We redefine a new controlling speed function to depend on the orientation coherence. The orientation coherence can be used to distinguish the continuous regions and the discontinuous regions, and can be calculated by utilizing fringe orientation. We introduce the new controlling speed function to the previous OPDEs and propose adaptive OPDEs filtering models. According to our proposed adaptive OPDEs filtering models, the filtering in the continuous and discontinuous regions can be selectively carried out. We demonstrate the performance of the proposed adaptive OPDEs via application to the simulated and experimental fringe patterns, and compare our methods with the previous OPDEs.

Motion estimation using point cluster method and Kalman filter.

Science.gov (United States)

Senesh, M; Wolf, A

2009-05-01

The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal

A cognition-based method to ease the computational load for an extended Kalman filter.

Science.gov (United States)

Li, Yanpeng; Li, Xiang; Deng, Bin; Wang, Hongqiang; Qin, Yuliang

2014-12-03

The extended Kalman filter (EKF) is the nonlinear model of a Kalman filter (KF). It is a useful parameter estimation method when the observation model and/or the state transition model is not a linear function. However, the computational requirements in EKF are a difficulty for the system. With the help of cognition-based designation and the Taylor expansion method, a novel algorithm is proposed to ease the computational load for EKF in azimuth predicting and localizing under a nonlinear observation model. When there are nonlinear functions and inverse calculations for matrices, this method makes use of the major components (according to current performance and the performance requirements) in the Taylor expansion. As a result, the computational load is greatly lowered and the performance is ensured. Simulation results show that the proposed measure will deliver filtering output with a similar precision compared to the regular EKF. At the same time, the computational load is substantially lowered.

Evaluation of sampling methods for Bacillus spore-contaminated HVAC filters

OpenAIRE

Calfee, M. Worth; Rose, Laura J.; Tufts, Jenia; Morse, Stephen; Clayton, Matt; Touati, Abderrahmane; Griffin-Gatchalian, Nicole; Slone, Christina; McSweeney, Neal

2013-01-01

The objective of this study was to compare an extraction-based sampling method to two vacuum-based sampling methods (vacuum sock and 37 mm cassette filter) with regards to their ability to recover Bacillus atrophaeus spores (surrogate for Bacillus anthracis) from pleated heating, ventilation, and air conditioning (HVAC) filters that are typically found in commercial and residential buildings. Electrostatic and mechanical HVAC filters were tested, both without and after loading with dust to 50...

Voxel-Based Spatial Filtering Method for Canopy Height Retrieval from Airborne Single-Photon Lidar

Directory of Open Access Journals (Sweden)

Hao Tang

2016-09-01

Full Text Available Airborne single-photon lidar (SPL is a new technology that holds considerable potential for forest structure and carbon monitoring at large spatial scales because it acquires 3D measurements of vegetation faster and more efficiently than conventional lidar instruments. However, SPL instruments use green wavelength (532 nm lasers, which are sensitive to background solar noise, and therefore SPL point clouds require more elaborate noise filtering than other lidar instruments to determine canopy heights, particularly in daytime acquisitions. Histogram-based aggregation is a commonly used approach for removing noise from photon counting lidar data, but it reduces the resolution of the dataset. Here we present an alternate voxel-based spatial filtering method that filters noise points efficiently while largely preserving the spatial integrity of SPL data. We develop and test our algorithms on an experimental SPL dataset acquired over Garrett County in Maryland, USA. We then compare canopy attributes retrieved using our new algorithm with those obtained from the conventional histogram binning approach. Our results show that canopy heights derived using the new algorithm have a strong agreement with field-measured heights (r2 = 0.69, bias = 0.42 m, RMSE = 4.85 m and discrete return lidar heights (r2 = 0.94, bias = 1.07 m, RMSE = 2.42 m. Results are consistently better than height accuracies from the histogram method (field data: r2 = 0.59, bias = 0.00 m, RMSE = 6.25 m; DRL: r2 = 0.78, bias = −0.06 m and RMSE = 4.88 m. Furthermore, we find that the spatial-filtering method retains fine-scale canopy structure detail and has lower errors over steep slopes. We therefore believe that automated spatial filtering algorithms such as the one presented here can support large-scale, canopy structure mapping from airborne SPL data.

Evaluation of a Cubature Kalman Filtering-Based Phase Unwrapping Method for Differential Interferograms with High Noise in Coal Mining Areas

Directory of Open Access Journals (Sweden)

Wanli Liu

2015-07-01

Full Text Available Differential interferometric synthetic aperture radar has been shown to be effective for monitoring subsidence in coal mining areas. Phase unwrapping can have a dramatic influence on the monitoring result. In this paper, a filtering-based phase unwrapping algorithm in combination with path-following is introduced to unwrap differential interferograms with high noise in mining areas. It can perform simultaneous noise filtering and phase unwrapping so that the pre-filtering steps can be omitted, thus usually retaining more details and improving the detectable deformation. For the method, the nonlinear measurement model of phase unwrapping is processed using a simplified Cubature Kalman filtering, which is an effective and efficient tool used in many nonlinear fields. Three case studies are designed to evaluate the performance of the method. In Case 1, two tests are designed to evaluate the performance of the method under different factors including the number of multi-looks and path-guiding indexes. The result demonstrates that the unwrapped results are sensitive to the number of multi-looks and that the Fisher Distance is the most suitable path-guiding index for our study. Two case studies are then designed to evaluate the feasibility of the proposed phase unwrapping method based on Cubature Kalman filtering. The results indicate that, compared with the popular Minimum Cost Flow method, the Cubature Kalman filtering-based phase unwrapping can achieve promising results without pre-filtering and is an appropriate method for coal mining areas with high noise.

Comparison of testing methods for particulate filters

International Nuclear Information System (INIS)

Ullmann, W.; Przyborowski, S.

1983-01-01

Four testing methods for particulate filters were compared by using the test rigs of the National Board of Nuclear Safety and Radiation Protection: 1) Measurement of filter penetration P as a function of particle size d by using a polydisperse NaC1 test aerosol and a scintillation particle counter; 2) Modified sodium flame test for measurement of total filter penetration P for various polydisperse NaC1 test aerosols; 3) Measurement of total filter penetration P for a polydisperse NaC1 test aerosol labelled with short-lived radon daughter products; 4) Measurement of total filter penetration P for a special paraffin oil test aerosol (oil fog test used in FRG according DIN 24 184, test aerosol A). The investigations were carried out on sheets of glass fibre paper (five grades of paper). Detailed information about the four testing methods and the used particle size distributions is given. The different results of the various methods are the base for the discussion of the most important parameters which influence the filter penetration P. The course of the function P=f(d) shows the great influence of the particle size. As expected there was also found a great dependence both from the test aerosol as well as from the principle and the measuring range of the aerosol-measuring device. The differences between the results of the various test methods are greater the lower the penetration. The use of NaCl test aerosol with various particle size distributions gives great differences for the respective penetration values. On the basis of these results and the values given by Dorman conclusions are made about the investigation of particulate filters both for the determination of filter penetration P as well as for the leak test of installed filters

A new greedy search method for the design of digital IIR filter

Directory of Open Access Journals (Sweden)

Ranjit Kaur

2015-07-01

Full Text Available A new greedy search method is applied in this paper to design the optimal digital infinite impulse response (IIR filter. The greedy search method is based on binary successive approximation (BSA and evolutionary search (ES. The suggested greedy search method optimizes the magnitude response and the phase response simultaneously and also finds the lowest order of the filter. The order of the filter is controlled by a control gene whose value is also optimized along with the filter coefficients to obtain optimum order of designed IIR filter. The stability constraints of IIR filter are taken care of during the design procedure. To determine the trade-off relationship between conflicting objectives in the non-inferior domain, the weighting method is exploited. The proposed approach is effectively applied to solve the multiobjective optimization problems of designing the digital low-pass (LP, high-pass (HP, bandpass (BP, and bandstop (BS filters. It has been demonstrated that this technique not only fulfills all types of filter performance requirements, but also the lowest order of the filter can be found. The computational experiments show that the proposed approach gives better digital IIR filters than the existing evolutionary algorithm (EA based methods.

A novel method for EMG decomposition based on matched filters

Directory of Open Access Journals (Sweden)

Ailton Luiz Dias Siqueira Júnior

Full Text Available Introduction Decomposition of electromyography (EMG signals into the constituent motor unit action potentials (MUAPs can allow for deeper insights into the underlying processes associated with the neuromuscular system. The vast majority of the methods for EMG decomposition found in the literature depend on complex algorithms and specific instrumentation. As an attempt to contribute to solving these issues, we propose a method based on a bank of matched filters for the decomposition of EMG signals. Methods Four main units comprise our method: a bank of matched filters, a peak detector, a motor unit classifier and an overlapping resolution module. The system’s performance was evaluated with simulated and real EMG data. Classification accuracy was measured by comparing the responses of the system with known data from the simulator and with the annotations of a human expert. Results The results show that decomposition of non-overlapping MUAPs can be achieved with up to 99% accuracy for signals with up to 10 active motor units and a signal-to-noise ratio (SNR of 10 dB. For overlapping MUAPs with up to 10 motor units per signal and a SNR of 20 dB, the technique allows for correct classification of approximately 71% of the MUAPs. The method is capable of processing, decomposing and classifying a 50 ms window of data in less than 5 ms using a standard desktop computer. Conclusion This article contributes to the ongoing research on EMG decomposition by describing a novel technique capable of delivering high rates of success by means of a fast algorithm, suggesting its possible use in future real-time embedded applications, such as myoelectric prostheses control and biofeedback systems.

Nanoparticle filtration performance of NIOSH-certified particulate air-purifying filtering facepiece respirators: evaluation by light scattering photometric and particle number-based test methods.

Science.gov (United States)

Rengasamy, Samy; Eimer, Benjamin C

2012-01-01

National Institute for Occupational Safety and Health (NIOSH) certification test methods employ charge neutralized NaCl or dioctyl phthalate (DOP) aerosols to measure filter penetration levels of air-purifying particulate respirators photometrically using a TSI 8130 automated filter tester at 85 L/min. A previous study in our laboratory found that widely different filter penetration levels were measured for nanoparticles depending on whether a particle number (count)-based detector or a photometric detector was used. The purpose of this study was to better understand the influence of key test parameters, including filter media type, challenge aerosol size range, and detector system. Initial penetration levels for 17 models of NIOSH-approved N-, R-, and P-series filtering facepiece respirators were measured using the TSI 8130 photometric method and compared with the particle number-based penetration (obtained using two ultrafine condensation particle counters) for the same challenge aerosols generated by the TSI 8130. In general, the penetration obtained by the photometric method was less than the penetration obtained with the number-based method. Filter penetration was also measured for ambient room aerosols. Penetration measured by the TSI 8130 photometric method was lower than the number-based ambient aerosol penetration values. Number-based monodisperse NaCl aerosol penetration measurements showed that the most penetrating particle size was in the 50 nm range for all respirator models tested, with the exception of one model at ~200 nm size. Respirator models containing electrostatic filter media also showed lower penetration values with the TSI 8130 photometric method than the number-based penetration obtained for the most penetrating monodisperse particles. Results suggest that to provide a more challenging respirator filter test method than what is currently used for respirators containing electrostatic media, the test method should utilize a sufficient number

A Method for SINS Alignment with Large Initial Misalignment Angles Based on Kalman Filter with Parameters Resetting

Directory of Open Access Journals (Sweden)

Xixiang Liu

2014-01-01

Full Text Available In the initial alignment process of strapdown inertial navigation system (SINS, large initial misalignment angles always bring nonlinear problem, which causes alignment failure when the classical linear error model and standard Kalman filter are used. In this paper, the problem of large misalignment angles in SINS initial alignment is investigated, and the key reason for alignment failure is given as the state covariance from Kalman filter cannot represent the true one during the steady filtering process. According to the analysis, an alignment method for SINS based on multiresetting the state covariance matrix of Kalman filter is designed to deal with large initial misalignment angles, in which classical linear error model and standard Kalman filter are used, but the state covariance matrix should be multireset before the steady process until large misalignment angles are decreased to small ones. The performance of the proposed method is evaluated by simulation and car test, and the results indicate that the proposed method can fulfill initial alignment with large misalignment angles effectively and the alignment accuracy of the proposed method is as precise as that of alignment with small misalignment angles.

Research based on matlab method of digital trapezoidal shaping filter

International Nuclear Information System (INIS)

Zhou Qinghua; Zhang Ruanyu; Li Taihua

2008-01-01

In order to develop digital shaping system fast and conveniently, the paper presents the method of optimizing the trapezoidal shaping filter's parameters by using MATLAB, and discusses the affections of the parameters to the shaping result by this method. (authors)

Bayesian target tracking based on particle filter

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

Regularization by fractional filter methods and data smoothing

International Nuclear Information System (INIS)

Klann, E; Ramlau, R

2008-01-01

This paper is concerned with the regularization of linear ill-posed problems by a combination of data smoothing and fractional filter methods. For the data smoothing, a wavelet shrinkage denoising is applied to the noisy data with known error level δ. For the reconstruction, an approximation to the solution of the operator equation is computed from the data estimate by fractional filter methods. These fractional methods are based on the classical Tikhonov and Landweber method, but avoid, at least partially, the well-known drawback of oversmoothing. Convergence rates as well as numerical examples are presented

General filtering method for electronic speckle pattern interferometry fringe images with various densities based on variational image decomposition.

Science.gov (United States)

Li, Biyuan; Tang, Chen; Gao, Guannan; Chen, Mingming; Tang, Shuwei; Lei, Zhenkun

2017-06-01

Filtering off speckle noise from a fringe image is one of the key tasks in electronic speckle pattern interferometry (ESPI). In general, ESPI fringe images can be divided into three categories: low-density fringe images, high-density fringe images, and variable-density fringe images. In this paper, we first present a general filtering method based on variational image decomposition that can filter speckle noise for ESPI fringe images with various densities. In our method, a variable-density ESPI fringe image is decomposed into low-density fringes, high-density fringes, and noise. A low-density fringe image is decomposed into low-density fringes and noise. A high-density fringe image is decomposed into high-density fringes and noise. We give some suitable function spaces to describe low-density fringes, high-density fringes, and noise, respectively. Then we construct several models and numerical algorithms for ESPI fringe images with various densities. And we investigate the performance of these models via our extensive experiments. Finally, we compare our proposed models with the windowed Fourier transform method and coherence enhancing diffusion partial differential equation filter. These two methods may be the most effective filtering methods at present. Furthermore, we use the proposed method to filter a collection of the experimentally obtained ESPI fringe images with poor quality. The experimental results demonstrate the performance of our proposed method.

Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

Science.gov (United States)

Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choe, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B; Gupta, Neha; Kohane, Isaac S; Green, Robert C; Kong, Sek Won

2014-08-01

As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous single nucleotide variants (SNVs); 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery in NA12878, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and an ensemble genotyping would be essential to minimize false-positive DNM candidates. © 2014 WILEY PERIODICALS, INC.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

Directory of Open Access Journals (Sweden)

Yuanqiang Ren

2017-05-01

Full Text Available Structural health monitoring (SHM of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

An adaptive filtering method based on EMD for X-ray pulsar navigation with uncertain measurement noise

Directory of Open Access Journals (Sweden)

Li N.

2017-01-01

Full Text Available Affected by the unstable pulse radiation and the pulsar directional errors, the statistical characteristics of the pulsar measurement noise may vary with time slowly and cannot be accurately determined, which cause the filtering accuracy of the extended Kalman filter(EKF in pulsar navigation positioning system decline sharply or even diverge. To solve this problem, an adaptive extended Kalman filtering algorithm based on the empirical mode decomposition(EMD is proposed. In this method, the high frequency noise is separated from measurement information of pulsar by the method of EMD, and the noise variance can be estimated to update the parameters of EKF. The simulation results demonstrate that compared with conventional EKF, the proposed method can adaptively track the change of the measurement noise, and still keeps high estimation accuracy with unknown measurement noise, the positioning accuracy of the pulsar navigation is improved simultaneously.

Evaluation of sampling methods for Bacillus spore-contaminated HVAC filters.

Science.gov (United States)

Calfee, M Worth; Rose, Laura J; Tufts, Jenia; Morse, Stephen; Clayton, Matt; Touati, Abderrahmane; Griffin-Gatchalian, Nicole; Slone, Christina; McSweeney, Neal

2014-01-01

The objective of this study was to compare an extraction-based sampling method to two vacuum-based sampling methods (vacuum sock and 37mm cassette filter) with regards to their ability to recover Bacillus atrophaeus spores (surrogate for Bacillus anthracis) from pleated heating, ventilation, and air conditioning (HVAC) filters that are typically found in commercial and residential buildings. Electrostatic and mechanical HVAC filters were tested, both without and after loading with dust to 50% of their total holding capacity. The results were analyzed by one-way ANOVA across material types, presence or absence of dust, and sampling device. The extraction method gave higher relative recoveries than the two vacuum methods evaluated (p≤0.001). On average, recoveries obtained by the vacuum methods were about 30% of those achieved by the extraction method. Relative recoveries between the two vacuum methods were not significantly different (p>0.05). Although extraction methods yielded higher recoveries than vacuum methods, either HVAC filter sampling approach may provide a rapid and inexpensive mechanism for understanding the extent of contamination following a wide-area biological release incident. Published by Elsevier B.V.

Evaluation of the filtration performance of NIOSH-approved N95 filtering facepiece respirators by photometric and number-based test methods.

Science.gov (United States)

Rengasamy, Samy; Miller, Adam; Eimer, Benjamin C

2011-01-01

N95 particulate filtering facepiece respirators are certified by measuring penetration levels photometrically with a presumed severe case test method using charge neutralized NaCl aerosols at 85 L/min. However, penetration values obtained by photometric methods have not been compared with count-based methods using contemporary respirators composed of electrostatic filter media and challenged with both generated and ambient aerosols. To better understand the effects of key test parameters (e.g., particle charge, detection method), initial penetration levels for five N95 model filtering facepiece respirators were measured using NaCl aerosols with the aerosol challenge and test equipment employed in the NIOSH respirator certification method (photometric) and compared with an ultrafine condensation particle counter method (count based) for the same NaCl aerosols as well as for ambient room air particles. Penetrations using the NIOSH test method were several-fold less than the penetrations obtained by the ultrafine condensation particle counter for NaCl aerosols as well as for room particles indicating that penetration measurement based on particle counting offers a more difficult challenge than the photometric method, which lacks sensitivity for particles photometric method may not be a more challenging aerosol test method. Filter penetrations can vary among workplaces with different particle size distributions, which suggests the need for the development of new or revised "more challenging" aerosol test methods for NIOSH certification of respirators.

Washing method of filter

International Nuclear Information System (INIS)

Izumidani, Masakiyo; Tanno, Kazuo.

1978-01-01

Purpose: To enable automatic filter operation and facilitate back-washing operation by back-washing filters used in a bwr nuclear power plant utilizing an exhaust gas from a ventilator or air conditioner. Method: Exhaust gas from an exhaust pipe of an ventilator or air conditioner is pressurized in a compressor and then introduced in a back-washing gas tank. Then, the exhaust gas pressurized to a predetermined pressure is blown from the inside to the outside of a filter to thereby separate impurities collected on the filter elements and introduce them to a waste tank. (Furukawa, Y.)

Regularization of DT-MRI Using 3D Median Filtering Methods

Directory of Open Access Journals (Sweden)

Soondong Kwon

2014-01-01

Full Text Available DT-MRI (diffusion tensor magnetic resonance imaging tractography is a method to determine the architecture of axonal fibers in the central nervous system by computing the direction of the principal eigenvectors obtained from tensor matrix, which is different from the conventional isotropic MRI. Tractography based on DT-MRI is known to need many computations and is highly sensitive to noise. Hence, adequate regularization methods, such as image processing techniques, are in demand. Among many regularization methods we are interested in the median filtering method. In this paper, we extended two-dimensional median filters already developed to three-dimensional median filters. We compared four median filtering methods which are two-dimensional simple median method (SM2D, two-dimensional successive Fermat method (SF2D, three-dimensional simple median method (SM3D, and three-dimensional successive Fermat method (SF3D. Three kinds of synthetic data with different altitude angles from axial slices and one kind of human data from MR scanner are considered for numerical implementation by the four filtering methods.

Single-Phase LLCL-Filter-based Grid-Tied Inverter with Low-Pass Filter Based Capacitor Current Feedback Active damper

DEFF Research Database (Denmark)

Liu, Yuan; Wu, Weimin; Li, Yun

2016-01-01

The capacitor-current-feedback active damping method is attractive for high-order-filter-based high power grid-tied inverter when the grid impedance varies within a wide range. In order to improve the system control bandwidth and attenuate the high order grid background harmonics by using the quasi....... In this paper, a low pass filter is proposed to be inserted in the capacitor current feedback loop op LLCL-filter based grid-tied inverter together with a digital proportional and differential compensator. The detailed theoretical analysis is given. For verification, simulations on a 2kW/220V/10kHz LLCL...

The spatial filtering method for solid particle velocity measurement based on an electrostatic sensor

International Nuclear Information System (INIS)

Xu, Chuanlong; Tang, Guanghua; Zhou, Bin; Wang, Shimin

2009-01-01

The spatial filtering method for particle velocity measurement has the advantages of simplicity of the measurement system and convenience of data processing. In this paper, the relationship between solid particles mean velocity in a pneumatic pipeline and the power spectrum of the output signal of an electrostatic sensor was mathematically modeled. The effects of the length of the sensor, the thickness of the dielectric pipe and its length on the spatial filtering characteristics of the sensor were also investigated using the finite element method. As for the roughness of and the difficult determination of the peak frequency f max of the power spectrum characteristics of the output signal of the sensor, a wavelet analysis based filtering method was applied to smooth the curve, which can accurately determine the peak frequency f max . Finally, experiments were performed on a pilot dense phase pneumatic conveying rig at high pressure to test the performance of the velocity measurement system. The experimental results show that the system repeatability is within ±4% over a gas superficial velocity range of 8.63–18.62 m s −1 for a particle concentration range of 0.067–0.130 m 3 m −3

Feature-Based Nonlocal Polarimetric SAR Filtering

Directory of Open Access Journals (Sweden)

Xiaoli Xing

2017-10-01

Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

Improvement of chirped pulse contrast using electro-optic birefringence scanning filter method

International Nuclear Information System (INIS)

Zeng Shuguang; Wang Xianglin; Wang Qishan; Zhang Bin; Sun Nianchun; Wang Fei

2013-01-01

A method using scanning filter to improve the contrast of chirped pulse is proposed, and the principle of this method is analyzed. The scanning filter is compared with the existing pulse-picking technique and nonlinear filtering technique. The scanning filter is a temporal gate that is independent on the intensity of the pulses, but on the instantaneous wavelengths of light. Taking the electro-optic birefringence scanning filter as an example, the application of scanning filter methods is illustrated. Based on numerical simulation and experimental research, it is found that the electro-optic birefringence scanning filter can eliminate a prepulse which is several hundred picoseconds before the main pulse, and the main pulse can maintain a high transmissivity. (authors)

Emotion Recognition of Speech Signals Based on Filter Methods

Directory of Open Access Journals (Sweden)

Narjes Yazdanian

2016-10-01

Full Text Available Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered. The aim of this study was to determine a set of affective features the speech signal is based on emotions. In this study system was designs that include three mains sections, features extraction, features selection and classification. After extraction of useful features such as, mel frequency cepstral coefficient (MFCC, linear prediction cepstral coefficients (LPC, perceptive linear prediction coefficients (PLP, ferment frequency, zero crossing rate, cepstral coefficients and pitch frequency, Mean, Jitter, Shimmer, Energy, Minimum, Maximum, Amplitude, Standard Deviation, at a later stage with filter methods such as Pearson Correlation Coefficient, t-test, relief and information gain, we came up with a method to rank and select effective features in emotion recognition. Then Result, are given to the classification system as a subset of input. In this classification stage, multi support vector machine are used to classify seven type of emotion. According to the results, that method of relief, together with multi support vector machine, has the most classification accuracy with emotion recognition rate of 93.94%.

An Improved Filtering Method for Quantum Color Image in Frequency Domain

Science.gov (United States)

Li, Panchi; Xiao, Hong

2018-01-01

In this paper we investigate the use of quantum Fourier transform (QFT) in the field of image processing. We consider QFT-based color image filtering operations and their applications in image smoothing, sharpening, and selective filtering using quantum frequency domain filters. The underlying principle used for constructing the proposed quantum filters is to use the principle of the quantum Oracle to implement the filter function. Compared with the existing methods, our method is not only suitable for color images, but also can flexibly design the notch filters. We provide the quantum circuit that implements the filtering task and present the results of several simulation experiments on color images. The major advantages of the quantum frequency filtering lies in the exploitation of the efficient implementation of the quantum Fourier transform.

Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob

2015-01-01

some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously...... operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed...

A novel optimized LCL-filter designing method for grid connected converter

DEFF Research Database (Denmark)

Guohong, Zeng; Rasmussen, Tonny Wederberg; Teodorescu, Remus

2010-01-01

This paper presents a new LCL-filters optimized designing method for grid connected voltage source converter. This method is based on the analysis of converter output voltage components and inherent relations among LCL-filter parameters. By introducing an optimizing index of equivalent total capa...

The singular value filter: a general filter design strategy for PCA-based signal separation in medical ultrasound imaging.

Science.gov (United States)

Mauldin, F William; Lin, Dan; Hossack, John A

2011-11-01

A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, which we refer to as the blind source separation (BSS) method, as well as a simple frequency-based finite impulse response (FIR) filter used as a baseline for comparison. The performance of each filter was quantified in simulated lesion images as well as experimental cardiac ultrasound data. SVF was demonstrated in both simulation and experimental results, over a wide range of imaging conditions, to outperform the BSS and FIR filtering methods in terms of contrast-to-noise ratio (CNR) and motion tracking performance. In experimental mouse heart data, SVF provided excellent artifact suppression with an average CNR improvement of 1.8 dB with over 40% reduction in displacement tracking error. It was further demonstrated from simulation and experimental results that SVF provided superior clutter rejection, as reflected in larger CNR values, when filtering was achieved using complex pulse-echo received data and non-binary filter coefficients.

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.

Michelson interferometer based interleaver design using classic IIR filter decomposition.

Science.gov (United States)

Cheng, Chi-Hao; Tang, Shasha

2013-12-16

An elegant method to design a Michelson interferometer based interleaver using a classic infinite impulse response (IIR) filter such as Butterworth, Chebyshev, and elliptic filters as a starting point are presented. The proposed design method allows engineers to design a Michelson interferometer based interleaver from specifications seamlessly. Simulation results are presented to demonstrate the validity of the proposed design method.

A NEW METHOD OF CHANNEL FRICTION INVERSION BASED ON KALMAN FILTER WITH UNKNOWN PARAMETER VECTOR

Institute of Scientific and Technical Information of China (English)

CHENG Wei-ping; MAO Gen-hai; LIU Guo-hua

2005-01-01

Channel friction is an important parameter in hydraulic analysis.A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed.Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected.In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state.For the nonlinear equations, computations of sensitivity matrices are time-costly.Two simplified measures can reduce computing time, but not influence the results.One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.

Bds/gps Integrated Positioning Method Research Based on Nonlinear Kalman Filtering

Science.gov (United States)

Ma, Y.; Yuan, W.; Sun, H.

2017-09-01

In order to realize fast and accurate BDS/GPS integrated positioning, it is necessary to overcome the adverse effects of signal attenuation, multipath effect and echo interference to ensure the result of continuous and accurate navigation and positioning. In this paper, pseudo-range positioning is used as the mathematical model. In the stage of data preprocessing, using precise and smooth carrier phase measurement value to promote the rough pseudo-range measurement value without ambiguity. At last, the Extended Kalman Filter(EKF), the Unscented Kalman Filter(UKF) and the Particle Filter(PF) algorithm are applied in the integrated positioning method for higher positioning accuracy. The experimental results show that the positioning accuracy of PF is the highest, and UKF is better than EKF.

Flat microwave photonic filter based on hybrid of two filters

International Nuclear Information System (INIS)

Qi, Chunhui; Pei, Li; Ning, Tigang; Li, Jing; Gao, Song

2010-01-01

A new microwave photonic filter (MPF) hybrid of two filters that can realize both multiple taps and a flat bandpass or bandstop response is presented. Based on the phase character of a Mach–Zehnder modulator (MZM), a two taps finite impulse response (FIR) filter is obtained as the first part. The second part is obtained by taking full advantage of the wavelength selectivity of the fiber Bragg grating (FBG) and the gain of a erbium-doped fiber (EDF). Combining the two filters, the flat bandpass or bandstop response is realized by changing the coupler's factor k, the reflectivity of FBG1 R 1 or the gain of the EDF g. Optimizing the system parameters, a flat bandpass response with amplitude depth of more than 45 dB is obtained at k = 0.5, R 1 = 0.33, g = 10, and a flat bandstop response is also obtained at k = 0.4, R 1 = 0.5, g = 2. In addition, the free-spectral range (FSR) can be controlled by changing the length of the EDF and the length difference between two MZMs. The method is proved feasible by some experiments. Such a method offers realistic solutions to support future radio-frequency (RF) optical communication systems

A New Filter Design Method for Disturbed Multilayer Hopfield Neural Networks

Directory of Open Access Journals (Sweden)

AHN, C. K.

2011-05-01

Full Text Available This paper investigates the passivity based filtering problem for multilayer Hopfield neural networks with external disturbance. A new passivity based filter design method for multilayer Hopfield neural networks is developed to ensure that the filtering error system is exponentially stable and passive from the external disturbance vector to the output error vector. The unknown gain matrix is obtained by solving a linear matrix inequality (LMI, which can be easily facilitated by using some standard numerical packages. An illustrative example is given to demonstrate the effectiveness of the proposed filter.

Adaptive Subband Filtering Method for MEMS Accelerometer Noise Reduction

Directory of Open Access Journals (Sweden)

Piotr PIETRZAK

2008-12-01

Full Text Available Silicon microaccelerometers can be considered as an alternative to high-priced piezoelectric sensors. Unfortunately, relatively high noise floor of commercially available MEMS (Micro-Electro-Mechanical Systems sensors limits the possibility of their usage in condition monitoring systems of rotating machines. The solution of this problem is the method of signal filtering described in the paper. It is based on adaptive subband filtering employing Adaptive Line Enhancer. For filter weights adaptation, two novel algorithms have been developed. They are based on the NLMS algorithm. Both of them significantly simplify its software and hardware implementation and accelerate the adaptation process. The paper also presents the software (Matlab and hardware (FPGA implementation of the proposed noise filter. In addition, the results of the performed tests are reported. They confirm high efficiency of the solution.

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.

Analysis of Filter-Bank-Based Methods for Fast Serial Acquisition of BOC-Modulated Signals

Directory of Open Access Journals (Sweden)

Elena Simona Lohan

2007-09-01

Full Text Available Binary-offset-carrier (BOC signals, selected for Galileo and modernized GPS systems, pose significant challenges for the code acquisition, due to the ambiguities (deep fades which are present in the envelope of the correlation function (CF. This is different from the BPSK-modulated CDMA signals, where the main correlation lobe spans over 2-chip interval, without any ambiguities or deep fades. To deal with the ambiguities due to BOC modulation, one solution is to use lower steps of scanning the code phases (i.e., lower than the traditional step of 0.5 chips used for BPSK-modulated CDMA signals. Lowering the time-bin steps entails an increase in the number of timing hypotheses, and, thus, in the acquisition times. An alternative solution is to transform the ambiguous CF into an “unambiguous” CF, via adequate filtering of the signal. A generalized class of frequency-based unambiguous acquisition methods is proposed here, namely the filter-bank-based (FBB approaches. The detailed theoretical analysis of FBB methods is given for serial-search single-dwell acquisition in single path static channels and a comparison is made with other ambiguous and unambiguous BOC acquisition methods existing in the literature.

Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis

Science.gov (United States)

Li, Y.

2013-05-01

The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.

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.

Matrix pencil method-based reference current generation for shunt active power filters

DEFF Research Database (Denmark)

Terriche, Yacine; Golestan, Saeed; Guerrero, Josep M.

2018-01-01

response and works well under distorted and unbalanced voltage. Moreover, the proposed method can estimate the voltage phase accurately; this property enables the algorithm to compensate for both power factor and current unbalance. The effectiveness of the proposed method is verified using simulation...... are using the discrete Fourier transform (DFT) in the frequency domain or the instantaneous p–q theory and the synchronous reference frame in the time domain. The DFT, however, suffers from the picket-fence effect and spectral leakage. On the other hand, the DFT takes at least one cycle of the nominal...... frequency. The time-domain methods show a weakness under voltage distortion, which requires prior filtering techniques. The aim of this study is to present a fast yet effective method for generating the RCC for SAPFs. The proposed method, which is based on the matrix pencil method, has a fast dynamic...

New Statistics for Texture Classification Based on Gabor Filters

Directory of Open Access Journals (Sweden)

J. Pavlovicova

2007-09-01

Full Text Available The paper introduces a new method of texture segmentation efficiency evaluation. One of the well known texture segmentation methods is based on Gabor filters because of their orientation and spatial frequency character. Several statistics are used to extract more information from results obtained by Gabor filtering. Big amount of input parameters causes a wide set of results which need to be evaluated. The evaluation method is based on the normal distributions Gaussian curves intersection assessment and provides a new point of view to the segmentation method selection.

Restricted Kalman Filtering Theory, Methods, and Application

CERN Document Server

Pizzinga, Adrian

2012-01-01

In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where th

A Method against Interrupted-Sampling Repeater Jamming Based on Energy Function Detection and Band-Pass Filtering

Directory of Open Access Journals (Sweden)

Hui Yuan

2017-01-01

Full Text Available Interrupted-sampling repeater jamming (ISRJ is a new kind of coherent jamming to the large time-bandwidth linear frequency modulation (LFM signal. Many jamming modes, such as lifelike multiple false targets and dense false targets, can be made through setting up different parameters. According to the “storage-repeater-storage-repeater” characteristics of the ISRJ and the differences in the time-frequency-energy domain between the ISRJ signal and the target echo signal, one new method based on the energy function detection and band-pass filtering is proposed to suppress the ISRJ. The methods mainly consist of two parts: extracting the signal segments without ISRJ and constructing band-pass filtering function with low sidelobe. The simulation results show that the method is effective in the ISRJ with different parameters.

Improving the precision of the keyword-matching pornographic text filtering method using a hybrid model.

Science.gov (United States)

Su, Gui-yang; Li, Jian-hua; Ma, Ying-hua; Li, Sheng-hong

2004-09-01

With the flooding of pornographic information on the Internet, how to keep people away from that offensive information is becoming one of the most important research areas in network information security. Some applications which can block or filter such information are used. Approaches in those systems can be roughly classified into two kinds: metadata based and content based. With the development of distributed technologies, content based filtering technologies will play a more and more important role in filtering systems. Keyword matching is a content based method used widely in harmful text filtering. Experiments to evaluate the recall and precision of the method showed that the precision of the method is not satisfactory, though the recall of the method is rather high. According to the results, a new pornographic text filtering model based on reconfirming is put forward. Experiments showed that the model is practical, has less loss of recall than the single keyword matching method, and has higher precision.

DEMONSTRATION BULLETIN: COLLOID POLISHING FILTER METHOD - FILTER FLOW TECHNOLOGY, INC.

Science.gov (United States)

The Filter Flow Technology, Inc. (FFT) Colloid Polishing Filter Method (CPFM) was tested as a transportable, trailer mounted, system that uses sorption and chemical complexing phenomena to remove heavy metals and nontritium radionuclides from water. Contaminated waters can be pro...

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

Science.gov (United States)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

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)

Particle filter based MAP state estimation: A comparison

NARCIS (Netherlands)

Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha

2009-01-01

MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi

Active Damping Techniques for LCL-Filtered Inverters-Based Microgrids

DEFF Research Database (Denmark)

Lorzadeh, Iman; Firoozabadi, Mehdi Savaghebi; Askarian Abyaneh, Hossein

2015-01-01

LCL-type filters are widely used in gridconnected voltage source inverters, since it provides switching ripples reduction with lower cost and weight than the L-type counterpart. However, the inclusion of LCL-filters in voltage source inverters complicates the current control design regarding system...... the different active damping approaches for grid-connected inverters with LCL filters, which are based on high-order filters and additional feedbacks methods. These techniques are analyzed and discussed in detail....... stability issues; because an inherent resonance peak appears due to zero impedance at that resonance frequency. Moreover, in grid-interactive low-voltage microgrids, the interactions among the LCL-filtered-based parallel inverters may result in a more complex multiresonance issue which may compromise...

Design of Passive Power Filter for Hybrid Series Active Power Filter using Estimation, Detection and Classification Method

Science.gov (United States)

Swain, Sushree Diptimayee; Ray, Pravat Kumar; Mohanty, K. B.

2016-06-01

This research paper discover the design of a shunt Passive Power Filter (PPF) in Hybrid Series Active Power Filter (HSAPF) that employs a novel analytic methodology which is superior than FFT analysis. This novel approach consists of the estimation, detection and classification of the signals. The proposed method is applied to estimate, detect and classify the power quality (PQ) disturbance such as harmonics. This proposed work deals with three methods: the harmonic detection through wavelet transform method, the harmonic estimation by Kalman Filter algorithm and harmonic classification by decision tree method. From different type of mother wavelets in wavelet transform method, the db8 is selected as suitable mother wavelet because of its potency on transient response and crouched oscillation at frequency domain. In harmonic compensation process, the detected harmonic is compensated through Hybrid Series Active Power Filter (HSAPF) based on Instantaneous Reactive Power Theory (IRPT). The efficacy of the proposed method is verified in MATLAB/SIMULINK domain and as well as with an experimental set up. The obtained results confirm the superiority of the proposed methodology than FFT analysis. This newly proposed PPF is used to make the conventional HSAPF more robust and stable.

Comparison of high efficiency particulate filter testing methods

International Nuclear Information System (INIS)

1985-01-01

High Efficiency Particulate Air (HEPA) filters are used for the removal of submicron size particulates from air streams. In nuclear industry they are used as an important engineering safeguard to prevent the release of air borne radioactive particulates to the environment. HEPA filters used in the nuclear industry should therefore be manufactured and operated under strict quality control. There are three levels of testing HEPA filters: i) testing of the filter media; ii) testing of the assembled filter including filter media and filter housing; and iii) on site testing of the complete filter installation before putting into operation and later for the purpose of periodic control. A co-ordinated research programme on particulate filter testing methods was taken up by the Agency and contracts were awarded to the Member Countries, Belgium, German Democratic Republic, India and Hungary. The investigations carried out by the participants of the present co-ordinated research programme include the results of the nowadays most frequently used HEPA filter testing methods both for filter medium test, rig test and in-situ test purposes. Most of the experiments were carried out at ambient temperature and humidity, but indications were given to extend the investigations to elevated temperature and humidity in the future for the purpose of testing the performance of HEPA filter under severe conditions. A major conclusion of the co-ordinated research programme was that it was not possible to recommend one method as a reference method for in situ testing of high efficiency particulate air filters. Most of the present conventional methods are adequate for current requirements. The reasons why no method is to be recommended were multiple, ranging from economical aspects, through incompatibility of materials to national regulations

Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method

OpenAIRE

Chen, Jian; Yuan, Shenfang; Qiu, Lei; Cai, Jian; Yang, Weibo

2016-01-01

Prognostics and health management techniques have drawn widespread attention due to their ability to facilitate maintenance activities based on need. On-line prognosis of fatigue crack propagation can offer information for optimizing operation and maintenance strategies in real-time. This paper proposes a Lamb wave-particle filter (LW-PF)-based method for on-line prognosis of fatigue crack propagation which takes advantages of the possibility of on-line monitoring to evaluate the actual crack...

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

Design of digital trapezoidal shaping filter based on LabVIEW

International Nuclear Information System (INIS)

Liu Yujuan; Qin Guoxiu; Yang Zhihui; Zhang Xiaodong

2013-01-01

It describes the design of a digital trapezoidal shaping filter to nuclear signals based on LabVIEW. A method of optimizing the trapezoidal shaping filter's parameters was presented and tested, and the test results of the effect of shaping filter algorithm were studied. (authors)

Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

DEFF Research Database (Denmark)

Drews, Martin; Lauritzen, Bent; Madsen, Henrik

2005-01-01

A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model...... parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...

Optimization-based particle filter for state and parameter estimation

Institute of Scientific and Technical Information of China (English)

Li Fu; Qi Fei; Shi Guangming; Zhang Li

2009-01-01

In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

Synthesis of Cascadable DDCC-Based Universal Filter Using NAM

Directory of Open Access Journals (Sweden)

Huu-Duy Tran

2015-08-01

Full Text Available A novel systematic approach for synthesizing DDCC-based voltage-mode biquadratic universal filters is proposed. The DDCCs are described by infinity-variables’ models of nullor-mirror elements which can be used in the nodal admittance matrix expansion process. Applying the proposed method, the obtained 12 equivalent filters offer the following features: multi-input and two outputs, realization of all five standard filter functions, namely lowpass, bandpass, highpass, notch and allpass, high-input impedance, employing only grounded capacitors and resistors, orthogonal controllability between pole frequency and quality factor, and cascadable, low active and passive sensitivities. The workability of some synthesized filters is verified by HSPICE simulations to demonstrate the feasibility of the proposed method.

Optimum filter-based discrimination of neutrons and gamma rays

International Nuclear Information System (INIS)

Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek

2015-01-01

An optimum filter-based method for discrimination of neutrons and gamma-rays in a mixed radiation field is presented. The existing filter-based implementations of discriminators require sample pulse responses in advance of the experiment run to build the filter coefficients, which makes them less practical. Our novel technique creates the coefficients during the experiment and improves their quality gradually. Applied to several sets of mixed neutron and photon signals obtained through different digitizers using stilbene scintillator, this approach is analyzed and its discrimination quality is measured. (authors)

Comparative study of in-situ filter test methods

International Nuclear Information System (INIS)

Marshall, M.; Stevens, D.C.

1981-01-01

Available methods of testing high efficiency particulate aerosol (HEPA) filters in-situ have been reviewed. In order to understand the relationship between the results produced by different methods a selection has been compared. Various pieces of equipment for generating and detecting aerosols have been tested and their suitability assessed. Condensation-nuclei, DOP (di-octyl phthalate) and sodium-flame in-situ filter test methods have been studied, using the 500 cfm (9000 m 3 /h) filter test rig at Harwell and in the field. Both the sodium-flame and DOP methods measure the penetration through leaks and filter material. However the measured penetration through filtered leaks depends on the aerosol size distribution and the detection method. Condensation-nuclei test methods can only be used to measure unfiltered leaks since condensation nuclei have a very low penetration through filtered leaks. A combination of methods would enable filtered and unfiltered leaks to be measured. A condensation-nucleus counter using n-butyl alcohol as the working fluid has the advantage of being able to detect any particle up to 1 μm in diameter, including DOP, and so could be used for this purpose. A single-particle counter has not been satisfactory because of interference from particles leaking into systems under extract, particularly downstream of filters, and because the concentration of the input aerosol has to be severely limited. The sodium-flame method requires a skilled operator and may cause safety and corrosion problems. The DOP method using a total light scattering detector has so far been the most satisfactory. It is fairly easy to use, measures reasonably low values of penetration and gives rapid results. DOP has had no adverse effect on HEPA filters over a long series of tests

Instantaneous spectrum estimation of earthquake ground motions based on unscented Kalman filter method

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Representing earthquake ground motion as time varying ARMA model, the instantaneous spectrum can only be determined by the time varying coefficients of the corresponding ARMA model. In this paper, unscented Kalman filter is applied to estimate the time varying coefficients. The comparison between the estimation results of unscented Kalman filter and Kalman filter methods shows that unscented Kalman filter can more precisely represent the distribution of the spectral peaks in time-frequency plane than Kalman filter, and its time and frequency resolution is finer which ensures its better ability to track the local properties of earthquake ground motions and to identify the systems with nonlinearity or abruptness. Moreover, the estimation results of ARMA models with different orders indicate that the theoretical frequency resolving power ofARMA model which was usually ignored in former studies has great effect on the estimation precision of instantaneous spectrum and it should be taken as one of the key factors in order selection of ARMA model.

Learning based particle filtering object tracking for visible-light systems.

Science.gov (United States)

Sun, Wei

2015-10-01

We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation

Directory of Open Access Journals (Sweden)

Wuming Zhang

2016-06-01

Full Text Available Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs from airborne LiDAR (light detection and ranging data. However, most filtering algorithms need to carefully set up a number of complicated parameters to achieve high accuracy. In this paper, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. Within the proposed approach, a LiDAR point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface. Finally, the ground points can be extracted from the LiDAR point cloud by comparing the original LiDAR points and the generated surface. Benchmark datasets provided by ISPRS (International Society for Photogrammetry and Remote Sensing working Group III/3 are used to validate the proposed filtering method, and the experimental results yield an average total error of 4.58%, which is comparable with most of the state-of-the-art filtering algorithms. The proposed easy-to-use filtering method may help the users without much experience to use LiDAR data and related technology in their own applications more easily.

Fast multiview three-dimensional reconstruction method using cost volume filtering

Science.gov (United States)

Lee, Seung Joo; Park, Min Ki; Jang, In Yeop; Lee, Kwan H.

2014-03-01

As the number of customers who want to record three-dimensional (3-D) information using a mobile electronic device increases, it becomes more and more important to develop a method which quickly reconstructs a 3-D model from multiview images. A fast multiview-based 3-D reconstruction method is presented, which is suitable for the mobile environment by constructing a cost volume of the 3-D height field. This method consists of two steps: the construction of a reliable base surface and the recovery of shape details. In each step, the cost volume is constructed using photoconsistency and then it is filtered according to the multiscale. The multiscale-based cost volume filtering allows the 3-D reconstruction to maintain the overall shape and to preserve the shape details. We demonstrate the strength of the proposed method in terms of computation time, accuracy, and unconstrained acquisition environment.

Stability Analysis and Active Damping for LLCL-filter-Based Grid-Connected Inverters

DEFF Research Database (Denmark)

Huang, Min; Wang, Xiongfei; Loh, Poh Chiang

2015-01-01

to use either passive or active damping methods. This paper analyzes the stability of the LLCL-filter based grid-connected inverter and identifies a critical resonant frequency for the LLCL-filter when sampling and transport delays are considered. In a high resonant frequency region the active damping...... is not required but in a low resonant frequency region the active damping is necessary. The basic LLCL resonance damping properties of different feedback states based on a notch filter concept are also studied. Then an active damping method which is using the capacitor current feedback for LLCL......-filter is introduced. Based on this active damping method, a design procedure for the controller is given. Last, both simulation and experimental results are provided to validate the theoretical analysis of this paper....

Supervised Filter Learning for Representation Based Face Recognition.

Directory of Open Access Journals (Sweden)

Chao Bi

Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

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.

Photonic crystal ring resonator based optical filters for photonic integrated circuits

International Nuclear Information System (INIS)

Robinson, S.

2014-01-01

In this paper, a two Dimensional (2D) Photonic Crystal Ring Resonator (PCRR) based optical Filters namely Add Drop Filter, Bandpass Filter, and Bandstop Filter are designed for Photonic Integrated Circuits (PICs). The normalized output response of the filters is obtained using 2D Finite Difference Time Domain (FDTD) method and the band diagram of periodic and non-periodic structure is attained by Plane Wave Expansion (PWE) method. The size of the device is minimized from a scale of few tens of millimeters to the order of micrometers. The overall size of the filters is around 11.4 μm × 11.4 μm which is highly suitable of photonic integrated circuits

Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

Directory of Open Access Journals (Sweden)

Keranmu Xielifuguli

2014-01-01

Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

A User-Oriented Splog Filtering Based on a Machine Learning

Science.gov (United States)

Yoshinaka, Takayuki; Ishii, Soichi; Fukuhara, Tomohiro; Masuda, Hidetaka; Nakagawa, Hiroshi

A method for filtering spam blogs (splogs) based on a machine learning technique, and its evaluation results are described. Today, spam blogs (splogs) became one of major issues on the Web. The problem of splogs is that values of blog sites are different by people. We propose a novel user-oriented splog filtering method that can adapt each user's preference for valuable blogs. We use the SVM(Support Vector Machine) for creating a personalized splog filter for each user. We had two experiments: (1) an experiment of individual splog judgement, and (2) an experiment for user oriented splog filtering. From the former experiment, we found existence of 'gray' blogs that are needed to treat by persons. From the latter experiment, we found that we can provide appropriate personalized filters by choosing the best feature set for each user. An overview of proposed method, and evaluation results are described.

Guided Image Filtering-Based Pan-Sharpening Method: A Case Study of GaoFen-2 Imagery

Directory of Open Access Journals (Sweden)

Yalan Zheng

2017-12-01

Full Text Available GaoFen-2 (GF-2 is a civilian optical satellite self-developed by China equipped with both multispectral and panchromatic sensors, and is the first satellite in China with a resolution below 1 m. Because the pan-sharpening methods on GF-2 imagery have not been a focus of previous works, we propose a novel pan-sharpening method based on guided image filtering and compare the performance to state-of-the-art methods on GF-2 images. Guided image filtering was introduced to decompose and transfer the details and structures from the original panchromatic and multispectral bands. Thereafter, an adaptive model that considers the local spectral relationship was designed to properly inject spatial information back into the original spectral bands. Four pairs of GF-2 images acquired from urban, water body, cropland, and forest areas were selected for the experiments. Both quantitative and visual inspections were used for the assessment. The experimental results demonstrated that for GF-2 imagery acquired over different scenes, the proposed approach consistently achieves high spectral fidelity and enhances spatial details, thereby benefitting the potential classification procedures.

Supplementary test method for carbon filters

International Nuclear Information System (INIS)

Normann, B.; Pettersson, S.-O.

1980-11-01

A test method for carbon filters using freon to detect leakage is described. The filters are used in nuclear power plants and in air-raid shelters to separate radioactive iodine.Sampling and detection limits are described and a proposal for a complete equipment is made.(G.B.)

A rigid porous filter and filtration method

Energy Technology Data Exchange (ETDEWEB)

Chiang, Ta-Kuan; Straub, Douglas, Straub L.; Dennis, Richard A.

1998-12-01

The present invention involves a porous rigid filter comprising a plurality of concentric filtration elements having internal flow passages and forming external flow passages there between. The present invention also involves a pressure vessel containing the filter for the removal of particulate from high pressure particulate containing gases, and further involves a method for using the filter to remove such particulate. The present filter has the advantage of requiring fewer filter elements due to the high surface area- to-volume ratio provided by the filter, requires a reduced pressure vessel size, and exhibits enhanced mechanical design properties, improved cleaning properties, configuration options, modularity and ease of fabrication.

Combined adaptive multiple subtraction based on optimized event tracing and extended wiener filtering

Science.gov (United States)

Tan, Jun; Song, Peng; Li, Jinshan; Wang, Lei; Zhong, Mengxuan; Zhang, Xiaobo

2017-06-01

The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

Wiener discrete cosine transform-based image filtering

Science.gov (United States)

Pogrebnyak, Oleksiy; Lukin, Vladimir V.

2012-10-01

A classical problem of additive white (spatially uncorrelated) Gaussian noise suppression in grayscale images is considered. The main attention is paid to discrete cosine transform (DCT)-based denoising, in particular, to image processing in blocks of a limited size. The efficiency of DCT-based image filtering with hard thresholding is studied for different sizes of overlapped blocks. A multiscale approach that aggregates the outputs of DCT filters having different overlapped block sizes is proposed. Later, a two-stage denoising procedure that presumes the use of the multiscale DCT-based filtering with hard thresholding at the first stage and a multiscale Wiener DCT-based filtering at the second stage is proposed and tested. The efficiency of the proposed multiscale DCT-based filtering is compared to the state-of-the-art block-matching and three-dimensional filter. Next, the potentially reachable multiscale filtering efficiency in terms of output mean square error (MSE) is studied. The obtained results are of the same order as those obtained by Chatterjee's approach based on nonlocal patch processing. It is shown that the ideal Wiener DCT-based filter potential is usually higher when noise variance is high.

Cluster Based Vector Attribute Filtering

NARCIS (Netherlands)

Kiwanuka, Fred N.; Wilkinson, Michael H.F.

2016-01-01

Morphological attribute filters operate on images based on properties or attributes of connected components. Until recently, attribute filtering was based on a single global threshold on a scalar property to remove or retain objects. A single threshold struggles in case no single property or

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

Science.gov (United States)

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-08

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

Directory of Open Access Journals (Sweden)

Ke Li

2016-01-01

Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

Science.gov (United States)

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-01

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

Investigation on filter method for smoothing spiral phase plate

Science.gov (United States)

Zhang, Yuanhang; Wen, Shenglin; Luo, Zijian; Tang, Caixue; Yan, Hao; Yang, Chunlin; Liu, Mincai; Zhang, Qinghua; Wang, Jian

2018-03-01

Spiral phase plate (SPP) for generating vortex hollow beams has high efficiency in various applications. However, it is difficult to obtain an ideal spiral phase plate because of its continuous-varying helical phase and discontinued phase step. This paper describes the demonstration of continuous spiral phase plate using filter methods. The numerical simulations indicate that different filter method including spatial domain filter, frequency domain filter has unique impact on surface topography of SPP and optical vortex characteristics. The experimental results reveal that the spatial Gaussian filter method for smoothing SPP is suitable for Computer Controlled Optical Surfacing (CCOS) technique and obtains good optical properties.

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)

A Divergence Median-based Geometric Detector with A Weighted Averaging Filter

Science.gov (United States)

Hua, Xiaoqiang; Cheng, Yongqiang; Li, Yubo; Wang, Hongqiang; Qin, Yuliang

2018-01-01

To overcome the performance degradation of the classical fast Fourier transform (FFT)-based constant false alarm rate detector with the limited sample data, a divergence median-based geometric detector on the Riemannian manifold of Heimitian positive definite matrices is proposed in this paper. In particular, an autocorrelation matrix is used to model the correlation of sample data. This method of the modeling can avoid the poor Doppler resolution as well as the energy spread of the Doppler filter banks result from the FFT. Moreover, a weighted averaging filter, conceived from the philosophy of the bilateral filtering in image denoising, is proposed and combined within the geometric detection framework. As the weighted averaging filter acts as the clutter suppression, the performance of the geometric detector is improved. Numerical experiments are given to validate the effectiveness of our proposed 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.

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...

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.

Dual linear structured support vector machine tracking method via scale correlation filter

Science.gov (United States)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

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)

Gaussian particle filter based pose and motion estimation

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

Active RC filter based implementation analysis part of two channel hybrid filter bank

Directory of Open Access Journals (Sweden)

Stojanović Vidosav

2014-01-01

Full Text Available In the present paper, a new design method for continuous-time powersymmetric active RC filters for Hybrid Filter Bank (HFB is proposed. Some theoretical properties of continious-time power-symmetric filters bank in a more general perspective are studied. This includes the derivation of a new general analytical form, and a study of poles and zeros locations in s-plane. In the proposed design method the analytic solution of filter coefficients is solved in sdomain using only one nonlinear equation Finally, the proposed approximation is compared to standard approximations. It was shown that attenuation and group delay characteristic of the proposed filter lie between Butterworth and elliptic characteristics. [Projekat Ministarstva nauke Republike Srbije, br. 32009TR

Kalman Filter Based Tracking in an Video Surveillance System

Directory of Open Access Journals (Sweden)

SULIMAN, C.

2010-05-01

Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

Acoustic wave filter based on periodically poled lithium niobate.

Science.gov (United States)

Courjon, Emilie; Bassignot, Florent; Ulliac, Gwenn; Benchabane, Sarah; Ballandras, Sylvain

2012-09-01

Solutions for the development of compact RF passive transducers as an alternative to standard surface or bulk acoustic wave devices are receiving increasing interest. This article presents results on the development of an acoustic band-pass filter based on periodically poled ferroelectric domains in lithium niobate. The fabrication of periodically poled transducers (PPTs) operating in the range of 20 to 650 MHz has been achieved on 3-in (76.2-mm) 500-μm-thick wafers. This kind of transducer is able to excite elliptical as well as longitudinal modes, yielding phase velocities of about 3800 and 6500 ms(-1), respectively. A new type of acoustic band-pass filter is proposed, based on the use of PPTs instead of the SAWs excited by classical interdigital transducers. The design and the fabrication of such a filter are presented, as well as experimental measurements of its electrical response and transfer function. The feasibility of such a PPT-based filter is thereby demonstrated and the limitations of this method are discussed.

Robust and Adaptive Block Tracking Method Based on Particle Filter

Directory of Open Access Journals (Sweden)

Bin Sun

2015-10-01

Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

Description of an identification method of thermocouple time constant based on application of recursive numerical filtering to temperature fluctuation

International Nuclear Information System (INIS)

Bernardin, B.; Le Guillou, G.; Parcy, JP.

1981-04-01

Usual spectral methods, based on temperature fluctuation analysis, aiming at thermocouple time constant identification are using an equipment too much sophisticated for on-line application. It is shown that numerical filtering is optimal for this application, the equipment is simpler than for spectral methods and less samples of signals are needed for the same accuracy. The method is described and a parametric study was performed using a temperature noise simulator [fr

Method and apparatus for a self-cleaning filter

Science.gov (United States)

Diebold, James P.; Lilley, Arthur; Browne, III, Kingsbury; Walt, Robb Ray; Duncan, Dustin; Walker, Michael; Steele, John; Fields, Michael

2010-11-16

A method and apparatus for removing fine particulate matter from a fluid stream without interrupting the overall process or flow. The flowing fluid inflates and expands the flexible filter, and particulate is deposited on the filter media while clean fluid is permitted to pass through the filter. This filter is cleaned when the fluid flow is stopped, the filter collapses, and a force is applied to distort the flexible filter media to dislodge the built-up filter cake. The dislodged filter cake falls to a location that allows undisrupted flow of the fluid after flow is restored. The shed particulate is removed to a bin for periodic collection. A plurality of filter cells can operate independently or in concert, in parallel, or in series to permit cleaning the filters without shutting off the overall fluid flow. The self-cleaning filter is low cost, has low power consumption, and exhibits low differential pressures.

Method and apparatus for a self-cleaning filter

Science.gov (United States)

Diebold, James P.; Lilley, Arthur; Browne, III, Kingsbury; Walt, Robb Ray; Duncan, Dustin; Walker, Michael; Steele, John; Fields, Michael

2013-09-10

A method and apparatus for removing fine particulate matter from a fluid stream without interrupting the overall process or flow. The flowing fluid inflates and expands the flexible filter, and particulate is deposited on the filter media while clean fluid is permitted to pass through the filter. This filter is cleaned when the fluid flow is stopped, the filter collapses, and a force is applied to distort the flexible filter media to dislodge the built-up filter cake. The dislodged filter cake falls to a location that allows undisrupted flow of the fluid after flow is restored. The shed particulate is removed to a bin for periodic collection. A plurality of filter cells can operate independently or in concert, in parallel, or in series to permit cleaning the filters without shutting off the overall fluid flow. The self-cleaning filter is low cost, has low power consumption, and exhibits low differential pressures.

Extended Kalman filter-based methods for pose estimation using visual, inertial and magnetic sensors: comparative analysis and performance evaluation.

Science.gov (United States)

Ligorio, Gabriele; Sabatini, Angelo Maria

2013-02-04

In this paper measurements from a monocular vision system are fused with inertial/magnetic measurements from an Inertial Measurement Unit (IMU) rigidly connected to the camera. Two Extended Kalman filters (EKFs) were developed to estimate the pose of the IMU/camera sensor moving relative to a rigid scene (ego-motion), based on a set of fiducials. The two filters were identical as for the state equation and the measurement equations of the inertial/magnetic sensors. The DLT-based EKF exploited visual estimates of the ego-motion using a variant of the Direct Linear Transformation (DLT) method; the error-driven EKF exploited pseudo-measurements based on the projection errors from measured two-dimensional point features to the corresponding three-dimensional fiducials. The two filters were off-line analyzed in different experimental conditions and compared to a purely IMU-based EKF used for estimating the orientation of the IMU/camera sensor. The DLT-based EKF was more accurate than the error-driven EKF, less robust against loss of visual features, and equivalent in terms of computational complexity. Orientation root mean square errors (RMSEs) of 1° (1.5°), and position RMSEs of 3.5 mm (10 mm) were achieved in our experiments by the DLT-based EKF (error-driven EKF); by contrast, orientation RMSEs of 1.6° were achieved by the purely IMU-based EKF.

Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

Institute of Scientific and Technical Information of China (English)

LI Shuo; TAO Ran

2006-01-01

We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

Stability analysis and active damping for LLCL-filter based grid-connected inverters

DEFF Research Database (Denmark)

Huang, Min; Blaabjerg, Frede; Loh, Poh Chiang

2014-01-01

A higher order passive power filter (LLCL-filter) for the grid-tied inverter is becoming attractive for the industrial applications due to the possibility to reduce the cost of the copper and the magnetic material. To avoid the well-known stability problems of the LLCL-filter it is requested to use...... either passive or active damping methods. This paper analyzes the stability when damping is required and when damping is not necessary considering sampling and transport delay. Basic LLCL resonance damping properties of different feedback states are also studied. Then an active damping method which...... is using the capacitor current feedback for LLCL-filter is introduced. Based on this method, a design procedure for the control method is given. Last, both simulation and experimental results are provided to validate the theoretical analysis of this paper....

An approach for fixed coefficient RNS-based FIR filter

Science.gov (United States)

Srinivasa Reddy, Kotha; Sahoo, Subhendu Kumar

2017-08-01

In this work, an efficient new modular multiplication method for {2k-1, 2k, 2k+1-1} moduli set is proposed to implement a residue number system (RNS)-based fixed coefficient finite impulse response filter. The new multiplication approach reduces the number of partial products by using pre-loaded product block. The reduction in partial products with the proposed modular multiplication improves the clock frequency and reduces the area and power as compared with the conventional modular multiplication. Further, the present approach eliminates a binary number to residue number converter circuit, which is usually needed at the front end of RNS-based system. In this work, two fixed coefficient filter architectures with the new modular multiplication approach are proposed. The filters are implemented using Verilog hardware description language. The United Microelectronics Corporation 90 nm technology library has been used for synthesis and the results area, power and delay are obtained with the help of Cadence register transfer level compiler. The power delay product (PDP) is also considered for performance comparison among the proposed filters. One of the proposed architecture is found to improve PDP gain by 60.83% as compared with the filter implemented with conventional modular multiplier. The filters functionality is validated with the help of Altera DSP Builder.

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

Science.gov (United States)

Wan, Renzhi; Zu, Yunxiao; Shao, Lin

2018-04-01

The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.

Novel method to improve power handling capability for coplanar waveguide high-temperature superconducting filter

Energy Technology Data Exchange (ETDEWEB)

Satoh, K; Koizumi, D; Narahashi, S [NTT DoCoMo, Inc., 3-5 Hikari-no-oka, 239-8536 Yokosuka (Japan)

2006-06-01

This paper proposes a novel method to improve the power handling capability of a coplanar waveguide (CPW) high-temperature superconducting (HTS) filter. The noteworthy point of the proposed method is that it is based on the concept that the power handling capability is improved by reducing the maximum current density of the filter. Numerical investigations confirm that a CPW HTS filter using 66-{omega} characteristic impedance resonators (66-{omega} CPW HTSF) reduces the maximum current density compared to that using conventional 50-{omega} resonators (50-{omega} CPW HTSF). We fabricated 5-GHz band four-pole Chevyshev CPW HTSFs based on the proposed and conventional methods. The fabricated 66-{omega} CPW HTSF exhibited the third-order intercept point (TOI) of + 61 dBm while the 50-{omega} CPW HTSF exhibited the TOI of + 54 dBm, both at 60 K. These results indicate the effectiveness of the proposed method.

Method for filtering radon from a gas system

International Nuclear Information System (INIS)

Sowinski, R.F.

1992-01-01

This patent describes a method of filtering, adjacent to an end user-customer's residence, or business in which at least a single gas appliance is located, a natural gas stream in which benz-a-anthracene has been concentrated at sufficient levels to be a health threat in a natural gas gathering and distributing network. It comprises introducing the natural gas stream to a filter selected from a group that includes impingement, passing the filtered natural gas stream to the customer's gas appliance wherein safe use of the energy associated with the stream occurs, periodically and safely removing the filter for disposing of captured benz-a-anthracene, inserting a new filter in place of the removed filter of step

Q-Method Extended Kalman Filter

Science.gov (United States)

Zanetti, Renato; Ainscough, Thomas; Christian, John; Spanos, Pol D.

2012-01-01

A new algorithm is proposed that smoothly integrates non-linear estimation of the attitude quaternion using Davenport s q-method and estimation of non-attitude states through an extended Kalman filter. The new method is compared to a similar existing algorithm showing its similarities and differences. The validity of the proposed approach is confirmed through numerical simulations.

Energy Based Clutter Filtering for Vector Flow Imaging

DEFF Research Database (Denmark)

Villagómez Hoyos, Carlos Armando; Jensen, Jonas; Ewertsen, Caroline

2017-01-01

for obtaining vector flow measurements, since the spectra overlaps at high beam-to-flow angles. In this work a distinct approach is proposed, where the energy of the velocity spectrum is used to differentiate among the two signals. The energy based method is applied by limiting the amplitude of the velocity...... spectrum function to a predetermined threshold. The effect of the clutter filtering is evaluated on a plane wave (PW) scan sequence in combination with transverse oscillation (TO) and directional beamforming (DB) for velocity estimation. The performance of the filter is assessed by comparison...

Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

KAUST Repository

Liu, Bo

2015-11-11

We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

An Automatic Parameter Identification Method for a PMSM Drive with LC-Filter

DEFF Research Database (Denmark)

Bech, Michael Møller; Christensen, Jeppe Haals; Weber, Magnus L.

2016-01-01

of the PMSM fed through an LC-filter. Based on the measured current response, model parameters for both the filter (L, R, C) and the PMSM (L and R) are estimated: First, the frequency response of the system is estimated using Welch Modified Periodogram method and then an optimization algorithm is used to find...... the parameters in an analytical reference model that minimize the model error. To demonstrate the practical feasibility of the method, a fully functional drive including an embedded real-time controller has been built. In addition to modulation, data acquisition and control the whole parameter identification...... method is also implemented on the real-time controller. Based on laboratory experiments on a 22 kW drive, it is concluded that the embedded identification method can estimate the five parameters in less than ten seconds....

A nowcasting technique based on application of the particle filter blending algorithm

Science.gov (United States)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

Science.gov (United States)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

Detail Enhancement for Infrared Images Based on Propagated Image Filter

Directory of Open Access Journals (Sweden)

Yishu Peng

2016-01-01

Full Text Available For displaying high-dynamic-range images acquired by thermal camera systems, 14-bit raw infrared data should map into 8-bit gray values. This paper presents a new method for detail enhancement of infrared images to display the image with a relatively satisfied contrast and brightness, rich detail information, and no artifacts caused by the image processing. We first adopt a propagated image filter to smooth the input image and separate the image into the base layer and the detail layer. Then, we refine the base layer by using modified histogram projection for compressing. Meanwhile, the adaptive weights derived from the layer decomposition processing are used as the strict gain control for the detail layer. The final display result is obtained by recombining the two modified layers. Experimental results on both cooled and uncooled infrared data verify that the proposed method outperforms the method based on log-power histogram modification and bilateral filter-based detail enhancement in both detail enhancement and visual effect.

Thickness filters for gradient based multi-material and thickness optimization of laminated composite structures

DEFF Research Database (Denmark)

Sørensen, Rene; Lund, Erik

2015-01-01

This paper presents a new gradient based method for performing discrete material and thickness optimization of laminated composite structures. The novelty in the new method lies in the application of so-called casting constraints, or thickness filters in this context, to control the thickness...... variation throughout the laminate. The filters replace the layerwise density variables with a single continuous through-the-thickness design variable. Consequently, the filters eliminate the need for having explicit constraints for preventing intermediate void through the thickness of the laminate....... Therefore, the filters reduce both the number of constraints and design variables in the optimization problem. Based upon a continuous approximation of a unit step function, the thickness filters are capable of projecting discrete 0/1 values to the underlying layerwise or ”physical” density variables which...

An approach of point cloud denoising based on improved bilateral filtering

Science.gov (United States)

Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin

2018-04-01

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

A pulse-shape discrimination method for improving Gamma-ray spectrometry based on a new digital shaping filter

Science.gov (United States)

Qin, Zhang-jian; Chen, Chuan; Luo, Jun-song; Xie, Xing-hong; Ge, Liang-quan; Wu, Qi-fan

2018-04-01

It is a usual practice for improving spectrum quality by the mean of designing a good shaping filter to improve signal-noise ratio in development of nuclear spectroscopy. Another method is proposed in the paper based on discriminating pulse-shape and discarding the bad pulse whose shape is distorted as a result of abnormal noise, unusual ballistic deficit or bad pulse pile-up. An Exponentially Decaying Pulse (EDP) generated in nuclear particle detectors can be transformed into a Mexican Hat Wavelet Pulse (MHWP) and the derivation process of the transform is given. After the transform is performed, the baseline drift is removed in the new MHWP. Moreover, the MHWP-shape can be discriminated with the three parameters: the time difference between the two minima of the MHWP, and the two ratios which are from the amplitude of the two minima respectively divided by the amplitude of the maximum in the MHWP. A new type of nuclear spectroscopy was implemented based on the new digital shaping filter and the Gamma-ray spectra were acquired with a variety of pulse-shape discrimination levels. It had manifested that the energy resolution and the peak-Compton ratio were both improved after the pulse-shape discrimination method was used.

Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.

Science.gov (United States)

Jia, Bin; Wang, Xiaodong

2013-12-17

: The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF3), and the fifth-degree cubature Kalman filter (CKF5) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.

An image-space parallel convolution filtering algorithm based on shadow map

Science.gov (United States)

Li, Hua; Yang, Huamin; Zhao, Jianping

2017-07-01

Shadow mapping is commonly used in real-time rendering. In this paper, we presented an accurate and efficient method of soft shadows generation from planar area lights. First this method generated a depth map from light's view, and analyzed the depth-discontinuities areas as well as shadow boundaries. Then these areas were described as binary values in the texture map called binary light-visibility map, and a parallel convolution filtering algorithm based on GPU was enforced to smooth out the boundaries with a box filter. Experiments show that our algorithm is an effective shadow map based method that produces perceptually accurate soft shadows in real time with more details of shadow boundaries compared with the previous works.

An algebraic method for constructing stable and consistent autoregressive filters

International Nuclear Information System (INIS)

Harlim, John; Hong, Hoon; Robbins, Jacob L.

2015-01-01

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides a discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern

Design and Implementation of Data Acquisition System Based on Digital Filtering Method for the Electrical Capacitance Tomography

Directory of Open Access Journals (Sweden)

LI Yang

2017-02-01

Full Text Available Aiming at the problem of high frequency noise interference in the ECT data acquisition system，on the basis of analysis of the ECT system data acquisition and control principles，we designed an improved distributed algorithm FIR low-pass digital filter combined with FPGA technology and digital filtering principle. The sampling frequency of the filter is 1 .5 MHz，the pass band cutoff frequency is 20MHz，and the design method is window function. We used the FDATooI toolbox in Matlab to extract and quantify the filter coefficients and the Quarters to simulate the simulation. Experimental results showed that the FIR digital filter can achieve the filtering function of the high frequency signal in the data acquisition system. Compared with the traditional DA algorithm，it has the advantages of small resource consumption and high acquisition speed and some other characteristics.

An Observer-Based Controller with a LMI-Based Filter against Wind-Induced Motion for High-Rise Buildings

Directory of Open Access Journals (Sweden)

Chao-Jun Chen

2017-01-01

Full Text Available Active mass damper (AMD control system is proposed for high-rise buildings to resist a strong wind. However, negative influence of noise in sensors impedes the application of AMD systems in practice. To reduce the adverse influence of noise on AMD systems, a Kalman filter and a linear matrix inequality- (LMI- based filter are designed. Firstly, a ten-year return period fluctuating wind load is simulated by mixed autoregressive-moving average (MARMA method, and its reliability is tested by wind speed power spectrum and correlation analysis. Secondly, a designed state observer with different filters uses wind-induced acceleration responses of a high-rise building as the feedback signal that includes noise to calculate control force in this paper. Finally, these methods are applied to a numerical example of a high-rise building and an experiment of a single span four-storey steel frame. Both numerical and experimental results are presented to verify that both Kalman filter and LMI-based filter can effectively suppress noise, but only the latter can guarantee the stability of AMD parameters.

FPGA Implementation of the Coupled Filtering Method and the Affine Warping Method.

Science.gov (United States)

Zhang, Chen; Liang, Tianzhu; Mok, Philip K T; Yu, Weichuan

2017-07-01

In ultrasound image analysis, the speckle tracking methods are widely applied to study the elasticity of body tissue. However, "feature-motion decorrelation" still remains as a challenge for the speckle tracking methods. Recently, a coupled filtering method and an affine warping method were proposed to accurately estimate strain values, when the tissue deformation is large. The major drawback of these methods is the high computational complexity. Even the graphics processing unit (GPU)-based program requires a long time to finish the analysis. In this paper, we propose field-programmable gate array (FPGA)-based implementations of both methods for further acceleration. The capability of FPGAs on handling different image processing components in these methods is discussed. A fast and memory-saving image warping approach is proposed. The algorithms are reformulated to build a highly efficient pipeline on FPGA. The final implementations on a Xilinx Virtex-7 FPGA are at least 13 times faster than the GPU implementation on the NVIDIA graphic card (GeForce GTX 580).

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.

Tunable M-channel filter based on Thue-Morse heterostructures containing meta materials

Directory of Open Access Journals (Sweden)

H Pashaei Adl

2015-01-01

Full Text Available In this paper the tunable M-channel filters based on Thue-Morse heterostructures consisting of single -negative materials has been studied. The results showed that the number of resonance modes inside the zero- gap increases as the number of heterogenous interface, M, increases. The number of resonance modes inside the zero- gap is equal to that of heterogenous interface M, and it can be used as M channels filter. This result provides a feasible method to adjust the channel number of multiple-channel filters. When losses are involved, the results showed that the electric fields of the resonance modes decay largely with the increase of the number of heterogenous interface and damping factors. Besides, the relationship between the quality factor of multiple-channel filters and the number of heterogenous interface M is linear, and the quality factor of multiple-channel filters decreases with the increase of the damping factor. These results provide feasible methods to adjust the quality factor of multiple-channel filters

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

Science.gov (United States)

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Lessons learned in preparing method 29 filters for compliance testing audits.

Science.gov (United States)

Martz, R F; McCartney, J E; Bursey, J T; Riley, C E

2000-01-01

Companies conducting compliance testing are required to analyze audit samples at the time they collect and analyze the stack samples if audit samples are available. Eastern Research Group (ERG) provides technical support to the EPA's Emission Measurements Center's Stationary Source Audit Program (SSAP) for developing, preparing, and distributing performance evaluation samples and audit materials. These audit samples are requested via the regulatory Agency and include spiked audit materials for EPA Method 29-Metals Emissions from Stationary Sources, as well as other methods. To provide appropriate audit materials to federal, state, tribal, and local governments, as well as agencies performing environmental activities and conducting emission compliance tests, ERG has recently performed testing of blank filter materials and preparation of spiked filters for EPA Method 29. For sampling stationary sources using an EPA Method 29 sampling train, the use of filters without organic binders containing less than 1.3 microg/in.2 of each of the metals to be measured is required. Risk Assessment testing imposes even stricter requirements for clean filter background levels. Three vendor sources of quartz fiber filters were evaluated for background contamination to ensure that audit samples would be prepared using filters with the lowest metal background levels. A procedure was developed to test new filters, and a cleaning procedure was evaluated to see if a greater level of cleanliness could be achieved using an acid rinse with new filters. Background levels for filters supplied by different vendors and within lots of filters from the same vendor showed a wide variation, confirmed through contact with several analytical laboratories that frequently perform EPA Method 29 analyses. It has been necessary to repeat more than one compliance test because of suspect metals background contamination levels. An acid cleaning step produced improvement in contamination level, but the

A Kalman Filter for SINS Self-Alignment Based on Vector Observation.

Science.gov (United States)

Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Tong, Jinwu

2017-01-29

In this paper, a self-alignment method for strapdown inertial navigation systems based on the q -method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate.

Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

Science.gov (United States)

Jena, D. P.; Panigrahi, S. N.

2016-03-01

Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

The optimal digital filters of sine and cosine transforms for geophysical transient electromagnetic method

Science.gov (United States)

Zhao, Yun-wei; Zhu, Zi-qiang; Lu, Guang-yin; Han, Bo

2018-03-01

The sine and cosine transforms implemented with digital filters have been used in the Transient electromagnetic methods for a few decades. Kong (2007) proposed a method of obtaining filter coefficients, which are computed in the sample domain by Hankel transform pair. However, the curve shape of Hankel transform pair changes with a parameter, which usually is set to be 1 or 3 in the process of obtaining the digital filter coefficients of sine and cosine transforms. First, this study investigates the influence of the parameter on the digital filter algorithm of sine and cosine transforms based on the digital filter algorithm of Hankel transform and the relationship between the sine, cosine function and the ±1/2 order Bessel function of the first kind. The results show that the selection of the parameter highly influences the precision of digital filter algorithm. Second, upon the optimal selection of the parameter, it is found that an optimal sampling interval s also exists to achieve the best precision of digital filter algorithm. Finally, this study proposes four groups of sine and cosine transform digital filter coefficients with different length, which may help to develop the digital filter algorithm of sine and cosine transforms, and promote its application.

Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

Institute of Scientific and Technical Information of China (English)

Zhaoxia PU; Joshua HACKER

2009-01-01

This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

Studies on Hepa filter test methods

International Nuclear Information System (INIS)

Lee, S.H.; Jon, K.S.; Park, W.J.; Ryoo, R.

1981-01-01

The purpose of this study is to compare testing methods of the HEPA filter adopted in other countries with each other, and to design and construct a test duct system to establish testing methods. The American D.O.P. test method, the British NaCl test method and several other independently developed methods are compared. It is considered that the D.O.P. method is most suitable for in-plant and leak tests

[Restoration filtering based on projection power spectrum for single-photon emission computed tomography].

Science.gov (United States)

Kubo, N

1995-04-01

To improve the quality of single-photon emission computed tomographic (SPECT) images, a restoration filter has been developed. This filter was designed according to practical "least squares filter" theory. It is necessary to know the object power spectrum and the noise power spectrum. The power spectrum is estimated from the power spectrum of a projection, when the high-frequency power spectrum of a projection is adequately approximated as a polynomial exponential expression. A study of the restoration with the filter based on a projection power spectrum was conducted, and compared with that of the "Butterworth" filtering method (cut-off frequency of 0.15 cycles/pixel), and "Wiener" filtering (signal-to-noise power spectrum ratio was a constant). Normalized mean-squared errors (NMSE) of the phantom, two line sources located in a 99mTc filled cylinder, were used. NMSE of the "Butterworth" filter, "Wiener" filter, and filtering based on a power spectrum were 0.77, 0.83, and 0.76 respectively. Clinically, brain SPECT images utilizing this new restoration filter improved the contrast. Thus, this filter may be useful in diagnosis of SPECT images.

Restoration filtering based on projection power spectrum for single-photon emission computed tomography

International Nuclear Information System (INIS)

Kubo, Naoki

1995-01-01

To improve the quality of single-photon emission computed tomographic (SPECT) images, a restoration filter has been developed. This filter was designed according to practical 'least squares filter' theory. It is necessary to know the object power spectrum and the noise power spectrum. The power spectrum is estimated from the power spectrum of a projection, when the high-frequency power spectrum of a projection is adequately approximated as a polynomial exponential expression. A study of the restoration with the filter based on a projection power spectrum was conducted, and compared with that of the 'Butterworth' filtering method (cut-off frequency of 0.15 cycles/pixel), and 'Wiener' filtering (signal-to-noise power spectrum ratio was a constant). Normalized mean-squared errors (NMSE) of the phantom, two line sources located in a 99m Tc filled cylinder, were used. NMSE of the 'Butterworth' filter, 'Wiener' filter, and filtering based on a power spectrum were 0.77, 0.83, and 0.76 respectively. Clinically, brain SPECT images utilizing this new restoration filter improved the contrast. Thus, this filter may be useful in diagnosis of SPECT images. (author)

Robustness analysis of active damping methods for an inverter connected to the grid with an LCL-filter

DEFF Research Database (Denmark)

Ricchiuto, D.; Liserre, M.; Kerekes, Tamas

2011-01-01

Grid-connected converters usually employ an LCL-filter to reduce PWM harmonics. To avoid the wellknown stability problems it is requested to use either passive or active damping methods. Active damping methods avoid losses and preserve the filter effectiveness but they are more sensitive...... to parameters variation. In this paper the robustness of active damping methods is investigated considering those using only the same state variable (grid-side or converter-side current) normally used for current control (filter-based) or those methods using more state-variables (multiloop). Simulation...

Comparative study on γ-ray spectrum by several filtering method

International Nuclear Information System (INIS)

Yuan Xinyu; Liu Liangjun; Zhou Jianliang

2011-01-01

Comparative study was conducted on results of gamma-ray spectrum by using a majority of active smoothing method, which were used to show filtering effect. The results showed that peak was widened and overlap peaks increased with energy domain filter in γ-ray spectrum. Filter and its parameters should be seriously taken into consideration in frequency domain. Wavelet transformation can keep signal in high frequency region well. Improved threshold method showed the advantages of hard and soft threshold method at the same time by comparison, which was suitable for weak peaks detection. A new filter was put forward to eke out gravity model approach, whose denoise level was detected by standard deviation. This method not only kept signal and net area of peak well,but also attained better result and had simple computer program. (authors)

Methods of filtering the graph images of the functions

Directory of Open Access Journals (Sweden)

Олександр Григорович Бурса

2017-06-01

Full Text Available The theoretical aspects of cleaning raster images of scanned graphs of functions from digital, chromatic and luminance distortions by using computer graphics techniques have been considered. The basic types of distortions characteristic of graph images of functions have been stated. To suppress the distortion several methods, providing for high-quality of the resulting images and saving their topological features, were suggested. The paper describes the techniques developed and improved by the authors: the method of cleaning the image of distortions by means of iterative contrasting, based on the step-by-step increase in image contrast in the graph by 1%; the method of small entities distortion restoring, based on the thinning of the known matrix of contrast increase filter (the allowable dimensions of the nucleus dilution radius convolution matrix, which provide for the retention of the graph lines have been established; integration technique of the noise reduction method by means of contrasting and distortion restoring method of small entities with known σ-filter. Each method in the complex has been theoretically substantiated. The developed methods involve treatment of graph images as the entire image (global processing and its fragments (local processing. The metrics assessing the quality of the resulting image with the global and local processing have been chosen, the substantiation of the choice as well as the formulas have been given. The proposed complex methods of cleaning the graphs images of functions from grayscale image distortions is adaptive to the form of an image carrier, the distortion level in the image and its distribution. The presented results of testing the developed complex of methods for a representative sample of images confirm its effectiveness

Multiple attenuation to reflection seismic data using Radon filter and Wave Equation Multiple Rejection (WEMR) method

Energy Technology Data Exchange (ETDEWEB)

Erlangga, Mokhammad Puput [Geophysical Engineering, Institut Teknologi Bandung, Ganesha Street no.10 Basic Science B Buliding fl.2-3 Bandung, 40132, West Java Indonesia puput.erlangga@gmail.com (Indonesia)

2015-04-16

Separation between signal and noise, incoherent or coherent, is important in seismic data processing. Although we have processed the seismic data, the coherent noise is still mixing with the primary signal. Multiple reflections are a kind of coherent noise. In this research, we processed seismic data to attenuate multiple reflections in the both synthetic and real seismic data of Mentawai. There are several methods to attenuate multiple reflection, one of them is Radon filter method that discriminates between primary reflection and multiple reflection in the τ-p domain based on move out difference between primary reflection and multiple reflection. However, in case where the move out difference is too small, the Radon filter method is not enough to attenuate the multiple reflections. The Radon filter also produces the artifacts on the gathers data. Except the Radon filter method, we also use the Wave Equation Multiple Elimination (WEMR) method to attenuate the long period multiple reflection. The WEMR method can attenuate the long period multiple reflection based on wave equation inversion. Refer to the inversion of wave equation and the magnitude of the seismic wave amplitude that observed on the free surface, we get the water bottom reflectivity which is used to eliminate the multiple reflections. The WEMR method does not depend on the move out difference to attenuate the long period multiple reflection. Therefore, the WEMR method can be applied to the seismic data which has small move out difference as the Mentawai seismic data. The small move out difference on the Mentawai seismic data is caused by the restrictiveness of far offset, which is only 705 meter. We compared the real free multiple stacking data after processing with Radon filter and WEMR process. The conclusion is the WEMR method can more attenuate the long period multiple reflection than the Radon filter method on the real (Mentawai) seismic data.

Kernel-based noise filtering of neutron detector signals

International Nuclear Information System (INIS)

Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

2007-01-01

This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

Control Strategy of Active Power Filter Based on Modular Multilevel Converter

Science.gov (United States)

Xie, Xifeng

2018-03-01

To improve the capacity, pressure resistance and the equivalent switching frequency of active power filter (APF), a control strategy of APF based on Modular Multilevel Converter (MMC) is presented. In this Control Strategy, the indirect current control method is used to achieve active current and reactive current decoupling control; Voltage Balance Control Strategy is to stabilize sub-module capacitor voltage, the predictive current control method is used to Track and control of harmonic currents. As a result, the harmonic current is restrained, and power quality is improved. Finally, the simulation model of active power filter controller based on MMC is established in Matlab/Simulink, the simulation proves that the proposed strategy is feasible and correct.

Perception-Based Filtering for MMOGs

Directory of Open Access Journals (Sweden)

Souad El Merhebi

2008-01-01

Full Text Available Online games have exploded in the last few years. These games face several problems linked to scalability and interactivity. In fact, online games should provide a quick feedback of users' interactions as well as a coherent view of the shared world. However, the search for enhanced scalability dramatically increases message exchange. Such an increase consumes processing power and bandwidth, and thus limits interactivity, consistency, and scalability. To reduce the rate of message exchange, distributed virtual environment systems use filtering techniques such as interest management that filters messages according to users' interests in the world. These interests are influenced by perceptual facts which we study in this paper in order to build upon them a perception-based filtering technique. This technique satisfies users' needs by precisely providing an exact filtering which is more efficient than other techniques.

Phase Coordinate System and p-q Theory Based Methods in Active Filtering Implementation

Directory of Open Access Journals (Sweden)

POPESCU, M.

2013-02-01

Full Text Available This paper is oriented towards implementation of the main theories of powers in the compensating current generation stage of a three-phase three-wire shunt active power system. The system control is achieved through a dSPACE 1103 platform which is programmed under the Matlab/Simulink environment. Four calculation blocks included in a specifically designed Simulink library are successively implemented in the experimental setup. The first two approaches, namely those based on the Fryze-Buchholz-Depenbrock theory and the generalized instantaneous reactive power theory, make use of phase quantities without any transformation of the coordinate system and provide the basis for calculating the compensating current when total compensation is desired. The others are based on the p-q theory concepts and require the direct and reverse transformation to/from the two-phases stationary reference frame. They are used for total compensation and partial compensation of the current harmonic distortion. The experimental results, in terms of active filtering performances, validate the control strategies implementation and provide arguments in choosing the most appropriate method.

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.

Reactor - and accelerator-based filtered beams

International Nuclear Information System (INIS)

Mill, A.J.; Harvey, J.R.

1980-01-01

The neutrons produced in high flux nuclear reactors and in accelerator, induced fission and spallation reactions, represent the most intense sources of neutrons available for research. However, the neutrons from these sources are not monoenergetic, covering the broad range extending from 10 -3 eV up to 10 7 eV or so. In order to make quantitative measurements of the effects of neutrons and their dependence on neutron energy it is desirable to have mono-energetic neutron sources. The paper describes briefly methods of obtaining mono-energetic neutrons and different methods of filtration. This is followed by more detailed discussion of neutron window filters and a summary of the filtered beam facilities using this technique. The review concludes with a discussion of the main applications of filtered beams and their present and future importance

Image defog algorithm based on open close filter and gradient domain recursive bilateral filter

Science.gov (United States)

Liu, Daqian; Liu, Wanjun; Zhao, Qingguo; Fei, Bowen

2017-11-01

To solve the problems of fuzzy details, color distortion, low brightness of the image obtained by the dark channel prior defog algorithm, an image defog algorithm based on open close filter and gradient domain recursive bilateral filter, referred to as OCRBF, was put forward. The algorithm named OCRBF firstly makes use of weighted quad tree to obtain more accurate the global atmospheric value, then exploits multiple-structure element morphological open and close filter towards the minimum channel map to obtain a rough scattering map by dark channel prior, makes use of variogram to correct the transmittance map,and uses gradient domain recursive bilateral filter for the smooth operation, finally gets recovery images by image degradation model, and makes contrast adjustment to get bright, clear and no fog image. A large number of experimental results show that the proposed defog method in this paper can be good to remove the fog , recover color and definition of the fog image containing close range image, image perspective, the image including the bright areas very well, compared with other image defog algorithms,obtain more clear and natural fog free images with details of higher visibility, what's more, the relationship between the time complexity of SIDA algorithm and the number of image pixels is a linear correlation.

Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images

Science.gov (United States)

Zhu, Yuhong; Li, Hongyang; Jiang, Huageng

2017-12-01

This paper presents an efficient filter method based on fuzzy logics for adaptively removing additive and impulsive noise from color images. The proposed filter comprises two parts including noise detection and noise removal filtering. In the detection part, the fuzzy peer group concept is applied to determine what type of noise is added to each pixel of the corrupted image. In the filter part, the impulse noise is deducted by the vector median filter in the CIELAB color space and an optimal fuzzy filter is introduced to reduce the Gaussian noise, while they can work together to remove the mixed Gaussian-impulse noise from color images. Experimental results on several color images proves the efficacy of the proposed fuzzy filter.

Detail-enhanced multimodality medical image fusion based on gradient minimization smoothing filter and shearing filter.

Science.gov (United States)

Liu, Xingbin; Mei, Wenbo; Du, Huiqian

2018-02-13

In this paper, a detail-enhanced multimodality medical image fusion algorithm is proposed by using proposed multi-scale joint decomposition framework (MJDF) and shearing filter (SF). The MJDF constructed with gradient minimization smoothing filter (GMSF) and Gaussian low-pass filter (GLF) is used to decompose source images into low-pass layers, edge layers, and detail layers at multiple scales. In order to highlight the detail information in the fused image, the edge layer and the detail layer in each scale are weighted combined into a detail-enhanced layer. As directional filter is effective in capturing salient information, so SF is applied to the detail-enhanced layer to extract geometrical features and obtain directional coefficients. Visual saliency map-based fusion rule is designed for fusing low-pass layers, and the sum of standard deviation is used as activity level measurement for directional coefficients fusion. The final fusion result is obtained by synthesizing the fused low-pass layers and directional coefficients. Experimental results show that the proposed method with shift-invariance, directional selectivity, and detail-enhanced property is efficient in preserving and enhancing detail information of multimodality medical images. Graphical abstract The detailed implementation of the proposed medical image fusion algorithm.

Accelerometer North Finding System Based on the Wavelet Packet De-noising Algorithm and Filtering Circuit

Directory of Open Access Journals (Sweden)

LU Yongle

2014-07-01

Full Text Available This paper demonstrates a method and system for north finding with a low-cost piezoelectricity accelerometer based on the Coriolis acceleration principle. The proposed setup is based on the choice of an accelerometer with residual noise of 35 ng•Hz-1/2. The plane of the north finding system is aligned parallel to the local level, which helps to eliminate the effect of plane error. The Coriolis acceleration caused by the earth’s rotation and the acceleration’s instantaneous velocity is much weaker than the g-sensitivity acceleration. To get a high accuracy and a shorter time for north finding system, in this paper, the Filtering Circuit and the wavelet packet de-nosing algorithm are used as the following. First, the hardware is designed as the alternating currents across by filtering circuit, so the DC will be isolated and the weak AC signal will be amplified. The DC is interfering signal generated by the earth's gravity. Then, we have used a wavelet packet to filter the signal which has been done through the filtering circuit. Finally, compare the north finding results measured by wavelet packet filtering with those measured by a low-pass filter. Wavelet filter de-noise data shows that wavelet packet filtering and wavelet filter measurement have high accuracy. Wavelet Packet filtering has stronger ability to remove burst noise and higher engineering environment adaptability than that of Wavelet filtering. Experimental results prove the effectiveness and project implementation of the accelerometer north finding method based on wavelet packet de-noising algorithm.

Finite difference time domain calculation of three-dimensional phononic band structures using a postprocessing method based on the filter diagonalization

International Nuclear Information System (INIS)

Su Xiaoxing; Ma Tianxue; Wang Yuesheng

2011-01-01

If the band structure of a three-dimensional (3D) phononic crystal (PNC) is calculated by using the finite difference time domain (FDTD) method combined with the fast Fourier transform (FFT)-based postprocessing method, good results can only be ensured by a sufficiently large number of FDTD iterations. On a common computer platform, the total computation time will be very long. To overcome this difficulty, an excellent harmonic inversion algorithm called the filter diagonalization method (FDM) can be used in the postprocessing to reduce the number of FDTD iterations. However, the low efficiency of the FDM, which occurs when a relatively long time series is given, does not necessarily ensure an effective reduction of the total computation time. In this paper, a postprocessing method based on the FDM is proposed. The main procedure of the method is designed considering the aim to make the time spent on the method itself far less than the corresponding time spent on the FDTD iterations. To this end, the FDTD time series is preprocessed to be shortened significantly before the FDM frequency extraction. The preprocessing procedure is performed with the filter and decimation operations, which are widely used in narrow-band signal processing. Numerical results for a typical 3D solid PNC system show that the proposed postprocessing method can be used to effectively reduce the total computation time of the FDTD calculation of 3D phononic band structures.

Finite difference time domain calculation of three-dimensional phononic band structures using a postprocessing method based on the filter diagonalization

Energy Technology Data Exchange (ETDEWEB)

Su Xiaoxing [School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044 (China); Ma Tianxue; Wang Yuesheng, E-mail: xxsu@bjtu.edu.cn [Institute of Engineering Mechanics, Beijing Jiaotong University, Beijing 100044 (China)

2011-10-15

If the band structure of a three-dimensional (3D) phononic crystal (PNC) is calculated by using the finite difference time domain (FDTD) method combined with the fast Fourier transform (FFT)-based postprocessing method, good results can only be ensured by a sufficiently large number of FDTD iterations. On a common computer platform, the total computation time will be very long. To overcome this difficulty, an excellent harmonic inversion algorithm called the filter diagonalization method (FDM) can be used in the postprocessing to reduce the number of FDTD iterations. However, the low efficiency of the FDM, which occurs when a relatively long time series is given, does not necessarily ensure an effective reduction of the total computation time. In this paper, a postprocessing method based on the FDM is proposed. The main procedure of the method is designed considering the aim to make the time spent on the method itself far less than the corresponding time spent on the FDTD iterations. To this end, the FDTD time series is preprocessed to be shortened significantly before the FDM frequency extraction. The preprocessing procedure is performed with the filter and decimation operations, which are widely used in narrow-band signal processing. Numerical results for a typical 3D solid PNC system show that the proposed postprocessing method can be used to effectively reduce the total computation time of the FDTD calculation of 3D phononic band structures.

Comparison of robust H∞ filter and Kalman filter for initial alignment of inertial navigation system

Institute of Scientific and Technical Information of China (English)

HAO Yan-ling; CHEN Ming-hui; LI Liang-jun; XU Bo

2008-01-01

There are many filtering methods that can be used for the initial alignment of an integrated inertial navigation system.This paper discussed the use of GPS,but focused on two kinds of filters for the initial alignment of an integrated strapdown inertial navigation system (SINS).One method is based on the Kalman filter (KF),and the other is based on the robust filter.Simulation results showed that the filter provides a quick transient response and a little more accurate estimate than KF,given substantial process noise or unknown noise statistics.So the robust filter is an effective and useful method for initial alignment of SINS.This research should make the use of SINS more popular,and is also a step for further research.

Filtering of SPECT reconstructions made using Bellini's attenuation correction method

International Nuclear Information System (INIS)

Glick, S.J.; Penney, B.C.; King, M.A.

1991-01-01

This paper evaluates a three-dimensional (3D) Wiener filter which is used to restore SPECT reconstructions which were made using Bellini's method of attenuation correction. Its performance is compared to that of several pre-reconstruction filers: the one-dimensional (1D) Butterworth, the two-dimensional (2D) Butterworth, and a 2D Wiener filer. A simulation study is used to compare the four filtering methods. An approximation to a clinical liver spleen study was used as the source distribution and algorithm which accounts for the depth and distance dependent blurring in SPECT was used to compute noise free projections. To study the effect of filtering method on tumor detection accuracy, a 2 cm diameter, cool spherical tumor (40% contrast) was placed at a known, but random, location with the liver. Projection sets for ten tumor locations were computed and five noise realizations of each set were obtained by introducing Poisson noise. The simulated projections were either: filtered with the 1D or 2D Butterworth or the 2D Wiener and then reconstructed using Bellini's intrinsic attenuation correction, or reconstructed first, then filtered with the 3D Wiener. The criteria used for comparison were: normalized mean square error (NMSE), cold spot contrast, and accuracy of tumor detection with an automated numerical method. Results indicate that restorations obtained with 3D Wiener filtering yielded significantly higher lesion contrast and lower NMSE values compared to the other methods of processing. The Wiener restoration filters and the 2D Butterworth all provided similar measures of detectability, which were noticeably higher than that obtained with 1D Butterworth smoothing

Avoiding the Use of Exhausted Drinking Water Filters: A Filter-Clock Based on Rusting Iron

Directory of Open Access Journals (Sweden)

Arnaud Igor Ndé-Tchoupé

2018-05-01

Full Text Available Efficient but affordable water treatment technologies are currently sought to solve the prevalent shortage of safe drinking water. Adsorption-based technologies are in the front-line of these efforts. Upon proper design, universally applied materials (e.g., activated carbons, bone chars, metal oxides are able to quantitatively remove inorganic and organic pollutants as well as pathogens from water. Each water filter has a defined removal capacity and must be replaced when this capacity is exhausted. Operational experience has shown that it may be difficult to convince some low-skilled users to buy new filters after a predicted service life. This communication describes the quest to develop a filter-clock to encourage all users to change their filters after the designed service life. A brief discussion on such a filter-clock based on rusting of metallic iron (Fe0 is presented. Integrating such filter-clocks in the design of water filters is regarded as essential for safeguarding public health.

Multi-band transmission color filters for multi-color white LEDs based visible light communication

Science.gov (United States)

Wang, Qixia; Zhu, Zhendong; Gu, Huarong; Chen, Mengzhu; Tan, Qiaofeng

2017-11-01

Light-emitting diodes (LEDs) based visible light communication (VLC) can provide license-free bands, high data rates, and high security levels, which is a promising technique that will be extensively applied in future. Multi-band transmission color filters with enough peak transmittance and suitable bandwidth play a pivotal role for boosting signal-noise-ratio in VLC systems. In this paper, multi-band transmission color filters with bandwidth of dozens nanometers are designed by a simple analytical method. Experiment results of one-dimensional (1D) and two-dimensional (2D) tri-band color filters demonstrate the effectiveness of the multi-band transmission color filters and the corresponding analytical method.

An improved filtered spherical harmonic method for transport calculations

International Nuclear Information System (INIS)

Ahrens, C.; Merton, S.

2013-01-01

Motivated by the work of R. G. McClarren, C. D. Hauck, and R. B. Lowrie on a filtered spherical harmonic method, we present a new filter for such numerical approximations to the multi-dimensional transport equation. In several test problems, we demonstrate that the new filter produces results with significantly less Gibbs phenomena than the filter used by McClarren, Hauck and Lowrie. This reduction in Gibbs phenomena translates into propagation speeds that more closely match the correct propagation speed and solutions that have fewer regions where the scalar flux is negative. (authors)

Systematic Design of the Lead-Lag Network Method for Active Damping in LCL-Filter Based Three Phase Converters

DEFF Research Database (Denmark)

Alzola, Rafael Pena; Liserre, Marco; Blaabjerg, Frede

2014-01-01

) nor its rationale has been explained. Thus, in this paper a straightforward procedure is developed to tune the lead-lag network with the help of software tools. The rationale of this procedure, based on the capacitor current feedback, is elucidated. Stability is studied by means of the root locus......Three-phase active rectifiers guarantee sinusoidal input currents and unity power factor at the price of a high switching frequency ripple. To adopt an LCL-filter, instead of an L-filter, allows using reduced values for the inductances and so preserving dynamics. However, stability problems can...... without using dissipative elements but, sometimes, needing additional sensors. This solution has been addressed in many publications. The lead-lag network method is one of the first reported procedures and continues being in use. However, neither there is a direct tuning procedure (without trial and error...

Identifying city PV roof resource based on Gabor filter

Science.gov (United States)

Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

2017-06-01

To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

Moving Average Filter-Based Phase-Locked Loops: Performance Analysis and Design Guidelines

DEFF Research Database (Denmark)

Golestan, Saeed; Ramezani, Malek; Guerrero, Josep M.

2014-01-01

this challenge, incorporating moving average filter(s) (MAF) into the PLL structure has been proposed in some recent literature. A MAF is a linear-phase finite impulse response filter which can act as an ideal low-pass filter, if certain conditions hold. The main aim of this paper is to present the control...... design guidelines for a typical MAF-based PLL. The paper starts with the general description of MAFs. The main challenge associated with using the MAFs is then explained, and its possible solutions are discussed. The paper then proceeds with a brief overview of the different MAF-based PLLs. In each case......, the PLL block diagram description is shown, the advantages and limitations are briefly discussed, and the tuning approach (if available) is evaluated. The paper then presents two systematic methods to design the control parameters of a typical MAF-based PLL: one for the case of using a proportional...

A family of quantization based piecewise linear filter networks

DEFF Research Database (Denmark)

Sørensen, John Aasted

1992-01-01

A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization...... of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization......). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting...

Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation : Robustness and Accuracy Assessment

NARCIS (Netherlands)

Bourque, Alexandra E; Bedwani, Stéphane; Carrier, Jean-François; Ménard, Cynthia; Borman, Pim; Bos, Clemens; Raaymakers, Bas W; Mickevicius, Nikolai; Paulson, Eric; Tijssen, Rob H N

PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments. METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized

Random Access for Machine-Type Communication based on Bloom Filtering

DEFF Research Database (Denmark)

Pratas, Nuno; Stefanovic, Cedomir; Madueño, Germán Corrales

2016-01-01

utilizes the system resources more efficiently and achieves similar or lower latency of connection establishment in case of synchronous arrivals, compared to the variant of the LTE-A access protocol that is optimized for MTC traffic. A dividend of the proposed method is that allows the base station (BS......We present a random access method inspired on Bloom filters that is suited for Machine-Type Communications (MTC). Each accessing device sends a signature during the contention process. A signature is constructed using the Bloom filtering method and contains information on the device identity...... and the connection establishment cause. We instantiate the proposed method over the current LTE-A access protocol. However, the method is applicable to a more general class of random access protocols that use preambles or other reservation sequences, as expected to be the case in 5G systems. We show that our method...

Estimation of Sideslip Angle Based on Extended Kalman Filter

Directory of Open Access Journals (Sweden)

Yupeng Huang

2017-01-01

Full Text Available The sideslip angle plays an extremely important role in vehicle stability control, but the sideslip angle in production car cannot be obtained from sensor directly in consideration of the cost of the sensor; it is essential to estimate the sideslip angle indirectly by means of other vehicle motion parameters; therefore, an estimation algorithm with real-time performance and accuracy is critical. Traditional estimation method based on Kalman filter algorithm is correct in vehicle linear control area; however, on low adhesion road, vehicles have obvious nonlinear characteristics. In this paper, extended Kalman filtering algorithm had been put forward in consideration of the nonlinear characteristic of the tire and was verified by the Carsim and Simulink joint simulation, such as the simulation on the wet cement road and the ice and snow road with double lane change. To test and verify the effect of extended Kalman filtering estimation algorithm, the real vehicle test was carried out on the limit test field. The experimental results show that the accuracy of vehicle sideslip angle acquired by extended Kalman filtering algorithm is obviously higher than that acquired by Kalman filtering in the area of the nonlinearity.

Stabilizing the thermal lattice Boltzmann method by spatial filtering.

Science.gov (United States)

Gillissen, J J J

2016-10-01

We propose to stabilize the thermal lattice Boltzmann method by filtering the second- and third-order moments of the collision operator. By means of the Chapman-Enskog expansion, we show that the additional numerical diffusivity diminishes in the low-wavnumber limit. To demonstrate the enhanced stability, we consider a three-dimensional thermal lattice Boltzmann system involving 33 discrete velocities. Filtering extends the linear stability of this thermal lattice Boltzmann method to 10-fold smaller transport coefficients. We further demonstrate that the filtering does not compromise the accuracy of the hydrodynamics by comparing simulation results to reference solutions for a number of standardized test cases, including natural convection in two dimensions.

Time-windows-based filtering method for near-surface detection of leakage from geologic carbon sequestration sites

Energy Technology Data Exchange (ETDEWEB)

Pan, L.; Lewicki, J.L.; Oldenburg, C.M.; Fischer, M.L.

2010-02-28

We use process-based modeling techniques to characterize the temporal features of natural biologically controlled surface CO{sub 2} fluxes and the relationships between the assimilation and respiration fluxes. Based on these analyses, we develop a signal-enhancing technique that combines a novel time-window splitting scheme, a simple median filtering, and an appropriate scaling method to detect potential signals of leakage of CO{sub 2} from geologic carbon sequestration sites from within datasets of net near-surface CO{sub 2} flux measurements. The technique can be directly applied to measured data and does not require subjective gap filling or data-smoothing preprocessing. Preliminary application of the new method to flux measurements from a CO{sub 2} shallow-release experiment appears promising for detecting a leakage signal relative to background variability. The leakage index of ?2 was found to span the range of biological variability for various ecosystems as determined by observing CO{sub 2} flux data at various control sites for a number of years.

OTRA-Based Multi-Function Inverse Filter Configuration

Directory of Open Access Journals (Sweden)

Abdhesh Kumar Singh

2017-01-01

Full Text Available A new OTRA-based multifunction Inverse filter configuration is presented which is capable of realizing low pass, high pass and band pass filters using only two OTRAs and five to six passive elements. To the best knowledge of the authors, any inverse filter configuration using OTRAs has not been reported in the literature earlier. The effect of the major parasitics of the OTRAs and their effect on the performance filter have been investigated and measured through simulation results and Monte-Carlo analysis. The workability of the proposed circuits has been confirmed by SPICE simulations using CMOS-based-OTRA realizable in 0.18 µm CMOS technology. The proposed circuits are the only ones which provide simultaneously the following features: use of reasonable number of active elements (only 2, realizability of all the three basic filter functions, employment of all virtually grounded resistors and capacitors and tunability of all filter parameters (except gain factor, H_0 for inverse high pass. The centre/cut-off frequency of the various filter circuits lying in the vicinity of 1 MHz have been found to be realizable, which has been verified through SPICE simulation results and have been found to be in good agreement with the theoretical results.

Removal method of radium in mine water by filter sand

International Nuclear Information System (INIS)

Taki, Tomihiro; Naganuma, Masaki

2003-01-01

Trace radium is contained in mine water from the old mine road in Ningyo-Toge Environmental Engineering Center, JNC. We observed that filter sand with hydrated manganese oxide adsorbed radium in the mine water safely for long time. The removal method of radium by filter sand cladding with hydrated manganese oxide was studied. The results showed that radium was removed continuously and last for a long time from mine water with sodium hypochlorite solution by passing through the filter sand cladding with hydrated manganese. Only sodium hypochlorite solution was used. When excess of it was added, residue chlorine was used as chlorine disinfection. Filter sand cladding with hydrated manganese on the market can remove radium in the mine water. The removal efficiency of radium is the same as the radium coprecipitation method added with barium chloride. The cost is much lower than the ordinary methods. Amount of waste decreased to about 1/20 of the coprecipitation method. (S.Y.)

Aggregated wind power generation probabilistic forecasting based on particle filter

International Nuclear Information System (INIS)

Li, Pai; Guan, Xiaohong; Wu, Jiang

2015-01-01

Highlights: • A new method for probabilistic forecasting of aggregated wind power generation. • A dynamic system is established based on a numerical weather prediction model. • The new method handles the non-Gaussian and time-varying wind power uncertainties. • Particle filter is applied to forecast predictive densities of wind generation. - Abstract: Probability distribution of aggregated wind power generation in a region is one of important issues for power system daily operation. This paper presents a novel method to forecast the predictive densities of the aggregated wind power generation from several geographically distributed wind farms, considering the non-Gaussian and non-stationary characteristics in wind power uncertainties. Based on a mesoscale numerical weather prediction model, a dynamic system is established to formulate the relationship between the atmospheric and near-surface wind fields of geographically distributed wind farms. A recursively backtracking framework based on the particle filter is applied to estimate the atmospheric state with the near-surface wind power generation measurements, and to forecast the possible samples of the aggregated wind power generation. The predictive densities of the aggregated wind power generation are then estimated based on these predicted samples by a kernel density estimator. In case studies, the new method presented is tested on a 9 wind farms system in Midwestern United States. The testing results that the new method can provide competitive interval forecasts for the aggregated wind power generation with conventional statistical based models, which validates the effectiveness of the new method

A method of alpha-radiating nuclide activity measuring in aerosol filters

International Nuclear Information System (INIS)

Ignatov, V.P.; Galkina, V.N.

1992-01-01

Scintillation method of determination of alpha-radiating nuclide activity in aerosol filters was suggested. The method involves dissolution of the filter in organic solvent, introduction of luminophore into solution prepared, drying of the preparation and measurement of radionuclide activity. Dependences of alpha-radiation detection efficiency on the content of luminophore, filter material, colourless and coloured substances in preparations analyzed were considered

In-plane Material Filters for the Discrete Material Optimization Method

DEFF Research Database (Denmark)

Sørensen, Rene; Lund, Erik

2015-01-01

, because the projection filter is a non-linear function of the design variables, the projected variables have to be re-scaled in a final so-called normalization filter. This is done to prevent the optimizer in creating superior, but non-physical pseudo-materials. The method is demonstrated on a series......This paper presents in-plane material filters for the Discrete Material Optimization method used for optimizing laminated composite structures. The filters make it possible for engineers to specify a minimum length scale which governs the minimum size of areas with constant material continuity....... Consequently, engineers can target the available production methods, and thereby increase its manufacturability while the optimizer is free to determine which material to apply together with an optimum location, shape, and size of these areas with constant material continuity. By doing so, engineers no longer...

Variance-to-mean method generalized by linear difference filter technique

International Nuclear Information System (INIS)

Hashimoto, Kengo; Ohsaki, Hiroshi; Horiguchi, Tetsuo; Yamane, Yoshihiro; Shiroya, Seiji

1998-01-01

The conventional variance-to-mean method (Feynman-α method) seriously suffers the divergency of the variance under such a transient condition as a reactor power drift. Strictly speaking, then, the use of the Feynman-α is restricted to a steady state. To apply the method to more practical uses, it is desirable to overcome this kind of difficulty. For this purpose, we propose an usage of higher-order difference filter technique to reduce the effect of the reactor power drift, and derive several new formulae taking account of the filtering. The capability of the formulae proposed was demonstrated through experiments in the Kyoto University Critical Assembly. The experimental results indicate that the divergency of the variance can be effectively suppressed by the filtering technique, and that the higher-order filter becomes necessary with increasing variation rate in power

Qualitative performance comparison of reactivity estimation between the extended Kalman filter technique and the inverse point kinetic method

International Nuclear Information System (INIS)

Shimazu, Y.; Rooijen, W.F.G. van

2014-01-01

Highlights: • Estimation of the reactivity of nuclear reactor based on neutron flux measurements. • Comparison of the traditional method, and the new approach based on Extended Kalman Filtering (EKF). • Estimation accuracy depends on filter parameters, the selection of which is described in this paper. • The EKF algorithm is preferred if the signal to noise ratio is low (low flux situation). • The accuracy of the EKF depends on the ratio of the filter coefficients. - Abstract: The Extended Kalman Filtering (EKF) technique has been applied for estimation of subcriticality with a good noise filtering and accuracy. The Inverse Point Kinetic (IPK) method has also been widely used for reactivity estimation. The important parameters for the EKF estimation are the process noise covariance, and the measurement noise covariance. However the optimal selection is quite difficult. On the other hand, there is only one parameter in the IPK method, namely the time constant for the first order delay filter. Thus, the selection of this parameter is quite easy. Thus, it is required to give certain idea for the selection of which method should be selected and how to select the required parameters. From this point of view, a qualitative performance comparison is carried out

Filtering apparatus and method for mixing, extraction and/or separation

DEFF Research Database (Denmark)

2013-01-01

The present invention relates to a filtering apparatus and method for mixing a compound of solid and fluid phases, separating the phases and/or extracting fluid from the compound. One embodiment of the invention discloses a filtering apparatus comprising a first filter section accommodating a fir...... in a beer brewing procedure....

Harmonic Active Filtering and Impedance-based Stability Analysis in Offshore Wind Power Plants

DEFF Research Database (Denmark)

Dhua, Debasish; Yang, Guangya; Zhang, Zhe

2017-01-01

installation and provides effectively similar functionality as passive filters. This work is focused on harmonic propagation studies in wind power plants, power quality evaluation at the point of connection and harmonic mitigation by active filtering. Finally, an impedance-based stability analysis......Nowadays, to eliminate harmonics injected by the wind turbines in offshore wind power plants there is a need to install passive filters. Moreover, the passive filters are not adaptive to harmonic profile changes due to topology changes, grid loading etc. Therefore, active filters in wind turbines...... are proposed as a flexible harmonic mitigation measure. The motivation of this study is to explore the possibility of embedding active filtering in wind turbine grid-side converters without having to change the system electrical infrastructure. The active filtering method can prevent additional equipment...

Spectral information enhancement using wavelet-based iterative filtering for in vivo gamma spectrometry.

Science.gov (United States)

Paul, Sabyasachi; Sarkar, P K

2013-04-01

Use of wavelet transformation in stationary signal processing has been demonstrated for denoising the measured spectra and characterisation of radionuclides in the in vivo monitoring analysis, where difficulties arise due to very low activity level to be estimated in biological systems. The large statistical fluctuations often make the identification of characteristic gammas from radionuclides highly uncertain, particularly when interferences from progenies are also present. A new wavelet-based noise filtering methodology has been developed for better detection of gamma peaks in noisy data. This sequential, iterative filtering method uses the wavelet multi-resolution approach for noise rejection and an inverse transform after soft 'thresholding' over the generated coefficients. Analyses of in vivo monitoring data of (235)U and (238)U were carried out using this method without disturbing the peak position and amplitude while achieving a 3-fold improvement in the signal-to-noise ratio, compared with the original measured spectrum. When compared with other data-filtering techniques, the wavelet-based method shows the best results.

Variable flexure-based fluid filter

Science.gov (United States)

Brown, Steve B.; Colston, Jr., Billy W.; Marshall, Graham; Wolcott, Duane

2007-03-13

An apparatus and method for filtering particles from a fluid comprises a fluid inlet, a fluid outlet, a variable size passage between the fluid inlet and the fluid outlet, and means for adjusting the size of the variable size passage for filtering the particles from the fluid. An inlet fluid flow stream is introduced to a fixture with a variable size passage. The size of the variable size passage is set so that the fluid passes through the variable size passage but the particles do not pass through the variable size passage.

Instantaneous Attitude Determination Based on Original Multi-antenna Observations Using Adaptively Robust Kalman Filtering

Directory of Open Access Journals (Sweden)

GAN Yu

2015-09-01

Full Text Available Attitude determination directly by carrier phase observation makes optimal use of observation and attitude constraints. The phase models based on misalignment angle and multiplicative quaternion error are derived. The state models for attitude estimation with and without external angular rate sensors are both erected. The attitude errors are estimated by adaptively robust filtering, in which the adaptive factors of ambiguity and attitude error are decided respectively following the idea of multi adaptive factor filtering. The factor of attitude is determined by a three-section function containing Ratio. Adaptively robust filtering makes the best use of constraint and historical information, fusing them in the calculation of float solution. As the accuracy of float solution and the structure of covariance matrix are improved greatly, the fix solution can be searched efficiently using LAMBDA (least-squares ambiguity decorrelation adjustment method merely, perfectly fulfilling the real-time requirement. Field test of a ship-based three-antenna attitude system is used to validate the proposed method. It is showed that direct attitude determination based on adaptively robust filtering has obvious advantages in efficiency and reliability.

A New Synchronous Reference Frame-Based Method for Single-Phase Shunt Active Power Filters

DEFF Research Database (Denmark)

Monfared, Mohammad; Golestan, Saeed; Guerrero, Josep M.

2013-01-01

This paper deals with the design of a novel method in the synchronous reference frame (SRF) to extract the reference compensating current for single-phase shunt active power filters (APFs). Unlike previous works in the SRF, the proposed method has an innovative feature that it does not need...... the fictitious current signal. Frequency-independent operation, accurate reference current extraction and relatively fast transient response are other key features of the presented strategy. The effectiveness of the proposed method is investigated by means of detailed mathematical analysis. The results confirm...

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.

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.

Acousto-Optic Tunable Filter Hyperspectral Microscope Imaging Method for Characterizing Spectra from Foodborne Pathogens.

Science.gov (United States)

Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral characteristics of samples, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmon...

Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Supriya Dhabal

2014-01-01

Full Text Available We present a novel hybrid algorithm based on particle swarm optimization (PSO and simulated annealing (SA for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The experimental results reveal that the performance of the optimal filter designed by the proposed SA-PSO method is improved. Further, the convergence behavior as well as optimization accuracy of proposed method has been improved significantly and computational time is also reduced. In addition, the proposed SA-PSO method also produces the best optimal solution with lower mean and variance which indicates that the algorithm can be used more efficiently in realizing two-dimensional digital filters.

Pressure-controlled terahertz filter based on 1D photonic crystal with a defective semiconductor

Science.gov (United States)

Qinwen, XUE; Xiaohua, WANG; Chenglin, LIU; Youwen, LIU

2018-03-01

The tunable terahertz (THz) filter has been designed and studied, which is composed of 1D photonic crystal (PC) containing a defect layer of semiconductor GaAs. The analytical solution of 1D defective PC (1DDPC) is deduced based on the transfer matrix method, and the electromagnetic plane wave numerical simulation of this 1DDPC is performed by using the finite element method. The calculated and simulated results have confirmed that the filtering transmittance of this 1DDPC in symmetric structure of air/(Si/SiO2) N /GaAs/(SiO2/Si) N /air is far higher than in asymmetric structure of air/(Si/SiO2) N /GaAs/(Si/SiO2) N /air, where the filtering frequency can be tuned by the external pressure. It can provide a feasible route to design the external pressure-controlled THz filter based on 1DPC with a defective semiconductor.

Efficient Scalable Median Filtering Using Histogram-Based Operations.

Science.gov (United States)

Green, Oded

2018-05-01

Median filtering is a smoothing technique for noise removal in images. While there are various implementations of median filtering for a single-core CPU, there are few implementations for accelerators and multi-core systems. Many parallel implementations of median filtering use a sorting algorithm for rearranging the values within a filtering window and taking the median of the sorted value. While using sorting algorithms allows for simple parallel implementations, the cost of the sorting becomes prohibitive as the filtering windows grow. This makes such algorithms, sequential and parallel alike, inefficient. In this work, we introduce the first software parallel median filtering that is non-sorting-based. The new algorithm uses efficient histogram-based operations. These reduce the computational requirements of the new algorithm while also accessing the image fewer times. We show an implementation of our algorithm for both the CPU and NVIDIA's CUDA supported graphics processing unit (GPU). The new algorithm is compared with several other leading CPU and GPU implementations. The CPU implementation has near perfect linear scaling with a speedup on a quad-core system. The GPU implementation is several orders of magnitude faster than the other GPU implementations for mid-size median filters. For small kernels, and , comparison-based approaches are preferable as fewer operations are required. Lastly, the new algorithm is open-source and can be found in the OpenCV library.

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.

Classification of Textures Using Filter Based Local Feature Extraction

Directory of Open Access Journals (Sweden)

Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

State and force observers based on multibody models and the indirect Kalman filter

Science.gov (United States)

Sanjurjo, Emilio; Dopico, Daniel; Luaces, Alberto; Naya, Miguel Ángel

2018-06-01

The aim of this work is to present two new methods to provide state observers by combining multibody simulations with indirect extended Kalman filters. One of the methods presented provides also input force estimation. The observers have been applied to two mechanism with four different sensor configurations, and compared to other multibody-based observers found in the literature to evaluate their behavior, namely, the unscented Kalman filter (UKF), and the indirect extended Kalman filter with simplified Jacobians (errorEKF). The new methods have some more computational cost than the errorEKF, but still much less than the UKF. Regarding their accuracy, both are better than the errorEKF. The method with input force estimation outperforms also the UKF, while the method without force estimation achieves results almost identical to those of the UKF. All the methods have been implemented as a reusable MATLAB® toolkit which has been released as Open Source in https://github.com/MBDS/mbde-matlab.

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

Science.gov (United States)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter

Directory of Open Access Journals (Sweden)

Bizhong Xia

2015-11-01

Full Text Available The estimation of state of charge (SOC is a crucial evaluation index in a battery management system (BMS. The value of SOC indicates the remaining capacity of a battery, which provides a good guarantee of safety and reliability of battery operation. It is difficult to get an accurate value of the SOC, being one of the inner states. In this paper, a strong tracking cubature Kalman filter (STCKF based on the cubature Kalman filter is presented to perform accurate and reliable SOC estimation. The STCKF algorithm can adjust gain matrix online by introducing fading factor to the state estimation covariance matrix. The typical second-order resistor-capacitor model is used as the battery’s equivalent circuit model to dynamically simulate characteristics of the battery. The exponential-function fitting method accomplishes the task of relevant parameters identification. Then, the developed STCKF algorithm has been introduced in detail and verified under different operation current profiles such as Dynamic Stress Test (DST and New European Driving Cycle (NEDC. Making a comparison with extended Kalman filter (EKF and CKF algorithm, the experimental results show the merits of the STCKF algorithm in SOC estimation accuracy and robustness.

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.

A narrowband filter based on 2D 8-fold photonic quasicrystal

Science.gov (United States)

Ren, Jie; Sun, XiaoHong; Wang, Shuai

2018-04-01

In this paper, a novel structure of narrowband filter based on 2D 8-fold photonic quasicrystal (PQC) is proposed and investigated. The structure size is 8 μm × 8 μm, which promises its applications in optical integrated circuits and communication devices. Finite Element Method (FEM) has been employed to investigate the band gap of the filter. The resonance wavelength, transmission coefficient and 3 dB bandwidth are analyzed by varying the parameters of the structure. By optimizing the parameters of the filter, two design formulas of resonance wavelength are obtained. Also, for its better linearity of the resonance, the structure with line-defect has also seen a large uptake in sensor design.

PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

Directory of Open Access Journals (Sweden)

Wei Leong Khong

2014-02-01

Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

Fuzzy adaptive Kalman filter for indoor mobile target positioning with INS/WSN integrated method

Institute of Scientific and Technical Information of China (English)

杨海; 李威; 罗成名

2015-01-01

Pure inertial navigation system (INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network (WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter (KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system (FIS), and the fuzzy adaptive Kalman filter (FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.

A Decoupling Control Method for Shunt Hybrid Active Power Filter Based on Generalized Inverse System

Directory of Open Access Journals (Sweden)

Xin Li

2017-01-01

Full Text Available In this paper, a novel decoupling control method based on generalized inverse system is presented to solve the problem of SHAPF (Shunt Hybrid Active Power Filter possessing the characteristics of 2-input-2-output nonlinearity and strong coupling. Based on the analysis of operation principle, the mathematical model of SHAPF is firstly built, which is verified to be invertible using interactor algorithm; then the generalized inverse system of SHAPF is obtained to connect in series with the original system so that the composite system is decoupled under the generalized inverse system theory. The PI additional controller is finally designed to control the decoupled 1-order pseudolinear system to make it possible to adjust the performance of the subsystem. The simulation results demonstrated by MATLAB show that the presented generalized inverse system strategy can realise the dynamic decoupling of SHAPF. And the control system has fine dynamic and static performance.

Analysis of the Passive Damping Losses in LCL-Filter-Based Grid Converters

DEFF Research Database (Denmark)

Alzola, Rafael Pena; Liserre, Marco; Blaabjerg, Frede

2013-01-01

Passive damping is the most adopted method to guarantee the stability of LCL-filter-based grid converters. The method is simple and, if the switching and sampling frequencies are sufficiently high, the damping losses are negligible. This letter proposes the tuning of different passive damping...

Adaptive probabilistic collocation based Kalman filter for unsaturated flow problem

Science.gov (United States)

Man, J.; Li, W.; Zeng, L.; Wu, L.

2015-12-01

The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the Polynomial Chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so called "cure of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF is even more computationally expensive than EnKF. Motivated by recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problem. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to alleviate the inconsistency between model parameters and states. The performance of RAPCKF is tested by unsaturated flow numerical cases. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.

Evaluation of harmonic detection methods for active power filter applications

DEFF Research Database (Denmark)

Asiminoaei, Lucian; Blaabjerg, Frede; Hansen, Steffan

2005-01-01

In the attempt to minimize the harmonic disturbances created by the non-linear loads the choice of the active power filters comes out to improve the filtering efficiency and to solve many issues existing with classical passive filters. One of the key points for a proper implementation of an active...... theories. Then, the work here proposes a simulation setup that decouples the harmonic reference generator from the active filter model and its controller. In this way the selected methods can be equally analyzed and compared with respect to their performance, which helps anticipating possible...

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.

A Method for Designing FIR Filters with Arbitrary Magnitude Characteristic Used for Modeling Human Audiogram

Directory of Open Access Journals (Sweden)

SZOPOS, E.

2012-05-01

Full Text Available This paper presents an iterative method for designing FIR filters that implement arbitrary magnitude characteristics, defined by the user through a set of frequency-magnitude points (frequency samples. The proposed method is based on the non-uniform frequency sampling algorithm. For each iteration a new set of frequency samples is generated, by processing the set used in the previous run; this implies changing the samples location around the previous frequency values and adjusting their magnitude through interpolation. If necessary, additional samples can be introduced, as well. After each iteration the magnitude characteristic of the resulting filter is determined by using the non-uniform DFT and compared with the required one; if the errors are larger than the acceptable levels (set by the user a new iteration is run; the length of the resulting filter and the values of its coefficients are also taken into consideration when deciding a re-run. To demonstrate the efficiency of the proposed method a tool for designing FIR filters that match human audiograms was implemented in LabVIEW. It was shown that the resulting filters have smaller coefficients than the standard one, and can also have lower order, while the errors remain relatively small.

Development of gel-filter method for high enrichment of low-molecular weight proteins from serum.

Directory of Open Access Journals (Sweden)

Lingsheng Chen

Full Text Available The human serum proteome has been extensively screened for biomarkers. However, the large dynamic range of protein concentrations in serum and the presence of highly abundant and large molecular weight proteins, make identification and detection changes in the amount of low-molecular weight proteins (LMW, molecular weight ≤ 30kDa difficult. Here, we developed a gel-filter method including four layers of different concentration of tricine SDS-PAGE-based gels to block high-molecular weight proteins and enrich LMW proteins. By utilizing this method, we identified 1,576 proteins (n = 2 from 10 μL serum. Among them, 559 (n = 2 proteins belonged to LMW proteins. Furthermore, this gel-filter method could identify 67.4% and 39.8% more LMW proteins than that in representative methods of glycine SDS-PAGE and optimized-DS, respectively. By utilizing SILAC-AQUA approach with labeled recombinant protein as internal standard, the recovery rate for GST spiked in serum during the treatment of gel-filter, optimized-DS, and ProteoMiner was 33.1 ± 0.01%, 18.7 ± 0.01% and 9.6 ± 0.03%, respectively. These results demonstrate that the gel-filter method offers a rapid, highly reproducible and efficient approach for screening biomarkers from serum through proteomic analyses.

Independent component analysis based filtering for penumbral imaging

International Nuclear Information System (INIS)

Chen Yenwei; Han Xianhua; Nozaki, Shinya

2004-01-01

We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters

A METHOD FOR RECORDING AND VIEWING STEREOSCOPIC IMAGES IN COLOUR USING MULTICHROME FILTERS

DEFF Research Database (Denmark)

2000-01-01

in a conventional stereogram recorded of the scene. The invention makes use of a colour-based encoding technique and viewing filters selected so that the human observer receives, in one eye, an image of nearly full colour information, in the other eye, an essentially monochrome image supplying the parallactic......The aim of the invention is to create techniques for the encoding, production and viewing of stereograms, supplemented by methods for selecting certain optical filters needed in these novel techniques, thus providing a human observer with stereograms each of which consist of a single image...

A Bioinspired Neural Model Based Extended Kalman Filter for Robot SLAM

Directory of Open Access Journals (Sweden)

Jianjun Ni

2014-01-01

Full Text Available Robot simultaneous localization and mapping (SLAM problem is a very important and challenging issue in the robotic field. The main tasks of SLAM include how to reduce the localization error and the estimated error of the landmarks and improve the robustness and accuracy of the algorithms. The extended Kalman filter (EKF based method is one of the most popular methods for SLAM. However, the accuracy of the EKF based SLAM algorithm will be reduced when the noise model is inaccurate. To solve this problem, a novel bioinspired neural model based SLAM approach is proposed in this paper. In the proposed approach, an adaptive EKF based SLAM structure is proposed, and a bioinspired neural model is used to adjust the weights of system noise and observation noise adaptively, which can guarantee the stability of the filter and the accuracy of the SLAM algorithm. The proposed approach can deal with the SLAM problem in various situations, for example, the noise is in abnormal conditions. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach.

WaVPeak: Picking NMR peaks through wavelet-based smoothing and volume-based filtering

KAUST Repository

Liu, Zhi

2012-02-10

Motivation: Nuclear magnetic resonance (NMR) has been widely used as a powerful tool to determine the 3D structures of proteins in vivo. However, the post-spectra processing stage of NMR structure determination usually involves a tremendous amount of time and expert knowledge, which includes peak picking, chemical shift assignment and structure calculation steps. Detecting accurate peaks from the NMR spectra is a prerequisite for all following steps, and thus remains a key problem in automatic NMR structure determination. Results: We introduce WaVPeak, a fully automatic peak detection method. WaVPeak first smoothes the given NMR spectrum by wavelets. The peaks are then identified as the local maxima. The false positive peaks are filtered out efficiently by considering the volume of the peaks. WaVPeak has two major advantages over the state-of-the-art peak-picking methods. First, through wavelet-based smoothing, WaVPeak does not eliminate any data point in the spectra. Therefore, WaVPeak is able to detect weak peaks that are embedded in the noise level. NMR spectroscopists need the most help isolating these weak peaks. Second, WaVPeak estimates the volume of the peaks to filter the false positives. This is more reliable than intensity-based filters that are widely used in existing methods. We evaluate the performance of WaVPeak on the benchmark set proposed by PICKY (Alipanahi et al., 2009), one of the most accurate methods in the literature. The dataset comprises 32 2D and 3D spectra from eight different proteins. Experimental results demonstrate that WaVPeak achieves an average of 96%, 91%, 88%, 76% and 85% recall on 15N-HSQC, HNCO, HNCA, HNCACB and CBCA(CO)NH, respectively. When the same number of peaks are considered, WaVPeak significantly outperforms PICKY. The Author(s) 2012. Published by Oxford University Press.

Comprehensive Utilization of Filter Residue from the Preparation Process of Zeolite-Based Catalysts

Directory of Open Access Journals (Sweden)

Shu-Qin Zheng

2016-05-01

Full Text Available A novel utilization method of filter residue from the preparation process of zeolite-based catalysts was investigated. Y zeolite and a fluid catalytic cracking (FCC catalyst were synthesized from filter residue. Compared to the Y zeolite synthesized by the conventional method, the Y zeolite synthesized from filter residue exhibited better thermal stability. The catalyst possessed wide-pore distribution. In addition, the pore volume, specific surface area, attrition resistance were superior to those of the reference catalyst. The yields of gasoline and light oil increased by 1.93 and 1.48 %, respectively. At the same time, the coke yield decreased by 0.41 %. The catalyst exhibited better gasoline and coke selectivity. The quality of the cracked gasoline had been improved.

A wavelet filtering method for cumulative gamma spectroscopy used in wear measurements

International Nuclear Information System (INIS)

Bianchi, Davide; Lenauer, Claudia; Betz, Gerhard; Vernes, András

2017-01-01

Continuous ultra-mild wear quantification using radioactive isotopes involves measuring very low amounts of activity in limited time intervals. This results in gamma spectra with poor signal-to-noise ratio and hence very scattered wear data, especially during running-in, where wear is intrinsically low. Therefore, advanced filtering methods reducing the wear data scattering and making the calculation of the main peak area more accurate are mandatory. An energy-time dependent threshold for wavelet detail coefficients based on Poisson statistics and using a combined Barwell law for the estimation of the average photon counting rate is then introduced. In this manner, it was shown that the accuracy of running-in wear quantification is enhanced. - Highlights: • Time-dependent Poisson statistics. • Wavelet-based filtering of cumulative gamma spectra. • Improvement of low wear analysis.

Comparison of various filtering methods for digital X-ray image processing

International Nuclear Information System (INIS)

Pfluger, T.; Reinfelder, H.E.; Dorschky, K.; Oppelt, A.; Siemens A.G., Erlangen

1987-01-01

Three filtering methods are explained and compared that are used for border edge enhancement of digitally processed X-ray images. The filters are compared by two examples, a radiograph of the chest, and one of the knee joint. The unsharpness mask is found to yield the best compromise between edge enhancement and image noise intensifying effect, whereas the results obtained by the high-pass filter or the Wallis filter are less good for diagnostic evaluation. The filtered images better display narrow lines, structural borders and edges, and finely spotted areas, than the original radiograph, so that diagnostic evaluation is easier after image filtering. (orig.) [de

Automated microaneurysm detection method based on double ring filter in retinal fundus images

Science.gov (United States)

Mizutani, Atsushi; Muramatsu, Chisako; Hatanaka, Yuji; Suemori, Shinsuke; Hara, Takeshi; Fujita, Hiroshi

2009-02-01

The presence of microaneurysms in the eye is one of the early signs of diabetic retinopathy, which is one of the leading causes of vision loss. We have been investigating a computerized method for the detection of microaneurysms on retinal fundus images, which were obtained from the Retinopathy Online Challenge (ROC) database. The ROC provides 50 training cases, in which "gold standard" locations of microaneurysms are provided, and 50 test cases without the gold standard locations. In this study, the computerized scheme was developed by using the training cases. Although the results for the test cases are also included, this paper mainly discusses the results for the training cases because the "gold standard" for the test cases is not known. After image preprocessing, candidate regions for microaneurysms were detected using a double-ring filter. Any potential false positives located in the regions corresponding to blood vessels were removed by automatic extraction of blood vessels from the images. Twelve image features were determined, and the candidate lesions were classified into microaneurysms or false positives using the rule-based method and an artificial neural network. The true positive fraction of the proposed method was 0.45 at 27 false positives per image. Forty-two percent of microaneurysms in the 50 training cases were considered invisible by the consensus of two co-investigators. When the method was evaluated for visible microaneurysms, the sensitivity for detecting microaneurysms was 65% at 27 false positives per image. Our computerized detection scheme could be improved for helping ophthalmologists in the early diagnosis of diabetic retinopathy.

Planetary gearbox fault feature enhancement based on combined adaptive filter method

Directory of Open Access Journals (Sweden)

Shuangshu Tian

2015-12-01

Full Text Available The reliability of vibration signals acquired from a planetary gear system (the indispensable part of wind turbine gearbox is directly related to the accuracy of fault diagnosis. The complex operation environment leads to lots of interference signals which are included in the vibration signals. Furthermore, both multiple gears meshing with each other and the differences in transmission rout produce strong nonlinearity in the vibration signals, which makes it difficult to eliminate the noise. This article presents a combined adaptive filter method by taking a delayed signal as reference signal, the Self-Adaptive Noise Cancellation method is adopted to eliminate the white noise. In the meanwhile, by applying Gaussian function to transform the input signal into high-dimension feature-space signal, the kernel least mean square algorithm is used to cancel the nonlinear interference. Effectiveness of the method has been verified by simulation signals and test rig signals. By dealing with simulation signal, the signal-to-noise ratio can be improved around 30 dB (white noise and the amplitude of nonlinear interference signal can be depressed up to 50%. Experimental results show remarkable improvements and enhance gear fault features.

Probability-based collaborative filtering model for predicting gene–disease associations

OpenAIRE

Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

2017-01-01

Background Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene–disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. Methods We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our mo...

Word2vec and dictionary based approach for uyghur text filtering

Science.gov (United States)

Tohti, Turdi; Zhao, Yunxing; Musajan, Winira

2017-08-01

With emerging of deep learning, the expression of words in computer has made major breakthroughs and the effect of text processing based on word vector has also been significantly improved. This paper maps all patterns into a more abstract vector space by Uyghur-Chinese dictionary and deep learning tool Word2vec, at first. Secondly, a similar pattern is found according the characteristics of the original pattern. Finally, texts are filtered using Wu-Manber algorithm. Experiments show that this method can get obvious filtering accuracy and recall of Uyghur text information improved.

Comparisons of adaptive TIN modelling filtering method and threshold segmentation filtering method of LiDAR point cloud

International Nuclear Information System (INIS)

Chen, Lin; Fan, Xiangtao; Du, Xiaoping

2014-01-01

Point cloud filtering is the basic and key step in LiDAR data processing. Adaptive Triangle Irregular Network Modelling (ATINM) algorithm and Threshold Segmentation on Elevation Statistics (TSES) algorithm are among the mature algorithms. However, few researches concentrate on the parameter selections of ATINM and the iteration condition of TSES, which can greatly affect the filtering results. First the paper presents these two key problems under two different terrain environments. For a flat area, small height parameter and angle parameter perform well and for areas with complex feature changes, large height parameter and angle parameter perform well. One-time segmentation is enough for flat areas, and repeated segmentations are essential for complex areas. Then the paper makes comparisons and analyses of the results by these two methods. ATINM has a larger I error in both two data sets as it sometimes removes excessive points. TSES has a larger II error in both two data sets as it ignores topological relations between points. ATINM performs well even with a large region and a dramatic topology while TSES is more suitable for small region with flat topology. Different parameters and iterations can cause relative large filtering differences

Novel Simplex Unscented Transform and Filter

Institute of Scientific and Technical Information of China (English)

Wan-Chun Li; Ping Wei; Xian-Ci Xiao

2008-01-01

In this paper, a new simplex unscented transform (UT) based Schmidt orthogonal algorithm and a new filter method based on this transform are proposed. This filter has less computation consumption than UKF (unscented Kalman filter), SUKF (simplex unscented Kalman filter) and EKF (extended Kalman filter). Computer simulation shows that this filter has the same performance as UKF and SUKF, and according to the analysis of the computational requirements of EKF, UKF and SUKF, this filter has preferable practicality value. Finally, the appendix shows the efficiency for this UT.

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.

Simplified Method for Groundwater Treatment Using Dilution and Ceramic Filter

Science.gov (United States)

Musa, S.; Ariff, N. A.; Kadir, M. N. Abdul; Denan, F.

2016-07-01

Groundwater is one of the natural resources that is not susceptible to pollutants. However, increasing activities of municipal, industrial, agricultural or extreme land use activities have resulted in groundwater contamination as occured at the Research Centre for Soft Soil Malaysia (RECESS), Universiti Tun Hussein Onn Malaysia (UTHM). Thus, aims of this study is to treat groundwater by using rainwater and simple ceramic filter as a treatment agent. The treatment uses rain water dilution, ceramic filters and combined method of dilute and filtering as an alternate treatment which are simple and more practical compared to modern or chemical methods. The water went through dilution treatment processes able to get rid of 57% reduction compared to initial condition. Meanwhile, the water that passes through the filtering process successfully get rid of as much as 86% groundwater parameters where only chloride does not pass the standard. Favorable results for the combination methods of dilution and filtration methods that can succesfully eliminate 100% parameters that donot pass the standards of the Ministry of Health and the Interim National Drinking Water Quality Standard such as those found in groundwater in RECESS, UTHM especially sulfate and chloride. As a result, it allows the raw water that will use clean drinking water and safe. It also proves that the method used in this study is very effective in improving the quality of groundwater.

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

Energy Technology Data Exchange (ETDEWEB)

Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U., Phys. Dept.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U., Phys. Dept.; Riley, Daniel [Cornell U., Phys. Dept.; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U., Phys. Dept.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

2017-11-16

Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Examples include the Intel Xeon Phi, GPGPUs, and similar technologies. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.

Slice image pretreatment for cone-beam computed tomography based on adaptive filter

International Nuclear Information System (INIS)

Huang Kuidong; Zhang Dinghua; Jin Yanfang

2009-01-01

According to the noise properties and the serial slice image characteristics in Cone-Beam Computed Tomography (CBCT) system, a slice image pretreatment for CBCT based on adaptive filter was proposed. The judging criterion for the noise is established firstly. All pixels are classified into two classes: adaptive center weighted modified trimmed mean (ACWMTM) filter is used for the pixels corrupted by Gauss noise and adaptive median (AM) filter is used for the pixels corrupted by impulse noise. In ACWMTM filtering algorithm, the estimated Gauss noise standard deviation in the current slice image with offset window is replaced by the estimated standard deviation in the adjacent slice image to the current with the corresponding window, so the filtering accuracy of the serial images is improved. The pretreatment experiment on CBCT slice images of wax model of hollow turbine blade shows that the method makes a good performance both on eliminating noises and on protecting details. (authors)

Collaborative Filtering Based on Sequential Extraction of User-Item Clusters

Science.gov (United States)

Honda, Katsuhiro; Notsu, Akira; Ichihashi, Hidetomo

Collaborative filtering is a computational realization of “word-of-mouth” in network community, in which the items prefered by “neighbors” are recommended. This paper proposes a new item-selection model for extracting user-item clusters from rectangular relation matrices, in which mutual relations between users and items are denoted in an alternative process of “liking or not”. A technique for sequential co-cluster extraction from rectangular relational data is given by combining the structural balancing-based user-item clustering method with sequential fuzzy cluster extraction appraoch. Then, the tecunique is applied to the collaborative filtering problem, in which some items may be shared by several user clusters.

A novel hypothesis splitting method implementation for multi-hypothesis filters

DEFF Research Database (Denmark)

Bayramoglu, Enis; Ravn, Ole; Andersen, Nils Axel

2013-01-01

The paper presents a multi-hypothesis filter library featuring a novel method for splitting Gaussians into ones with smaller variances. The library is written in C++ for high performance and the source code is open and free1. The multi-hypothesis filters commonly approximate the distribution tran...

Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab

International Nuclear Information System (INIS)

An, Dawn; Choi, Joo-Ho; Kim, Nam Ho

2013-01-01

This paper presents a Matlab-based tutorial for model-based prognostics, which combines a physical model with observed data to identify model parameters, from which the remaining useful life (RUL) can be predicted. Among many model-based prognostics algorithms, the particle filter is used in this tutorial for parameter estimation of damage or a degradation model. The tutorial is presented using a Matlab script with 62 lines, including detailed explanations. As examples, a battery degradation model and a crack growth model are used to explain the updating process of model parameters, damage progression, and RUL prediction. In order to illustrate the results, the RUL at an arbitrary cycle are predicted in the form of distribution along with the median and 90% prediction interval. This tutorial will be helpful for the beginners in prognostics to understand and use the prognostics method, and we hope it provides a standard of particle filter based prognostics. -- Highlights: ► Matlab-based tutorial for model-based prognostics is presented. ► A battery degradation model and a crack growth model are used as examples. ► The RUL at an arbitrary cycle are predicted using the particle filter

Signal reconstruction in wireless sensor networks based on a cubature Kalman particle filter

International Nuclear Information System (INIS)

Huang Jin-Wang; Feng Jiu-Chao

2014-01-01

For solving the issues of the signal reconstruction of nonlinear non-Gaussian signals in wireless sensor networks (WSNs), a new signal reconstruction algorithm based on a cubature Kalman particle filter (CKPF) is proposed in this paper. We model the reconstruction signal first and then use the CKPF to estimate the signal. The CKPF uses a cubature Kalman filter (CKF) to generate the importance proposal distribution of the particle filter and integrates the latest observation, which can approximate the true posterior distribution better. It can improve the estimation accuracy. CKPF uses fewer cubature points than the unscented Kalman particle filter (UKPF) and has less computational overheads. Meanwhile, CKPF uses the square root of the error covariance for iterating and is more stable and accurate than the UKPF counterpart. Simulation results show that the algorithm can reconstruct the observed signals quickly and effectively, at the same time consuming less computational time and with more accuracy than the method based on UKPF. (general)

Sealing Clay Text Segmentation Based on Radon-Like Features and Adaptive Enhancement Filters

Directory of Open Access Journals (Sweden)

Xia Zheng

2015-01-01

Full Text Available Text extraction is a key issue in sealing clay research. The traditional method based on rubbings increases the risk of sealing clay damage and is unfavorable to sealing clay protection. Therefore, using digital image of sealing clay, a new method for text segmentation based on Radon-like features and adaptive enhancement filters is proposed in this paper. First, adaptive enhancement LM filter bank is used to get the maximum energy image; second, the edge image of the maximum energy image is calculated; finally, Radon-like feature images are generated by combining maximum energy image and its edge image. The average image of Radon-like feature images is segmented by the image thresholding method. Compared with 2D Otsu, GA, and FastFCM, the experiment result shows that this method can perform better in terms of accuracy and completeness of the text.

A Kalman Filter-Based Method to Generate Continuous Time Series of Medium-Resolution NDVI Images

Directory of Open Access Journals (Sweden)

Fernando Sedano

2014-12-01

Full Text Available A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products at four sites with different ecosystems and land cover-land use dynamics. The results show that the time series of synthetic NDVI images captured seasonal land surface dynamics and maintained the spatial structure of the landscape at higher spatial resolution. The time series of synthetic medium-resolution NDVI images were validated within a Monte Carlo simulation framework. Normalized residuals decreased as the number of available observations increased, ranging from 0.2 to below 0.1. Residuals were also significantly lower for time series of synthetic NDVI images generated at combined recursion (smoothing than individually at forward and backward recursions (filtering. Conversely, the uncertainties of the synthetic images also decreased when the number of available observations increased and combined recursions were implemented.

GPS Interference Mitigation Using Derivative-free Kalman Filter-based RNN

Directory of Open Access Journals (Sweden)

W. L. Mao

2016-09-01

Full Text Available The global positioning system (GPS with accurate positioning and timing properties has become integral part of all applications around the world. Radio frequency interference can significantly decrease the performance of GPS receivers or even completely prohibit the acquisition or tracking of satellites. The approaches of system performances that can be further enhanced by preprocessing to reject the jamming signal will be investigated. A recurrent neural network (RNN predictor for the GPS anti-jamming applications will be proposed. The adaptive RNN predictor is utilized to accurately predict the narrowband waveform based on an unscented Kalman filter (UKF-based algorithm. The UKF algorithm as a derivative-free alternative to the extended Kalman filter (EKF in the framework of state-estimation is adopted to achieve better performance in terms of convergence rate and quality of solution. The adaptive RNN filter can be successfully applied for the suppression of interference with a number of different narrowband formats, i.e. continuous wave interference (CWI, multi-tone CWI, swept CWI and pulsed CWI, to emulate realistic circumstances. Simulation results show that the proposed UKF-based scheme can offer the superior performances to suppress the interference over the conventional methods by computing mean squared prediction error (MSPE and signal-to-noise ratio (SNR improvements.

An effective method of surgical treatment of refractory glaucoma patients using Ex-PRESSTM filtering device

Directory of Open Access Journals (Sweden)

Sergey Yuryevich Astakhov

2013-03-01

Full Text Available Based on data obtained from examination and subsequent follow-up of 47 patients (50 eyes with refractory glaucoma, an efficacy estimation of a new method of the Ex-PRESSTM filtering device implantation was performed. The data analysis showed that the proposed surgical procedure has a low level of intra- and post-operative complications, is characterized by technical ease, and provides a long term stabilization of the glaucomatous process. Therefore it is possible to draw a conclusion that the Ex-PRESSTM filtering device implantation is an effective method for the treatment of refractory glaucoma.

A New Method for the Deposition of Metallic Silver on Porous Ceramic Water Filters

Directory of Open Access Journals (Sweden)

Kathryn N. Jackson

2018-01-01

Full Text Available A new method of silver application to a porous ceramic water filter used for point-of-use water treatment is developed. We evaluated filter performance for filters manufactured by the conventional method of painting an aqueous suspension of silver nanoparticles onto the filter and filters manufactured with a new method that applies silver nitrate to the clay-water-sawdust mixture prior to pressing and firing the filter. Filters were evaluated using miscible displacement flow-through experiments with pulse and continuous-feed injections of E. coli. Flow characteristics were quantified by tracer experiments using [3H]H2O. Experiments using pulse injections of E. coli showed similar performance in breakthrough curves between the two application methods. Long-term challenge tests performed with a continuous feed of E. coli and growth medium resulted in similar log removal rates, but the removal rate by nanosilver filters decreased over time. Silver nitrate filters provided consistent removal with lower silver levels in the effluent and effective bacterial disinfection. Results from continued use with synthetic groundwater over 4 weeks, with a pulse injection of E. coli at 2 and 4 weeks, support similar conclusions—nanosilver filters perform better initially, but after 4 weeks of use, nanosilver filters suffer larger decreases in performance. Results show that including silver nitrate in the mixing step may effectively reduce costs, improve silver retention in the filter, increase effective lifespan, and maintain effective pathogen removal while also eliminating the risk of exposure to inhalation of silver nanoparticles by workers in developing-world filter production facilities.

Data assimilation method for fractured reservoirs using mimetic finite differences and ensemble Kalman filter

KAUST Repository

Ping, Jing; Al-Hinai, Omar; Wheeler, Mary F.

2017-01-01

-Gaussian in this case, it is a challenge to estimate fracture distributions by conventional history matching approaches. In this work, a method that combines vector-based level-set parameterization technique and ensemble Kalman filter (EnKF) for estimating fracture

Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems

Directory of Open Access Journals (Sweden)

Min Chul Kim

2011-10-01

Full Text Available Recently, the range of available Radio Frequency Identification (RFID tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.

Science.gov (United States)

Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

2011-01-01

Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less mean squared error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

Designing metallic iron based water filters: Light from methylene blue discoloration.

Science.gov (United States)

Btatkeu-K, B D; Tchatchueng, J B; Noubactep, C; Caré, S

2016-01-15

Available water filtration systems containing metallic iron (Fe(0) filters) are pragmatically designed. There is a lack of sound design criteria to exploit the full potential of Fe(0) filters. A science-based design relies on valuable information on processes within a Fe(0) filter, including chemical reactions, hydrodynamics and their relation to the performance of the filter. The aim of this study was to establish a simple method to evaluate the initial performance of Fe(0) filters. The differential adsorptive affinity of methylene blue (MB) onto sand and iron oxide is exploited to characterize the evolution of a Fe(0)/sand system using the pure sand system as operational reference. Five systems were investigated for more than 70 days: pure sand, pure Fe(0), Fe(0)/sand, Fe(0)/pumice and Fe(0)/sand/pumice. Individual systems were characterized by the extent of changes in pH value, iron breakthrough, MB breakthrough and hydraulic conductivity. Results showed that for MB discoloration (i) pure sand was the most efficient system, (ii) hybrid systems were more sustainable than the pure Fe(0) system, and (iii) the pores of used pumice are poorly interconnected. Characterizing the initial reactivity of Fe(0) filters using MB discoloration has introduced a powerful tool for the exploration of various aspects of filter design. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters.

Science.gov (United States)

Song, Jin Woo; Park, Chan Gook

2018-04-21

An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms.

Angular filter refractometry analysis using simulated annealing [An improved method for characterizing plasma density profiles using angular filter refractometry

International Nuclear Information System (INIS)

Angland, P.; Haberberger, D.; Ivancic, S. T.; Froula, D. H.

2017-01-01

Here, a new method of analysis for angular filter refractometry images was developed to characterize laser-produced, long-scale-length plasmas using an annealing algorithm to iterative converge upon a solution. Angular filter refractometry (AFR) is a novel technique used to characterize the density pro files of laser-produced, long-scale-length plasmas. A synthetic AFR image is constructed by a user-defined density profile described by eight parameters, and the algorithm systematically alters the parameters until the comparison is optimized. The optimization and statistical uncertainty calculation is based on a minimization of the χ2 test statistic. The algorithm was successfully applied to experimental data of plasma expanding from a flat, laser-irradiated target, resulting in average uncertainty in the density profile of 5-10% in the region of interest.

An improved three-dimension reconstruction method based on guided filter and Delaunay

Science.gov (United States)

Liu, Yilin; Su, Xiu; Liang, Haitao; Xu, Huaiyuan; Wang, Yi; Chen, Xiaodong

2018-01-01

Binocular stereo vision is becoming a research hotspot in the area of image processing. Based on traditional adaptive-weight stereo matching algorithm, we improve the cost volume by averaging the AD (Absolute Difference) of RGB color channels and adding x-derivative of the grayscale image to get the cost volume. Then we use guided filter in the cost aggregation step and weighted median filter for post-processing to address the edge problem. In order to get the location in real space, we combine the deep information with the camera calibration to project each pixel in 2D image to 3D coordinate matrix. We add the concept of projection to region-growing algorithm for surface reconstruction, its specific operation is to project all the points to a 2D plane through the normals of clouds and return the results back to 3D space according to these connection relationship among the points in 2D plane. During the triangulation in 2D plane, we use Delaunay algorithm because it has optimal quality of mesh. We configure OpenCV and pcl on Visual Studio for testing, and the experimental results show that the proposed algorithm have higher computational accuracy of disparity and can realize the details of the real mesh model.

pyAmpli: an amplicon-based variant filter pipeline for targeted resequencing data.

Science.gov (United States)

Beyens, Matthias; Boeckx, Nele; Van Camp, Guy; Op de Beeck, Ken; Vandeweyer, Geert

2017-12-14

Haloplex targeted resequencing is a popular method to analyze both germline and somatic variants in gene panels. However, involved wet-lab procedures may introduce false positives that need to be considered in subsequent data-analysis. No variant filtering rationale addressing amplicon enrichment related systematic errors, in the form of an all-in-one package, exists to our knowledge. We present pyAmpli, a platform independent parallelized Python package that implements an amplicon-based germline and somatic variant filtering strategy for Haloplex data. pyAmpli can filter variants for systematic errors by user pre-defined criteria. We show that pyAmpli significantly increases specificity, without reducing sensitivity, essential for reporting true positive clinical relevant mutations in gene panel data. pyAmpli is an easy-to-use software tool which increases the true positive variant call rate in targeted resequencing data. It specifically reduces errors related to PCR-based enrichment of targeted regions.

Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics.

Directory of Open Access Journals (Sweden)

Wan Yang

2014-04-01

Full Text Available A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.. Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters--a basic particle filter (PF with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF, and particle Markov chain Monte Carlo (pMCMC--and three ensemble filters--the ensemble Kalman filter (EnKF, the ensemble adjustment Kalman filter (EAKF, and the rank histogram filter (RHF--were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003-2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable; the three particle filters perform slightly better predicting peaks 1-5 weeks in the future; the ensemble filters are more accurate predicting peaks in

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.

Fast filtering algorithm based on vibration systems and neural information exchange and its application to micro motion robot

International Nuclear Information System (INIS)

Gao Wa; Zha Fu-Sheng; Li Man-Tian; Song Bao-Yu

2014-01-01

This paper develops a fast filtering algorithm based on vibration systems theory and neural information exchange approach. The characters, including the derivation process and parameter analysis, are discussed and the feasibility and the effectiveness are testified by the filtering performance compared with various filtering methods, such as the fast wavelet transform algorithm, the particle filtering method and our previously developed single degree of freedom vibration system filtering algorithm, according to simulation and practical approaches. Meanwhile, the comparisons indicate that a significant advantage of the proposed fast filtering algorithm is its extremely fast filtering speed with good filtering performance. Further, the developed fast filtering algorithm is applied to the navigation and positioning system of the micro motion robot, which is a high real-time requirement for the signals preprocessing. Then, the preprocessing data is used to estimate the heading angle error and the attitude angle error of the micro motion robot. The estimation experiments illustrate the high practicality of the proposed fast filtering algorithm. (general)

Leak detection of complex pipelines based on the filter diagonalization method: robust technique for eigenvalue assessment

International Nuclear Information System (INIS)

Lay-Ekuakille, Aimé; Pariset, Carlo; Trotta, Amerigo

2010-01-01

The FDM (filter diagonalization method), an interesting technique used in nuclear magnetic resonance data processing for tackling FFT (fast Fourier transform) limitations, can be used by considering pipelines, especially complex configurations, as a vascular apparatus with arteries, veins, capillaries, etc. Thrombosis, which might occur in humans, can be considered as a leakage for the complex pipeline, the human vascular apparatus. The choice of eigenvalues in FDM or in spectra-based techniques is a key issue in recovering the solution of the main equation (for FDM) or frequency domain transformation (for FFT) in order to determine the accuracy in detecting leaks in pipelines. This paper deals with the possibility of improving the leak detection accuracy of the FDM technique thanks to a robust algorithm by assessing the problem of eigenvalues, making it less experimental and more analytical using Tikhonov-based regularization techniques. The paper starts from the results of previous experimental procedures carried out by the authors

Multiple HEPA filter test methods, January--December 1976

International Nuclear Information System (INIS)

Schuster, B.; Kyle, T.; Osetek, D.

1977-06-01

The testing of tandem high-efficiency particulate air (HEPA) filter systems is of prime importance for the measurement of accurate overall system protection factors. A procedure, based on the use of an intra-cavity laser particle spectrometer, has been developed for measuring protection factors in the 10 8 range. A laboratory scale model of a filter system was constructed and initially tested to determine individual HEPA filter characteristics with regard to size and state (liquid or solid) of several test aerosols. Based on these laboratory measurements, in-situ testing has been successfully conducted on a number of single and tandem filter installations within the Los Alamos Scientific Laboratory as well as on extraordinary large single systems at Rocky Flats. For the purpose of recovery and for simplified solid waste disposal, or prefiltering purposes, two versions of an inhomogeneous electric field air cleaner have been devised and are undergoing testing. Initial experience with one of the systems, which relies on an electrostatic spraying phenomenon, indicates performance efficiency of greater than 99.9% for flow velocities commonly used in air cleaning systems. Among the effluents associated with nuclear fuel reprocessing is 129 I. An intra-cavity laser detection system is under development which shows promise of being able to detect mixing ratios of one part in 10 7 , I 2 in air

Two-Level Chebyshev Filter Based Complementary Subspace Method: Pushing the Envelope of Large-Scale Electronic Structure Calculations.

Science.gov (United States)

Banerjee, Amartya S; Lin, Lin; Suryanarayana, Phanish; Yang, Chao; Pask, John E

2018-06-12

We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).

Complete filter-based cerebral embolic protection with transcatheter aortic valve replacement.

Science.gov (United States)

Van Gils, Lennart; Kroon, Herbert; Daemen, Joost; Ren, Claire; Maugenest, Anne-Marie; Schipper, Marguerite; De Jaegere, Peter P; Van Mieghem, Nicolas M

2018-03-01

To evaluate the value of left vertebral artery filter protection in addition to the current filter-based embolic protection technology to achieve complete cerebral protection during TAVR. The occurrence of cerebrovascular events after transcatheter aortic valve replacement (TAVR) has fueled concern for its potential application in younger patients with longer life expectancy. Transcatheter cerebral embolic protection (TCEP) devices may limit periprocedural cerebrovascular events by preventing macro and micro-embolization to the brain. Conventional filter-based TCEP devices cover three extracranial contributories to the brain, yet leave the left vertebral artery unprotected. Patients underwent TAVR with complete TCEP. A dual-filter system was deployed in the brachiocephalic trunk and left common carotid artery with an additional single filter in the left vertebral artery. After TAVR all filters were retrieved and sent for histopathological evaluation by an experienced pathologist. Eleven patients received a dual-filter system and nine of them received an additional left vertebral filter. In the remaining two patients, the left vertebral filter could not be deployed. No periprocedural strokes occurred. We found debris in all filters, consisting of thrombus, tissue derived debris, and foreign body material. The left vertebral filter contained debris in an equal amount of patients as the Sentinel filters. The size of the captured particles was similar between all filters. The left vertebral artery is an important entry route for embolic material to the brain during TAVR. Selective filter protection of the left vertebral artery revealed embolic debris in all patients. The clinical value of complete filter-based TCEP during TAVR warrants further research. © 2017 Wiley Periodicals, Inc.

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.

Feasibility Studies of the Two Filters Method in TJ-II for Electron Temperature Measurements in High Density Plasmas

International Nuclear Information System (INIS)

Baiao, D.; Medina, F.; Ochando, M.; Varandas, C.

2009-01-01

The TJ-II plasma soft X-ray emission was studied in order to establish an adequate setup for an electron temperature diagnostic suitable for high density, with spatial and temporal resolutions, based on the two-filters method. The preliminary experimental results reported were obtained with two diagnostics (an X-ray PHA based on a Ge detector and a tomography system) already installed in TJ-II stellarator. These results lead to the conclusion that the two-filters method was a suitable option for an electron temperature diagnostic for high-density plasmas in TJ-II. We present the design and fi rst results obtained with a prototype for the measurement of electron temperature in TJ-II plasmas heated with energetic neutral beams. This system consists in two AXUV20A detectors which measure the soft X-ray plasma emissivity trough beryllium filters of different thickness. From the two-filters technique it is possible to estimate the electron temperature. The analyses carried out allowed concluding which filter thicknesses are most suited for TJ-II plasmas, and enhanced the need of a computer code to simulate signals and plasma compositions. (Author) 7 refs.

Feasibility Studies of the Two Filters Method in TJ-II for Electron Temperature Measurements in High Density Plasmas

Energy Technology Data Exchange (ETDEWEB)

Baiao, D.; Medina, F.; Ochando, M.; Varandas, C.

2009-07-01

The TJ-II plasma soft X-ray emission was studied in order to establish an adequate setup for an electron temperature diagnostic suitable for high density, with spatial and temporal resolutions, based on the two-filters method. The preliminary experimental results reported were obtained with two diagnostics (an X-ray PHA based on a Ge detector and a tomography system) already installed in TJ-II stellarator. These results lead to the conclusion that the two-filters method was a suitable option for an electron temperature diagnostic for high-density plasmas in TJ-II. We present the design and fi rst results obtained with a prototype for the measurement of electron temperature in TJ-II plasmas heated with energetic neutral beams. This system consists in two AXUV20A detectors which measure the soft X-ray plasma emissivity trough beryllium filters of different thickness. From the two-filters technique it is possible to estimate the electron temperature. The analyses carried out allowed concluding which filter thicknesses are most suited for TJ-II plasmas, and enhanced the need of a computer code to simulate signals and plasma compositions. (Author) 7 refs.

Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter

International Nuclear Information System (INIS)

Son, Junbo; Zhou, Shiyu; Sankavaram, Chaitanya; Du, Xinyu; Zhang, Yilu

2016-01-01

In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. - Highlights: • A computationally efficient constrained Kalman filter is proposed. • Proposed filter is integrated into an online failure prognosis framework. • A set of proper constraints significantly improves the failure prediction accuracy. • Promising results are reported in the application of battery failure prognosis.

Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

KAUST Repository

Luo, Xiaodong

2011-12-01

A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used in the Kalman filter. By design, the H∞ filter is more robust than the Kalman filter, in the sense that the estimation error in the H∞ filter in general has a finite growth rate with respect to the uncertainties in assimilation, except for a special case that corresponds to the Kalman filter. The original form of the H∞ filter contains global constraints in time, which may be inconvenient for sequential data assimilation problems. Therefore a variant is introduced that solves some time-local constraints instead, and hence it is called the time-local H∞ filter (TLHF). By analogy to the ensemble Kalman filter (EnKF), the concept of ensemble time-local H∞ filter (EnTLHF) is also proposed. The general form of the EnTLHF is outlined, and some of its special cases are discussed. In particular, it is shown that an EnKF with certain covariance inflation is essentially an EnTLHF. In this sense, the EnTLHF provides a general framework for conducting covariance inflation in the EnKF-based methods. Some numerical examples are used to assess the relative robustness of the TLHF–EnTLHF in comparison with the corresponding KF–EnKF method.

Towards effective and robust list-based packet filter for signature-based network intrusion detection: an engineering approach

DEFF Research Database (Denmark)

Meng, Weizhi; Li, Wenjuan; Kwok, Lam For

2017-01-01

Network intrusion detection systems (NIDSs) which aim to identify various attacks, have become an essential part of current security infrastructure. In particular, signature-based NIDSs are being widely implemented in industry due to their low rate of false alarms. However, the signature matching...... this problem, packet filtration is a promising solution to reduce unwanted traffic. Motivated by this, in this work, a list-based packet filter was designed and an engineering method of combining both blacklist and whitelist techniques was introduced. To further secure such filters against IP spoofing attacks...... in traffic filtration as well as workload reduction, and is robust against IP spoofing attacks....

All-Pole Recursive Digital Filters Design Based on Ultraspherical Polynomials

Directory of Open Access Journals (Sweden)

N. Stojanovic

2014-09-01

Full Text Available A simple method for approximation of all-pole recursive digital filters, directly in digital domain, is described. Transfer function of these filters, referred to as Ultraspherical filters, is controlled by order of the Ultraspherical polynomial, nu. Parameter nu, restricted to be a nonnegative real number (nu ≥ 0, controls ripple peaks in the passband of the magnitude response and enables a trade-off between the passband loss and the group delay response of the resulting filter. Chebyshev filters of the first and of the second kind, and also Legendre and Butterworth filters are shown to be special cases of these allpole recursive digital filters. Closed form equations for the computation of the filter coefficients are provided. The design technique is illustrated with examples.

Biogas Filter Based on Local Natural Zeolite Materials

OpenAIRE

Krido Wahono, Satriyo; Anggo Rizal, Wahyu

2014-01-01

UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as ...

Electrically heated particulate filter regeneration methods and systems for hybrid vehicles

Science.gov (United States)

Gonze, Eugene V.; Paratore, Jr., Michael J.

2010-10-12

A control system for controlling regeneration of a particulate filter for a hybrid vehicle is provided. The system generally includes a regeneration module that controls current to the particulate filter to initiate regeneration. An engine control module controls operation of an engine of the hybrid vehicle based on the control of the current to the particulate filter.

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.

Proposing Wavelet-Based Low-Pass Filter and Input Filter to Improve Transient Response of Grid-Connected Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Bijan Rahmani

2016-08-01

Full Text Available Available photovoltaic (PV systems show a prolonged transient response, when integrated into the power grid via active filters. On one hand, the conventional low-pass filter, employed within the integrated PV system, works with a large delay, particularly in the presence of system’s low-order harmonics. On the other hand, the switching of the DC (direct current–DC converters within PV units also prolongs the transient response of an integrated system, injecting harmonics and distortion through the PV-end current. This paper initially develops a wavelet-based low-pass filter to improve the transient response of the interconnected PV systems to grid lines. Further, a damped input filter is proposed within the PV system to address the raised converter’s switching issue. Finally, Matlab/Simulink simulations validate the effectiveness of the proposed wavelet-based low-pass filter and damped input filter within an integrated PV system.

Low-power adaptive filter based on RNS components

DEFF Research Database (Denmark)

Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Del Re, Andrea

2007-01-01

In this paper a low-power implementation of an adaptive FIR filter is presented. The filter is designed to meet the constraints of channel equalization for fixed wireless communications that typically requires a large number of taps, but a serial updating of the filter coefficients, based...... on the least mean squares (LMS) algorithm, is allowed. Previous work showed that the use of the residue number system (RNS) for the variable FIR filter grants advantages both in area and power consumption. On the other hand, the use of a binary serial implementation of the adaptation algorithm eliminates...... the need for complex scaling circuits in RNS. The advantages in terms of area and speed of the presented filter, with respect to its two's complement counterpart, are evaluated for implementations in standard cells....

Cooperative Localization for Multi-AUVs Based on GM-PHD Filters and Information Entropy Theory

Directory of Open Access Journals (Sweden)

Lichuan Zhang

2017-10-01

Full Text Available Cooperative localization (CL is considered a promising method for underwater localization with respect to multiple autonomous underwater vehicles (multi-AUVs. In this paper, we proposed a CL algorithm based on information entropy theory and the probability hypothesis density (PHD filter, aiming to enhance the global localization accuracy of the follower. In the proposed framework, the follower carries lower cost navigation systems, whereas the leaders carry better ones. Meanwhile, the leaders acquire the followers’ observations, including both measurements and clutter. Then, the PHD filters are utilized on the leaders and the results are communicated to the followers. The followers then perform weighted summation based on all received messages and obtain a final positioning result. Based on the information entropy theory and the PHD filter, the follower is able to acquire a precise knowledge of its position.

Adaptive Filtering Using Recurrent Neural Networks

Science.gov (United States)

Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.

2005-01-01

A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

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.

Passivity-based design of robust passive damping for LCL-filtered voltage source converters

DEFF Research Database (Denmark)

Wang, Xiongfei; Blaabjerg, Frede; Loh, Poh Chiang

2015-01-01

Passive damping is proven as a robust stabilizing technique for LCL-filtered voltage source converters. However, conventional design methods of passive dampers are based on the passive components only, while the inherent damping effect of time delay in the digital control system is overlooked....... In this paper, a frequency-domain passivity-based design approach is proposed, where the passive dampers are designed to eliminate the negative real part of the converter output admittance with closed-loop current control, rather than shaping the LCL-filter itself. Thus, the influence of time delay...... in the current control is included, which allows a relaxed design of the passive damper with the reduced power loss and improved stability robustness against grid parameters variations. Design procedures of two commonly used passive dampers with LCL-filtered VSCs are illustrated. Experimental results validate...

Characteristics of BeiDou Navigation Satellite System Multipath and Its Mitigation Method Based on Kalman Filter and Rauch-Tung-Striebel Smoother.

Science.gov (United States)

Zhang, Qiuzhao; Yang, Wei; Zhang, Shubi; Liu, Xin

2018-01-12

Global Navigation Satellite System (GNSS) carrier phase measurement for short baseline meets the requirements of deformation monitoring of large structures. However, the carrier phase multipath effect is the main error source with double difference (DD) processing. There are lots of methods to deal with the multipath errors of Global Position System (GPS) carrier phase data. The BeiDou navigation satellite System (BDS) multipath mitigation is still a research hotspot because the unique constellation design of BDS makes it different to mitigate multipath effects compared to GPS. Multipath error periodically repeats for its strong correlation to geometry of satellites, reflective surface and antenna which is also repetitive. We analyzed the characteristics of orbital periods of BDS satellites which are consistent with multipath repeat periods of corresponding satellites. The results show that the orbital periods and multipath periods for BDS geostationary earth orbit (GEO) and inclined geosynchronous orbit (IGSO) satellites are about one day but the periods of MEO satellites are about seven days. The Kalman filter (KF) and Rauch-Tung-Striebel Smoother (RTSS) was introduced to extract the multipath models from single difference (SD) residuals with traditional sidereal filter (SF). Wavelet filter and Empirical mode decomposition (EMD) were also used to mitigate multipath effects. The experimental results show that the three filters methods all have obvious effect on improvement of baseline accuracy and the performance of KT-RTSS method is slightly better than that of wavelet filter and EMD filter. The baseline vector accuracy on east, north and up (E, N, U) components with KF-RTSS method were improved by 62.8%, 63.6%, 62.5% on day of year 280 and 57.3%, 53.4%, 55.9% on day of year 281, respectively.

Characteristics of BeiDou Navigation Satellite System Multipath and Its Mitigation Method Based on Kalman Filter and Rauch-Tung-Striebel Smoother

Directory of Open Access Journals (Sweden)

Qiuzhao Zhang

2018-01-01

Full Text Available Global Navigation Satellite System (GNSS carrier phase measurement for short baseline meets the requirements of deformation monitoring of large structures. However, the carrier phase multipath effect is the main error source with double difference (DD processing. There are lots of methods to deal with the multipath errors of Global Position System (GPS carrier phase data. The BeiDou navigation satellite System (BDS multipath mitigation is still a research hotspot because the unique constellation design of BDS makes it different to mitigate multipath effects compared to GPS. Multipath error periodically repeats for its strong correlation to geometry of satellites, reflective surface and antenna which is also repetitive. We analyzed the characteristics of orbital periods of BDS satellites which are consistent with multipath repeat periods of corresponding satellites. The results show that the orbital periods and multipath periods for BDS geostationary earth orbit (GEO and inclined geosynchronous orbit (IGSO satellites are about one day but the periods of MEO satellites are about seven days. The Kalman filter (KF and Rauch-Tung-Striebel Smoother (RTSS was introduced to extract the multipath models from single difference (SD residuals with traditional sidereal filter (SF. Wavelet filter and Empirical mode decomposition (EMD were also used to mitigate multipath effects. The experimental results show that the three filters methods all have obvious effect on improvement of baseline accuracy and the performance of KT-RTSS method is slightly better than that of wavelet filter and EMD filter. The baseline vector accuracy on east, north and up (E, N, U components with KF-RTSS method were improved by 62.8%, 63.6%, 62.5% on day of year 280 and 57.3%, 53.4%, 55.9% on day of year 281, respectively.

Graphene-based tunable terahertz filter with rectangular ring ...

Indian Academy of Sciences (India)

A plasmonic band-pass filter based on graphene rectangular ring resonator with double narrow gaps is proposed and numerically investigated by finite-difference time-domain (FDTD) simulations. For the filter with or without gaps, the resonant frequencies can be effectively adjusted by changing the width of the graphene ...

Graphene-based tunable terahertz filter with rectangular ring ...

Indian Academy of Sciences (India)

WEI SU

2017-08-16

Aug 16, 2017 ... Abstract. A plasmonic band-pass filter based on graphene rectangular ring resonator with double narrow gaps is proposed and numerically investigated by finite-difference time-domain (FDTD) simulations. For the filter with or without gaps, the resonant frequencies can be effectively adjusted by changing ...

Method and means for filtering polychlorinated biphenyls from a gas stream

International Nuclear Information System (INIS)

Sowinski, R.F.

1992-01-01

This patent describes a method of filtering, adjacent to an end user-customer's residence or business in which at least a single gas appliance is located, a natural gas stream in which polychlorinated biphenyls (PCB's) and degraded PCB products have been concentrated at sufficient levels to be a health threat in a natural gas gathering and distributing network. It comprises: introducing the natural gas stream to a filter selected from a group that includes impingement, absorbing and adsorbing media whereby PCB's and degraded PCB products concentrated in the gas stream at sufficient levels to be a health threat by a periodic loading of the natural gas within the gathering and distributing network, are filtered from the gas stream and captured irrespective of mode of transport, passing the filtered natural gas stream to the customer's gas appliance wherein safe use of the energy associated with the stream occurs; periodically and safely removing the filter, inserting a new filter in place of the removed filter

Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

Science.gov (United States)

Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

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.

Filter optimization of Si and SiC semiconductor-based H5 and Conergy-NPC transformerless PV inverters

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

Single-phase transformerless Photovoltaic (PV) inverters are synthesized by combining available solutions in terms of the power section topology, power semiconductors manufacturing technology and structure of the output filter. A design method is presented in this paper for optimizing the power......C-based PV inverters will inject more energy into the electric grid, compared to the Si-based structures and enable the reduction of the output filter size, weight and cost. Employing an LLCL-type output filter and simultaneously reducing the cost of SiC power semiconductors to the level of their Si...

Research on signal processing of shock absorber test bench based on zero-phase filter

Science.gov (United States)

Wu, Yi; Ding, Guoqing

2017-10-01

The quality of force-displacement diagram is significant to help evaluate the performance of shock absorbers. Damping force sampling data is often interfered by Gauss white noise, 50Hz power interference and its harmonic wave during the process of testing; data de-noising has become the core problem of drawing true, accurate and real-time indicator diagram. The noise and interference can be filtered out through generic IIR or FIR low-pass filter, but addition phase lag of useful signal will be caused due to the inherent attribute of IIR and FIR filter. The paper uses FRR method to realize zero-phase digital filtering in a software way based on mutual cancellation of phase lag between the forward and reverse sequences after through the filter. High-frequency interference above 40Hz are filtered out completely and noise attenuation is more than -40dB, with no additional phase lag. The method is able to restore the true signal as far as possible. Theoretical simulation and practical test indicate high-frequency noises have been effectively inhibited in multiple typical speed cases, signal-to-noise ratio being greatly improved; the curve in indicator diagram has better smoothness and fidelity. The FRR algorithm has low computational complexity, fast running time, and can be easily transplanted in multiple platforms.

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.

Gas Path Health Monitoring for a Turbofan Engine Based on a Nonlinear Filtering Approach

Directory of Open Access Journals (Sweden)

Yiqiu Lv

2013-01-01

Full Text Available Different approaches for gas path performance estimation of dynamic systems are commonly used, the most common being the variants of the Kalman filter. The extended Kalman filter (EKF method is a popular approach for nonlinear systems which combines the traditional Kalman filtering and linearization techniques to effectively deal with weakly nonlinear and non-Gaussian problems. Its mathematical formulation is based on the assumption that the probability density function (PDF of the state vector can be approximated to be Gaussian. Recent investigations have focused on the particle filter (PF based on Monte Carlo sampling algorithms for tackling strong nonlinear and non-Gaussian models. Considering the aircraft engine is a complicated machine, operating under a harsh environment, and polluted by complex noises, the PF might be an available way to monitor gas path health for aircraft engines. Up to this point in time a number of Kalman filtering approaches have been used for aircraft turbofan engine gas path health estimation, but the particle filters have not been used for this purpose and a systematic comparison has not been published. This paper presents gas path health monitoring based on the PF and the constrained extend Kalman particle filter (cEKPF, and then compares the estimation accuracy and computational effort of these filters to the EKF for aircraft engine performance estimation under rapid faults and general deterioration. Finally, the effects of the constraint mechanism and particle number on the cEKPF are discussed. We show in this paper that the cEKPF outperforms the EKF, PF and EKPF, and conclude that the cEKPF is the best choice for turbofan engine health monitoring.

All-Pole Recursive Digital Filters Design Based on Ultraspherical Polynomials

OpenAIRE

N. Stojanovic; N. Stamenkovic; V. Stojanovic

2014-01-01

A simple method for approximation of all-pole recursive digital filters, directly in digital domain, is described. Transfer function of these filters, referred to as Ultraspherical filters, is controlled by order of the Ultraspherical polynomial, nu. Parameter nu, restricted to be a nonnegative real number (nu ≥ 0), controls ripple peaks in the passband of the magnitude response and enables a trade-off between the passband loss and the group delay response of the resulting filter. Chebyshev f...

A Matrix-Free Posterior Ensemble Kalman Filter Implementation Based on a Modified Cholesky Decomposition

Directory of Open Access Journals (Sweden)

Elias D. Nino-Ruiz

2017-07-01

Full Text Available In this paper, a matrix-free posterior ensemble Kalman filter implementation based on a modified Cholesky decomposition is proposed. The method works as follows: the precision matrix of the background error distribution is estimated based on a modified Cholesky decomposition. The resulting estimator can be expressed in terms of Cholesky factors which can be updated based on a series of rank-one matrices in order to approximate the precision matrix of the analysis distribution. By using this matrix, the posterior ensemble can be built by either sampling from the posterior distribution or using synthetic observations. Furthermore, the computational effort of the proposed method is linear with regard to the model dimension and the number of observed components from the model domain. Experimental tests are performed making use of the Lorenz-96 model. The results reveal that, the accuracy of the proposed implementation in terms of root-mean-square-error is similar, and in some cases better, to that of a well-known ensemble Kalman filter (EnKF implementation: the local ensemble transform Kalman filter. In addition, the results are comparable to those obtained by the EnKF with large ensemble sizes.

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

Science.gov (United States)

Winkler, Irene; Debener, Stefan; Müller, Klaus-Robert; Tangermann, Michael

2015-01-01

Standard artifact removal methods for electroencephalographic (EEG) signals are either based on Independent Component Analysis (ICA) or they regress out ocular activity measured at electrooculogram (EOG) channels. Successful ICA-based artifact reduction relies on suitable pre-processing. Here we systematically evaluate the effects of high-pass filtering at different frequencies. Offline analyses were based on event-related potential data from 21 participants performing a standard auditory oddball task and an automatic artifactual component classifier method (MARA). As a pre-processing step for ICA, high-pass filtering between 1-2 Hz consistently produced good results in terms of signal-to-noise ratio (SNR), single-trial classification accuracy and the percentage of `near-dipolar' ICA components. Relative to no artifact reduction, ICA-based artifact removal significantly improved SNR and classification accuracy. This was not the case for a regression-based approach to remove EOG artifacts.

Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide

DEFF Research Database (Denmark)

Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui

2016-01-01

Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN and satel......Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...

[Research on engine remaining useful life prediction based on oil spectrum analysis and particle filtering].

Science.gov (United States)

Sun, Lei; Jia, Yun-xian; Cai, Li-ying; Lin, Guo-yu; Zhao, Jin-song

2013-09-01

The spectrometric oil analysis(SOA) is an important technique for machine state monitoring, fault diagnosis and prognosis, and SOA based remaining useful life(RUL) prediction has an advantage of finding out the optimal maintenance strategy for machine system. Because the complexity of machine system, its health state degradation process can't be simply characterized by linear model, while particle filtering(PF) possesses obvious advantages over traditional Kalman filtering for dealing nonlinear and non-Gaussian system, the PF approach was applied to state forecasting by SOA, and the RUL prediction technique based on SOA and PF algorithm is proposed. In the prediction model, according to the estimating result of system's posterior probability, its prior probability distribution is realized, and the multi-step ahead prediction model based on PF algorithm is established. Finally, the practical SOA data of some engine was analyzed and forecasted by the above method, and the forecasting result was compared with that of traditional Kalman filtering method. The result fully shows the superiority and effectivity of the

The overview of damping methods for three-phase grid-tied inverter with LLCL-filter

DEFF Research Database (Denmark)

Huang, Min; Blaabjerg, Frede; Loh, Poh Chiang

2014-01-01

Compared with LCL filter, an LLCL-filter is characterized with smaller size and lower cost for grid-connected inverters. But this high order filter may also have resonant problem which will affect the system stability. Many methods can be used to alleviate the resonant problem including active da...... and shows the advantages as well as disadvantages of these methods....

Autonomous Navigation for Autonomous Underwater Vehicles Based on Information Filters and Active Sensing

Directory of Open Access Journals (Sweden)

Tianhong Yan

2011-11-01

Full Text Available This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM, and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China. Weak links in the information matrix in an extended information filter (EIF can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM. All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM.

Autonomous navigation for autonomous underwater vehicles based on information filters and active sensing.

Science.gov (United States)

He, Bo; Zhang, Hongjin; Li, Chao; Zhang, Shujing; Liang, Yan; Yan, Tianhong

2011-01-01

This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China). Weak links in the information matrix in an extended information filter (EIF) can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM). All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM.

Low Power Systolic Array Based Digital Filter for DSP Applications

Directory of Open Access Journals (Sweden)

S. Karthick

2015-01-01

Full Text Available Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.

Ultrasonic computerized tomography (CT) for temperature measurements with limited projection data based on extrapolated filtered back projection (FBP) method

International Nuclear Information System (INIS)

Zhu Ning; Jiang Yong; Kato, Seizo

2005-01-01

This study uses ultrasound in combination with tomography to obtain three-dimensional temperature measurements using projection data obtained from limited projection angle. The main feature of the new computerized tomography (CT) reconstruction algorithm is to employ extrapolation scheme to make up for the incomplete projection data, it is based on the conventional filtered back projection (FBP) method while on top of that taking into account the correlation between the projection data and Fourier transform-based extrapolation. Computer simulation is conducted to verify the above algorithm. An experimental 3D temperature distribution measurement is also carried out to validate the proposed algorithm. The simulation and experimental results demonstrate that the extrapolated FBP CT algorithm is highly effective in dealing with projection data from limited projection angle

[Design Method Analysis and Performance Comparison of Wall Filter for Ultrasound Color Flow Imaging].

Science.gov (United States)

Wang, Lutao; Xiao, Jun; Chai, Hua

2015-08-01

The successful suppression of clutter arising from stationary or slowly moving tissue is one of the key issues in medical ultrasound color blood imaging. Remaining clutter may cause bias in the mean blood frequency estimation and results in a potentially misleading description of blood-flow. In this paper, based on the principle of general wall-filter, the design process of three classes of filters, infinitely impulse response with projection initialization (Prj-IIR), polynomials regression (Pol-Reg), and eigen-based filters are previewed and analyzed. The performance of the filters was assessed by calculating the bias and variance of a mean blood velocity using a standard autocorrelation estimator. Simulation results show that the performance of Pol-Reg filter is similar to Prj-IIR filters. Both of them can offer accurate estimation of mean blood flow speed under steady clutter conditions, and the clutter rejection ability can be enhanced by increasing the ensemble size of Doppler vector. Eigen-based filters can effectively remove the non-stationary clutter component, and further improve the estimation accuracy for low speed blood flow signals. There is also no significant increase in computation complexity for eigen-based filters when the ensemble size is less than 10.

Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.

Science.gov (United States)

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-11-30

Common spatial pattern (CSP) has been most popularly applied to motor-imagery (MI) feature extraction for classification in brain-computer interface (BCI) application. Successful application of CSP depends on the filter band selection to a large degree. However, the most proper band is typically subject-specific and can hardly be determined manually. This study proposes a sparse filter band common spatial pattern (SFBCSP) for optimizing the spatial patterns. SFBCSP estimates CSP features on multiple signals that are filtered from raw EEG data at a set of overlapping bands. The filter bands that result in significant CSP features are then selected in a supervised way by exploiting sparse regression. A support vector machine (SVM) is implemented on the selected features for MI classification. Two public EEG datasets (BCI Competition III dataset IVa and BCI Competition IV IIb) are used to validate the proposed SFBCSP method. Experimental results demonstrate that SFBCSP help improve the classification performance of MI. The optimized spatial patterns by SFBCSP give overall better MI classification accuracy in comparison with several competing methods. The proposed SFBCSP is a potential method for improving the performance of MI-based BCI. Copyright © 2015 Elsevier B.V. All rights reserved.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

Science.gov (United States)

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

2017-03-03

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Oblique Projection Polarization Filtering-Based Interference Suppressions for Radar Sensor Networks

Directory of Open Access Journals (Sweden)

Cao Bin

2010-01-01

Full Text Available The interferences coming from the radar members degrade the detection and recognition performance of the radar sensor networks (RSNs if the waveforms of the radar members are nonorthogonal. In this paper, we analyze the interferences by exploring the polarization information of the electromagnetic (EM waves. Then, we propose the oblique projection polarization filtering- (OPPF- based scheme to suppress the interferences while keeping the amplitude and phase of its own return in RSNs, even if the polarized states of the radar members are not orthogonal. We consider the cooperative RSNs environment where the polarization information of each radar member is known to all. The proposed method uses all radar members' polarization information to establish the corresponding filtering operator. The Doppler-shift and its uncertainty are independent of the polarization information, which contributes that the interferences can be suppressed without the utilization of the spatial, the temporal, the frequency, the time-delay and the Doppler-shift information. Theoretical analysis and the mathematical deduction show that the proposed scheme is a valid and simple implementation. Simulation results also demonstrate that this method can obtain a good filtering performance when dealing with the problem of interference suppressions for RSNs.

Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

Directory of Open Access Journals (Sweden)

Yanting Du

2018-02-01

Full Text Available In order to estimate the diesel particulate filter (DPF soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF. The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods.

Kalman Filtering with Real-Time Applications

CERN Document Server

Chui, Charles K

2009-01-01

Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering.

Transistor-based filter for inhibiting load noise from entering a power supply

Science.gov (United States)

Taubman, Matthew S

2013-07-02

A transistor-based filter for inhibiting load noise from entering a power supply is disclosed. The filter includes a first transistor having an emitter coupled to a power supply, a collector coupled to a load, and a base. The filter also includes a first capacitor coupled between the base of the first transistor and a ground terminal. The filter further includes an impedance coupled between the base and a node between the collector and the load, or a second transistor and second capacitor. The impedance can be a resistor or an inductor.

Exploring an optimal wavelet-based filter for cryo-ET imaging.

Science.gov (United States)

Huang, Xinrui; Li, Sha; Gao, Song

2018-02-07

Cryo-electron tomography (cryo-ET) is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures. However, cryo-ET imaging has two serious disadvantages-low dose and low image contrast-which result in high-resolution information being obscured by noise and image quality being degraded, and this causes errors in biological interpretation. The purpose of this research is to explore an optimal wavelet denoising technique to reduce noise in cryo-ET images. We perform tests using simulation data and design a filter using the optimum selected wavelet parameters (three-level decomposition, level-1 zeroed out, subband-dependent threshold, a soft-thresholding and spline-based discrete dyadic wavelet transform (DDWT)), which we call a modified wavelet shrinkage filter; this filter is suitable for noisy cryo-ET data. When testing using real cryo-ET experiment data, higher quality images and more accurate measures of a biological structure can be obtained with the modified wavelet shrinkage filter processing compared with conventional processing. Because the proposed method provides an inherent advantage when dealing with cryo-ET images, it can therefore extend the current state-of-the-art technology in assisting all aspects of cryo-ET studies: visualization, reconstruction, structural analysis, and interpretation.

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.

Use of wavelet based iterative filtering to improve denoising of spectral information for in-vivo gamma spectrometry

International Nuclear Information System (INIS)

Paul, Sabyasachi; Sarkar, P.K.

2012-05-01

The characterization of radionuclide in the in-vivo monitoring analysis using gamma spectrometry poses difficulty due to very low activity level in biological systems. The large statistical fluctuations often make identification of characteristic gammas from radionuclides highly uncertain, particularly when interferences from progenies are also present. A new wavelet based noise filtering methodology has been developed for better detection of gamma peaks while analyzing noisy spectrometric data. This sequential, iterative filtering method uses the wavelet multi-resolution approach for the noise rejection and inverse transform after soft thresholding over the generated coefficients. Analyses of in-vivo monitoring data of 235 U and 238 U have been carried out using this method without disturbing the peak position and amplitude while achieving a threefold improvement in the signal to noise ratio, compared to the original measured spectrum. When compared with other data filtering techniques, the wavelet based method shows better results. (author)

Method for Improving Indoor Positioning Accuracy Using Extended Kalman Filter

Directory of Open Access Journals (Sweden)

Seoung-Hyeon Lee

2016-01-01

Full Text Available Beacons using bluetooth low-energy (BLE technology have emerged as a new paradigm of indoor positioning service (IPS because of their advantages such as low power consumption, miniaturization, wide signal range, and low cost. However, the beacon performance is poor in terms of the indoor positioning accuracy because of noise, motion, and fading, all of which are characteristics of a bluetooth signal and depend on the installation location. Therefore, it is necessary to improve the accuracy of beacon-based indoor positioning technology by fusing it with existing indoor positioning technology, which uses Wi-Fi, ZigBee, and so forth. This study proposes a beacon-based indoor positioning method using an extended Kalman filter that recursively processes input data including noise. After defining the movement of a smartphone on a flat two-dimensional surface, it was assumed that the beacon signal is nonlinear. Then, the standard deviation and properties of the beacon signal were analyzed. According to the analysis results, an extended Kalman filter was designed and the accuracy of the smartphone’s indoor position was analyzed through simulations and tests. The proposed technique achieved good indoor positioning accuracy, with errors of 0.26 m and 0.28 m from the average x- and y-coordinates, respectively, based solely on the beacon signal.

Imaging reconstruction based on improved wavelet denoising combined with parallel-beam filtered back-projection algorithm

Science.gov (United States)

Ren, Zhong; Liu, Guodong; Huang, Zhen

2012-11-01

The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.

Simultaneous pattern recognition and track fitting by the Kalman filtering method

International Nuclear Information System (INIS)

Billoir, P.

1990-01-01

A progressive pattern recognition algorithm based on the Kalman filtering method has been tested. The algorithm starts from a small track segment or from a fitted track of a neighbouring detector, then extends the candidate tracks by adding measured points one by one. The fitted parameters and weight matrix of the candidate track are updated when adding a point, and give an increasing precision on prediction of the next point. Thus, pattern recognition and track fitting can be accomplished simultaneously. The method has been implemented and tested for track reconstruction for the vertex detector of the ZEUS experiment at DESY. Detailed procedures of the method and its performance are presented. Its flexibility is described as well. (orig.)

Inverse spiking filter based acquisition enhancement in software based global positioning system receiver

Directory of Open Access Journals (Sweden)

G. Arul Elango

2015-01-01

Full Text Available The lower visibility of the satellite in the acquisition stage of a GPS receiver under worst noisy situation leads to reacquisition of the data and thereby takes a longer time to obtain the first position fix. If the impulse noise affects the GPS signal, the conventional ways of acquiring the satellites do not guarantee to meet the minimum requirement of four satellites to find the user position. The performance of GPS receiver acquisition can be improved in the low SNR level using inverse spiking filtering technique. In the proposed method, the estimate of the desired GPS L1 signal corrupted by impulse noise (gn is obtained by the prediction error filter (hopt, which is the optimum inverse filter that reshapes the noisy signal (yn into a desired GPS signal (xn. In the proposed method, to detect the visible satellites under weak signal conditions the traditional differential coherent approach is combined with the inverse spiking filter method to increase the number of visible satellites and to avoid the reacquisition process. Montecarlo simulation is carried out to assess the performance of the proposed method for C/N0 of 20 dB-Hz and results indicate that the modified differential coherent method effectively excises the noise with 90% probability of detection. Subsequently tracking operation is also tested to confirm the acquisition performance by demodulating the navigation data successfully.

Bayesian signal processing classical, modern, and particle filtering methods

CERN Document Server

Candy, James V

2016-01-01

This book aims to give readers a unified Bayesian treatment starting from the basics (Baye's rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on "Sequential Bayesian Detection," a new section on "Ensemble Kalman Filters" as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to "fill-in-the gaps" of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical "sanity testing" lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed an...

Efficient OCT Image Enhancement Based on Collaborative Shock Filtering.

Science.gov (United States)

Liu, Guohua; Wang, Ziyu; Mu, Guoying; Li, Peijin

2018-01-01

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments.

Collecting Protein Biomarkers in Breath Using Electret Filters: A Preliminary Method on New Technical Model and Human Study.

Directory of Open Access Journals (Sweden)

Wang Li

Full Text Available Biomarkers in exhaled breath are useful for respiratory disease diagnosis in human volunteers. Conventional methods that collect non-volatile biomarkers, however, necessitate an extensive dilution and sanitation processes that lowers collection efficiencies and convenience of use. Electret filter emerged in recent decade to collect virus biomarkers in exhaled breath given its simplicity and effectiveness. To investigate the capability of electret filters to collect protein biomarkers, a model that consists of an atomizer that produces protein aerosol and an electret filter that collects albumin and carcinoembryonic antigen-a typical biomarker in lung cancer development- from the atomizer is developed. A device using electret filter as the collecting medium is designed to collect human albumin from exhaled breath of 6 volunteers. Comparison of the collecting ability between the electret filter method and other 2 reported methods is finally performed based on the amounts of albumin collected from human exhaled breath. In conclusion, a decreasing collection efficiency ranging from 17.6% to 2.3% for atomized albumin aerosol and 42% to 12.5% for atomized carcinoembryonic antigen particles is found; moreover, an optimum volume of sampling human exhaled breath ranging from 100 L to 200 L is also observed; finally, the self-designed collecting device shows a significantly better performance in collecting albumin from human exhaled breath than the exhaled breath condensate method (p0.05. In summary, electret filters are potential in collecting non-volatile biomarkers in human exhaled breath not only because it was simpler, cheaper and easier to use than traditional methods but also for its better collecting performance.

Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm.

Science.gov (United States)

Zhang, Tao; Zhu, Yongyun; Zhou, Feng; Yan, Yaxiong; Tong, Jinwu

2017-06-17

Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability.

Widely Tunable 4th Order Switched Gm -C Band-Pass Filter Based on N-Path Filters

NARCIS (Netherlands)

Darvishi, M.; van der Zee, Ronan A.R.; Klumperink, Eric A.M.; Nauta, Bram

2012-01-01

Abstract—A widely tunable 4th order BPF based on the subtraction of two 2nd order 4-path passive-mixer filters with slightly different center frequencies is proposed. The center frequency of each 4-path filter is slightly shifted relative to its clock frequency (one upward and the other one

Study on UPF Harmonic Current Detection Method Based on DSP

Energy Technology Data Exchange (ETDEWEB)

Zhao, H J [Northwestern Polytechnical University, Xi' an 710072 (China); Pang, Y F [Xi' an University of Technology, Xi' an 710048 (China); Qiu, Z M [Xi' an University of Technology, Xi' an 710048 (China); Chen, M [Northwestern Polytechnical University, Xi' an 710072 (China)

2006-10-15

Unity power factor (UPF) harmonic current detection method applied to active power filter (APF) is presented in this paper. The intention of this method is to make nonlinear loads and active power filter in parallel to be an equivalent resistance. So after compensation, source current is sinusoidal, and has the same shape of source voltage. Meanwhile, there is no harmonic in source current, and the power factor becomes one. The mathematic model of proposed method and the optimum project for equivalent low pass filter in measurement are presented. Finally, the proposed detection method applied to a shunt active power filter experimental prototype based on DSP TMS320F2812 is developed. Simulation and experiment results indicate the method is simple and easy to implement, and can obtain the real-time calculation of harmonic current exactly.

The applicability of micro-filters produced by nuclear methods in the food industry

International Nuclear Information System (INIS)

Szabo, S.A.; Ember, G.

1982-01-01

Problems of the applicability in the food industry of micro-filters produced by nuclear methods are dealt with. Production methods of the polymeric micro-filters, their main characteristics as well as their most important application fields (breweries, dairies, alcoholic- and soft-drink plants, wine industry) are briefly reviewed. (author)

Biogas Filter Based on Local Natural Zeolite Materials

Directory of Open Access Journals (Sweden)

Satriyo Krido Wahono

2014-02-01

Full Text Available UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as increasing methane contents, increasing heating value, reduction of odors, reduction of corrosion potential, increasing the efficiency and stability of the generator.

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

On the Systematic Synthesis of OTA-Based KHN Filters

Directory of Open Access Journals (Sweden)

Y.A. Li

2014-04-01

Full Text Available According to the nullor-mirror descriptions of OTA, the NAM expansion method for three different types of KHN filters employing OTAs is considered. The type-A filters employing five OTAs have 32 different forms, the type-B filters employing four OTAs have 32 different forms, and the type-C filters employing three OTAs have eight different forms. At last a total of 72 circuits are received. Having used canonic number of components, the circuits are easy to be integrated and both pole frequency and Q-factor can be tuned electronically through tuning bias currents of the OTAs. The MULTISIM simulation results have been included to verify the workability of the derived circuit.

Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence.

Science.gov (United States)

Li, Sui-Xian

2018-05-07

Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI). However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ₂ norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence

Directory of Open Access Journals (Sweden)

Sui-Xian Li

2018-05-01

Full Text Available Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI. However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ2 norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

A new method for E-government procurement using collaborative filtering and Bayesian approach.

Science.gov (United States)

Zhang, Shuai; Xi, Chengyu; Wang, Yan; Zhang, Wenyu; Chen, Yanhong

2013-01-01

Nowadays, as the Internet services increase faster than ever before, government systems are reinvented as E-government services. Therefore, government procurement sectors have to face challenges brought by the explosion of service information. This paper presents a novel method for E-government procurement (eGP) to search for the optimal procurement scheme (OPS). Item-based collaborative filtering and Bayesian approach are used to evaluate and select the candidate services to get the top-M recommendations such that the involved computation load can be alleviated. A trapezoidal fuzzy number similarity algorithm is applied to support the item-based collaborative filtering and Bayesian approach, since some of the services' attributes can be hardly expressed as certain and static values but only be easily represented as fuzzy values. A prototype system is built and validated with an illustrative example from eGP to confirm the feasibility of our approach.

A New Method for E-Government Procurement Using Collaborative Filtering and Bayesian Approach

Directory of Open Access Journals (Sweden)

Shuai Zhang

2013-01-01

Full Text Available Nowadays, as the Internet services increase faster than ever before, government systems are reinvented as E-government services. Therefore, government procurement sectors have to face challenges brought by the explosion of service information. This paper presents a novel method for E-government procurement (eGP to search for the optimal procurement scheme (OPS. Item-based collaborative filtering and Bayesian approach are used to evaluate and select the candidate services to get the top-M recommendations such that the involved computation load can be alleviated. A trapezoidal fuzzy number similarity algorithm is applied to support the item-based collaborative filtering and Bayesian approach, since some of the services’ attributes can be hardly expressed as certain and static values but only be easily represented as fuzzy values. A prototype system is built and validated with an illustrative example from eGP to confirm the feasibility of our approach.

Preliminary energy-filtering neutron imaging with time-of-flight method on PKUNIFTY: A compact accelerator based neutron imaging facility at Peking University

Energy Technology Data Exchange (ETDEWEB)

Wang, Hu; Zou, Yubin, E-mail: zouyubin@pku.edu.cn; Wen, Weiwei; Lu, Yuanrong; Guo, Zhiyu

2016-07-01

Peking University Neutron Imaging Facility (PKUNIFTY) works on an accelerator–based neutron source with a repetition period of 10 ms and pulse duration of 0.4 ms, which has a rather low Cd ratio. To improve the effective Cd ratio and thus improve the detection capability of the facility, energy-filtering neutron imaging was realized with the intensified CCD camera and time-of-flight (TOF) method. Time structure of the pulsed neutron source was firstly simulated with Geant4, and the simulation result was evaluated with experiment. Both simulation and experiment results indicated that fast neutrons and epithermal neutrons were concentrated in the first 0.8 ms of each pulse period; meanwhile in the period of 0.8–2.0 ms only thermal neutrons existed. Based on this result, neutron images with and without energy filtering were acquired respectively, and it showed that detection capability of PKUNIFTY was improved with setting the exposure interval as 0.8–2.0 ms, especially for materials with strong moderating capability.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

Directory of Open Access Journals (Sweden)

Anthony Hoak

2017-03-01

Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm

Directory of Open Access Journals (Sweden)

S. Radhika

2016-04-01

Full Text Available Maximum correntropy criterion (MCC based adaptive filters are found to be robust against impulsive interference. This paper proposes a novel MCC based adaptive filter with variable step size in order to obtain improved performance in terms of both convergence rate and steady state error with robustness against impulsive interference. The optimal variable step size is obtained by minimizing the Mean Square Deviation (MSD error from one iteration to the other. Simulation results in the context of a highly impulsive system identification scenario show that the proposed algorithm has faster convergence and lesser steady state error than the conventional MCC based adaptive filters.

Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

Science.gov (United States)

Shrivastava, Akash; Mohanty, A. R.

2018-03-01

This paper proposes a model-based method to estimate single plane unbalance parameters (amplitude and phase angle) in a rotor using Kalman filter and recursive least square based input force estimation technique. Kalman filter based input force estimation technique requires state-space model and response measurements. A modified system equivalent reduction expansion process (SEREP) technique is employed to obtain a reduced-order model of the rotor system so that limited response measurements can be used. The method is demonstrated using numerical simulations on a rotor-disk-bearing system. Results are presented for different measurement sets including displacement, velocity, and rotational response. Effects of measurement noise level, filter parameters (process noise covariance and forgetting factor), and modeling error are also presented and it is observed that the unbalance parameter estimation is robust with respect to measurement noise.

The filter of choice: filtration method preference among injecting drug users

Directory of Open Access Journals (Sweden)

Keijzer Lenneke

2011-08-01

Full Text Available Abstract Background Injection drug use syringe filters (IDUSF are designed to prevent several complications related to the injection of drugs. Due to their small pore size, their use can reduce the solution's insoluble particle content and thus diminish the prevalence of phlebitis, talcosis.... Their low drug retention discourages from filter reuse and sharing and can thus prevent viral and microbial infections. In France, drug users have access to sterile cotton filters for 15 years and to an IDUSF (the Sterifilt® for 5 years. This study was set up to explore the factors influencing filter preference amongst injecting drug users. Methods Quantitative and qualitative data were gathered through 241 questionnaires and the participation of 23 people in focus groups. Results Factors found to significantly influence filter preference were duration and frequency of injecting drug use, the type of drugs injected and subculture. Furthermore, IDU's rationale for the preference of one type of filter over others was explored. It was found that filter preference depends on perceived health benefits (reduced harms, prevention of vein damage, protection of injection sites, drug retention (low retention: better high, protective mechanism against the reuse of filters; high retention: filter reuse as a protective mechanism against withdrawal, technical and practical issues (filter clogging, ease of use, time needed to prepare an injection and believes (the conviction that a clear solution contains less active compound. Conclusion It was concluded that the factors influencing filter preference are in favour of change; a shift towards the use of more efficient filters can be made through increased availability, information and demonstrations.

Indoor anti-occlusion visible light positioning systems based on particle filtering

Science.gov (United States)

Jiang, Meng; Huang, Zhitong; Li, Jianfeng; Zhang, Ruqi; Ji, Yuefeng

2015-04-01

As one of the most popular categories of mobile services, a rapid growth of indoor location-based services has been witnessed over the past decades. Indoor positioning methods based on Wi-Fi, radio-frequency identification or Bluetooth are widely commercialized; however, they have disadvantages such as low accuracy or high cost. An emerging method using visible light is under research recently. The existed visible light positioning (VLP) schemes using carrier allocation, time allocation and multiple receivers all have limitations. This paper presents a novel mechanism using particle filtering in VLP system. By this method no additional devices are needed and the occlusion problem in visible light would be alleviated which will effectively enhance the flexibility for indoor positioning.

Physics-based coastal current tomographic tracking using a Kalman filter.

Science.gov (United States)

Wang, Tongchen; Zhang, Ying; Yang, T C; Chen, Huifang; Xu, Wen

2018-05-01

Ocean acoustic tomography can be used based on measurements of two-way travel-time differences between the nodes deployed on the perimeter of the surveying area to invert/map the ocean current inside the area. Data at different times can be related using a Kalman filter, and given an ocean circulation model, one can in principle now cast and even forecast current distribution given an initial distribution and/or the travel-time difference data on the boundary. However, an ocean circulation model requires many inputs (many of them often not available) and is unpractical for estimation of the current field. A simplified form of the discretized Navier-Stokes equation is used to show that the future velocity state is just a weighted spatial average of the current state. These weights could be obtained from an ocean circulation model, but here in a data driven approach, auto-regressive methods are used to obtain the time and space dependent weights from the data. It is shown, based on simulated data, that the current field tracked using a Kalman filter (with an arbitrary initial condition) is more accurate than that estimated by the standard methods where data at different times are treated independently. Real data are also examined.

Design of Current-Controller with PR-regulator for LCL-Filter Based Grid-Connected Converter

DEFF Research Database (Denmark)

Zeng, Guohong; Rasmussen, Tonny Wederberg

2010-01-01

In the application of LCL-filter based converters, the structure and parameters of current-controller is very important for the system stability and output current quality. This paper presents a filter-capacitor current feedback control scheme for grid-connected converter. The controller...... is consisted of a proportional-resonance regulator and a proportional regulator. Unlike the existing control strategy with unit capacitor current feedback, the proposed method applies the proportional regulator to the feedback path, which can decouple these two regulators, and simplify the tuning process...... of the control strategy and the proposed current controller design method are verified by the simulation results of a 50kVA grid-connected inverter....

A mobile and web application-based recommendation system using color quantization and collaborative filtering

OpenAIRE

KAYA, FİDAN; YILDIZ, GÜREL; KAVAK, ADNAN

2015-01-01

In this paper, a recommendation system based on a mobile and web application is proposed for indoor decoration. The main contribution of this work is to apply two-stage filtering using linear matching and collaborative filtering to make recommendations. In the mobile application part, the image of the medium captured by a mobile phone is analyzed using color quantization methods, and these color analysis results along with other user-defined parameters such as height, width, and type of the p...

Information filtering based on corrected redundancy-eliminating mass diffusion.

Science.gov (United States)

Zhu, Xuzhen; Yang, Yujie; Chen, Guilin; Medo, Matus; Tian, Hui; Cai, Shi-Min

2017-01-01

Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects' attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is based on a spreading process on the network. Extensive experiments on three benchmark data sets-Movilens, Netflix and Amazon-show that when used in recommendation, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices.

Kalman filtering with real-time applications

CERN Document Server

Chui, Charles K

2017-01-01

This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help de...

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.

T-S Fuzzy Model-Based Approximation and Filter Design for Stochastic Time-Delay Systems with Hankel Norm Criterion

Directory of Open Access Journals (Sweden)

Yanhui Li

2014-01-01

Full Text Available This paper investigates the Hankel norm filter design problem for stochastic time-delay systems, which are represented by Takagi-Sugeno (T-S fuzzy model. Motivated by the parallel distributed compensation (PDC technique, a novel filtering error system is established. The objective is to design a suitable filter that guarantees the corresponding filtering error system to be mean-square asymptotically stable and to have a specified Hankel norm performance level γ. Based on the Lyapunov stability theory and the Itô differential rule, the Hankel norm criterion is first established by adopting the integral inequality method, which can make some useful efforts in reducing conservativeness. The Hankel norm filtering problem is casted into a convex optimization problem with a convex linearization approach, which expresses all the conditions for the existence of admissible Hankel norm filter as standard linear matrix inequalities (LMIs. The effectiveness of the proposed method is demonstrated via a numerical example.

Median Filtering Methods for Non-volcanic Tremor Detection

Science.gov (United States)

Damiao, L. G.; Nadeau, R. M.; Dreger, D. S.; Luna, B.; Zhang, H.

2016-12-01

Various properties of median filtering over time and space are used to address challenges posed by the Non-volcanic tremor detection problem. As part of a "Big-Data" effort to characterize the spatial and temporal distribution of ambient tremor throughout the Northern San Andreas Fault system, continuous seismic data from multiple seismic networks with contrasting operational characteristics and distributed over a variety of regions are being used. Automated median filtering methods that are flexible enough to work consistently with these data are required. Tremor is characterized by a low-amplitude, long-duration signal-train whose shape is coherent at multiple stations distributed over a large area. There are no consistent phase arrivals or mechanisms in a given tremor's signal and even the durations and shapes among different tremors vary considerably. A myriad of masquerading noise, anthropogenic and natural-event signals must also be discriminated in order to obtain accurate tremor detections. We present here results of the median methods applied to data from four regions of the San Andreas Fault system in northern California (Geysers Geothermal Field, Napa, Bitterwater and Parkfield) to illustrate the ability of the methods to detect tremor under diverse conditions.

Switching non-local median filter

Science.gov (United States)

Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji

2015-06-01

This paper describes a novel image filtering method for removal of random-valued impulse noise superimposed on grayscale images. Generally, it is well known that switching-type median filters are effective for impulse noise removal. In this paper, we propose a more sophisticated switching-type impulse noise removal method in terms of detail-preserving performance. Specifically, the noise detector of the proposed method finds out noise-corrupted pixels by focusing attention on the difference between the value of a pixel of interest (POI) and the median of its neighboring pixel values, and on the POI's isolation tendency from the surrounding pixels. Furthermore, the removal of the detected noise is performed by the newly proposed median filter based on non-local processing, which has superior detail-preservation capability compared to the conventional median filter. The effectiveness and the validity of the proposed method are verified by some experiments using natural grayscale images.

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

Science.gov (United States)

Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

2016-11-01

This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

Detection method based on Kalman filter for high speed rail defect AE signal on wheel-rail rolling rig

Science.gov (United States)

Hao, Qiushi; Shen, Yi; Wang, Yan; Zhang, Xin

2018-01-01

Nondestructive test (NDT) of rails has been carried out intermittently in traditional approaches, which highly restricts the detection efficiency under rapid development of high speed railway nowadays. It is necessary to put forward a dynamic rail defect detection method for rail health monitoring. Acoustic emission (AE) as a practical real-time detection technology takes advantage of dynamic AE signal emitted from plastic deformation of material. Detection capacities of AE on rail defects have been verified due to its sensitivity and dynamic merits. Whereas the application under normal train service circumstance has been impeded by synchronous background noises, which are directly linked to the wheel speed. In this paper, surveys on a wheel-rail rolling rig are performed to investigate defect AE signals with varying speed. A dynamic denoising method based on Kalman filter is proposed and its detection effectiveness and flexibility are demonstrated by theory and computational results. Moreover, after comparative analysis of modelling precision at different speeds, it is predicted that the method is also applicable for high speed condition beyond experiments.

Development of a filter-based method for detecting silver nanoparticles and their heteroaggregation in aqueous environments by surface-enhanced Raman spectroscopy

International Nuclear Information System (INIS)

Guo, Huiyuan; Xing, Baoshan; He, Lili

2016-01-01

The rising application of silver nanoparticles (AgNPs) and subsequent release into aquatic systems have generated public concerns over their potential risk and harm to aquatic organisms and human health. Effective and practical analytical methods for AgNPs are urgently needed for their risk assessment. In this study we established an innovative approach to detect trace levels of AgNPs in environmental water through integrating a filtration technique into surface-enhanced Raman spectroscopy (SERS) and compared it with previously established centrifuge-based method. The purpose of filtration was to trap and enrich salt-aggregated AgNPs from water samples onto the filter membrane, through which indicator was then passed and complexed with AgNPs. The enhanced SERS signals of indicator could reflect the presence and quantity of AgNPs in the samples. The most favorable benefit of filtration is being able to process large volume samples, which is more practical for water samples, and greatly improves the sensitivity of AgNP detection. In this study, we tested 20 mL AgNPs-containing samples and the filter-based method is able to detect AgNPs as low as 5 μg/L, which is 20 folds lower than the centrifuge-based method. In addition, the speed and precision of the detection were greatly improved. This approach was used to detect trace levels of AgNPs in real environmental water successfully. Meanwhile, the heteroaggregation of AgNPs with minerals in water was reliably monitored by the new method. Overall, a combination of the filtration-SERS approach provides a rapid, simple, and sensitive way to detect AgNPs and analyze their environmental behavior. - Highlights: • We developed a filtration-SERS method for analyzing AgNPs in water. • Detection limit can be improved by increasing sample volume for filtration. • Trace levels of AgNPs in natural water samples can be successfully detected. • Filtration-SERS is more efficient and precise than centrifugation-SERS. �

Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide

DEFF Research Database (Denmark)

Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui

2016-01-01

Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN and satel...... and satellite communication signals. Due to planar structures proposed here, it is easy to integrate in the microwave integrated systems, which can play an important role in the microwave communication circuit and system.......Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...

Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models

KAUST Repository

El Gharamti, Mohamad; Hoteit, Ibrahim

2014-01-01

The accuracy of groundwater flow and transport model predictions highly depends on our knowledge of subsurface physical parameters. Assimilation of contaminant concentration data from shallow dug wells could help improving model behavior, eventually resulting in better forecasts. In this paper, we propose a joint state-parameter estimation scheme which efficiently integrates a low-rank extended Kalman filtering technique, namely the Singular Evolutive Extended Kalman (SEEK) filter, with the prominent complex-step method (CSM). The SEEK filter avoids the prohibitive computational burden of the Extended Kalman filter by updating the forecast along the directions of error growth only, called filter correction directions. CSM is used within the SEEK filter to efficiently compute model derivatives with respect to the state and parameters along the filter correction directions. CSM is derived using complex Taylor expansion and is second order accurate. It is proven to guarantee accurate gradient computations with zero numerical round-off errors, but requires complexifying the numerical code. We perform twin-experiments to test the performance of the CSM-based SEEK for estimating the state and parameters of a subsurface contaminant transport model. We compare the efficiency and the accuracy of the proposed scheme with two standard finite difference-based SEEK filters as well as with the ensemble Kalman filter (EnKF). Assimilation results suggest that the use of the CSM in the context of the SEEK filter may provide up to 80% more accurate solutions when compared to standard finite difference schemes and is competitive with the EnKF, even providing more accurate results in certain situations. We analyze the results based on two different observation strategies. We also discuss the complexification of the numerical code and show that this could be efficiently implemented in the context of subsurface flow models. © 2013 Elsevier B.V.

Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models

KAUST Repository

El Gharamti, Mohamad

2014-02-01

The accuracy of groundwater flow and transport model predictions highly depends on our knowledge of subsurface physical parameters. Assimilation of contaminant concentration data from shallow dug wells could help improving model behavior, eventually resulting in better forecasts. In this paper, we propose a joint state-parameter estimation scheme which efficiently integrates a low-rank extended Kalman filtering technique, namely the Singular Evolutive Extended Kalman (SEEK) filter, with the prominent complex-step method (CSM). The SEEK filter avoids the prohibitive computational burden of the Extended Kalman filter by updating the forecast along the directions of error growth only, called filter correction directions. CSM is used within the SEEK filter to efficiently compute model derivatives with respect to the state and parameters along the filter correction directions. CSM is derived using complex Taylor expansion and is second order accurate. It is proven to guarantee accurate gradient computations with zero numerical round-off errors, but requires complexifying the numerical code. We perform twin-experiments to test the performance of the CSM-based SEEK for estimating the state and parameters of a subsurface contaminant transport model. We compare the efficiency and the accuracy of the proposed scheme with two standard finite difference-based SEEK filters as well as with the ensemble Kalman filter (EnKF). Assimilation results suggest that the use of the CSM in the context of the SEEK filter may provide up to 80% more accurate solutions when compared to standard finite difference schemes and is competitive with the EnKF, even providing more accurate results in certain situations. We analyze the results based on two different observation strategies. We also discuss the complexification of the numerical code and show that this could be efficiently implemented in the context of subsurface flow models. © 2013 Elsevier B.V.

Method of mounting filter elements and mounting therefor

International Nuclear Information System (INIS)

Karelin, J.; Neumann, G.M.

1981-01-01

A process for the insertion and exchange of the filter elements for suspended matter is performed from the clean-air-side. During the insertion of a filter element, a plastic tube (Which encircles the circumference of the filter element and which exceeds in its length the layer thickness of the filter element several times) is tightly connected in its middle section with the side walls, which side walls form a border around the filter element; and then the open end of the plastic tube, which faces the frame, is connected by way of a tight fit with a ring, which is actually known and which surrounds the orifice of the frame into which the filter element is inserted. The filter element is connected with the frame by means of tightening devices, and the outer free end of the tube is turned inside out and around the filter element for the purpose of unhindered air passage through the filter layer, that during the exchange of the contaminated filter element, the outer open end of the tube is heat sealed. The filter element is disconnected and removed from the frame by flipping down of the tightening devices, and the tube is heat sealed in the section between the filter element and the frame, and, that during the insertion of a new filter element, a new tube is attached by way of tight fitting to the ring of the frame , which tube is at its middle section tightly connected with the filter element, and which tube is attached to the ring of the frame in an actually known by overlapping of the heat-sealed tube rest. The tube rest is pulled onto the new tube and pulled off the ring, and the filter element is tightly connected with the frame by means of the tightening devices

Noise Reduction with Optimal Variable Span Linear Filters

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll

2016-01-01

In this paper, the problem of noise reduction is addressed as a linear filtering problem in a novel way by using concepts from subspace-based enhancement methods, resulting in variable span linear filters. This is done by forming the filter coefficients as linear combinations of a number...... included in forming the filter. Using these concepts, a number of different filter designs are considered, like minimum distortion, Wiener, maximum SNR, and tradeoff filters. Interestingly, all these can be expressed as special cases of variable span filters. We also derive expressions for the speech...... demonstrate the advantages and properties of the variable span filter designs, and their potential performance gain compared to widely used speech enhancement methods....

SAR Interferogram Filtering of Shearlet Domain Based on Interferometric Phase Statistics

Directory of Open Access Journals (Sweden)

Yonghong He

2017-02-01

Full Text Available This paper presents a new filtering approach for Synthetic Aperture Radar (SAR interferometric phase noise reduction in the shearlet domain, depending on the coherent statistical characteristics. Shearlets provide a multidirectional and multiscale decomposition that have advantages over wavelet filtering methods when dealing with noisy phase fringes. Phase noise in SAR interferograms is directly related to the interferometric coherence and the look number of the interferogram. Therefore, an optimal interferogram filter should incorporate information from both of them. The proposed method combines the phase noise standard deviation with the shearlet transform. Experimental results show that the proposed method can reduce the interferogram noise while maintaining the spatial resolution, especially in areas with low coherence.

MR image reconstruction via guided filter.

Science.gov (United States)

Huang, Heyan; Yang, Hang; Wang, Kang

2018-04-01

Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.

An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

Science.gov (United States)

Liu, Yahui; Fan, Xiaoqian; Lv, Chen; Wu, Jian; Li, Liang; Ding, Dawei

2018-02-01

Information fusion method of INS/GPS navigation system based on filtering technology is a research focus at present. In order to improve the precision of navigation information, a navigation technology based on Adaptive Kalman Filter with attenuation factor is proposed to restrain noise in this paper. The algorithm continuously updates the measurement noise variance and processes noise variance of the system by collecting the estimated and measured values, and this method can suppress white noise. Because a measured value closer to the current time would more accurately reflect the characteristics of the noise, an attenuation factor is introduced to increase the weight of the current value, in order to deal with the noise variance caused by environment disturbance. To validate the effectiveness of the proposed algorithm, a series of road tests are carried out in urban environment. The GPS and IMU data of the experiments were collected and processed by dSPACE and MATLAB/Simulink. Based on the test results, the accuracy of the proposed algorithm is 20% higher than that of a traditional Adaptive Kalman Filter. It also shows that the precision of the integrated navigation can be improved due to the reduction of the influence of environment noise.

Calculation methods of reactivity using derivatives of nuclear power and Filter fir

International Nuclear Information System (INIS)

Diaz, Daniel Suescun

2007-01-01

This work presents two new methods for the solution of the inverse point kinetics equation. The first method is based on the integration by parts of the integral of the inverse point kinetics equation, which results in a power series in terms of the nuclear power in time dependence. Applying some conditions to the nuclear power, the reactivity is represented as first and second derivatives of this nuclear power. This new calculation method for reactivity has special characteristics, amongst which the possibility of using different sampling periods, and the possibility of restarting the calculation, after its interruption associated it with a possible equipment malfunction, allowing the calculation of reactivity in a non-continuous way. Apart from this reactivity can be obtained with or without dependency on the nuclear power memory. The second method is based on the Laplace transform of the point kinetics equations, resulting in an expression equivalent to the inverse kinetics equation as a function of the power history. The reactivity can be written in terms of the summation of convolution with response to impulse, characteristic of a linear system. For its digital form the Z-transform is used, which is the discrete version of the Laplace transform. In this method it can be pointed out that the linear part is equivalent to a filter named Finite Impulse Response (Fir). The Fir filter will always be, stable and non-varying in time, and, apart from this, it can be implemented in the non-recursive way. This type of implementation does not require feedback, allowing the calculation of reactivity in a continuous way. The proposed methods were validated using signals with random noise and showing the relationship between the reactivity difference and the degree of the random noise. (author)

Tunable double-channel filter based on two-dimensional ferroelectric photonic crystals

International Nuclear Information System (INIS)

Jiang, Ping; Ding, Chengyuan; Hu, Xiaoyong; Gong, Qihuang

2007-01-01

A tunable double-channel filter is presented, which is based on a two-dimensional nonlinear ferroelectric photonic crystal made of cerium doped barium titanate. The filtering properties of the photonic crystal filter can be tuned by adjusting the defect structure or by a pump light. The influences of the structure disorders caused by the perturbations in the radius or the position of air holes on the filtering properties are also analyzed

Tunable double-channel filter based on two-dimensional ferroelectric photonic crystals

Energy Technology Data Exchange (ETDEWEB)

Jiang, Ping [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China); Ding, Chengyuan [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China); Hu, Xiaoyong [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China)]. E-mail: xiaoyonghu@pku.edu.cn; Gong, Qihuang [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China)]. E-mail: qhgong@pku.edu.cn

2007-04-02

A tunable double-channel filter is presented, which is based on a two-dimensional nonlinear ferroelectric photonic crystal made of cerium doped barium titanate. The filtering properties of the photonic crystal filter can be tuned by adjusting the defect structure or by a pump light. The influences of the structure disorders caused by the perturbations in the radius or the position of air holes on the filtering properties are also analyzed.

Electromagnetic design methods in systems-on-chip: integrated filters for wireless CMOS RFICs

International Nuclear Information System (INIS)

Contopanagos, Harry

2005-01-01

We present general methods for designing on-chip CMOS passives and utilizing these integrated elements to design on-chip CMOS filters for wireless communications. These methods rely on full-wave electromagnetic numerical calculations that capture all the physics of the underlying foundry technologies. This is especially crucial for deep sub-micron CMOS technologies as it is important to capture the physical effects of finite (and mediocre) Q-factors limited by material losses and constraints on expensive die area, low self-resonance frequencies and dual parasitics that are particularly prevalent in deep sub-micron CMOS processes (65 nm-0.18 μm. We use these integrated elements in an ideal synthesis of a Bluetooth/WLAN pass-band filter in single-ended or differential architectures, and show the significant deviations of the on-chip filter response from the ideal one. We identify which elements in the filter circuit need to maximize their Q-factors and which Q-factors do not affect the filter performance. This saves die area, and predicts the FET parameters (especially transconductances) and negative-resistance FET topologies that have to be integrated in the filter to restore its performance. (invited paper)

Electromagnetic design methods in systems-on-chip: integrated filters for wireless CMOS RFICs

Energy Technology Data Exchange (ETDEWEB)

Contopanagos, Harry [Institute for Microelectronics, NCSR ' Demokritos' , PO Box 60228, GR-153 10 Aghia Paraskevi, Athens (Greece)

2005-01-01

We present general methods for designing on-chip CMOS passives and utilizing these integrated elements to design on-chip CMOS filters for wireless communications. These methods rely on full-wave electromagnetic numerical calculations that capture all the physics of the underlying foundry technologies. This is especially crucial for deep sub-micron CMOS technologies as it is important to capture the physical effects of finite (and mediocre) Q-factors limited by material losses and constraints on expensive die area, low self-resonance frequencies and dual parasitics that are particularly prevalent in deep sub-micron CMOS processes (65 nm-0.18 {mu}m. We use these integrated elements in an ideal synthesis of a Bluetooth/WLAN pass-band filter in single-ended or differential architectures, and show the significant deviations of the on-chip filter response from the ideal one. We identify which elements in the filter circuit need to maximize their Q-factors and which Q-factors do not affect the filter performance. This saves die area, and predicts the FET parameters (especially transconductances) and negative-resistance FET topologies that have to be integrated in the filter to restore its performance. (invited paper)

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

Multi-tap complex-coefficient incoherent microwave photonic filters based on optical single-sideband modulation and narrow band optical filtering.

Science.gov (United States)

Sagues, Mikel; García Olcina, Raimundo; Loayssa, Alayn; Sales, Salvador; Capmany, José

2008-01-07

We propose a novel scheme to implement tunable multi-tap complex coefficient filters based on optical single sideband modulation and narrow band optical filtering. A four tap filter is experimentally demonstrated to highlight the enhanced tuning performance provided by complex coefficients. Optical processing is performed by the use of a cascade of four phase-shifted fiber Bragg gratings specifically fabricated for this purpose.

Si(Li) x-ray spectrometer with signal processing system based on digital filtering

International Nuclear Information System (INIS)

Lakatos, Tamas

1985-01-01

A new signal processing system is under development at ATOMKI, Debrecen, Hungary, based on digital filtering by a microprocessor. The advantages of the new method are summarized. Dead time can be decreased and the speed of signal processing can be increased. Computer simulations verified the theoretical conclusions. (D.Gy.)

Design and implementation of predictive filtering system for current reference generation of active power filter

Energy Technology Data Exchange (ETDEWEB)

Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

2007-02-15

The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

Science.gov (United States)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.

An improvement of the filter diagonalization-based post-processing method applied to finite difference time domain calculations of three-dimensional phononic band structures

International Nuclear Information System (INIS)

Su Xiaoxing; Zhang Chuanzeng; Ma Tianxue; Wang Yuesheng

2012-01-01

When three-dimensional (3D) phononic band structures are calculated by using the finite difference time domain (FDTD) method with a relatively small number of iterations, the results can be effectively improved by post-processing the FDTD time series (FDTD-TS) based on the filter diagonalization method (FDM), instead of the classical fast Fourier transform. In this paper, we propose a way to further improve the performance of the FDM-based post-processing method by introducing a relatively large number of observing points to record the FDTD-TS. To this end, the existing scheme of FDTD-TS preprocessing is modified. With the new preprocessing scheme, the processing efficiency of a single FDTD-TS can be improved significantly, and thus the entire post-processing method can have sufficiently high efficiency even when a relatively large number of observing points are used. The feasibility of the proposed method for improvement is verified by the numerical results.

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

Directory of Open Access Journals (Sweden)

Byeong Hak Kim

2017-12-01

Full Text Available Unmanned aerial vehicles (UAVs are equipped with optical systems including an infrared (IR camera such as electro-optical IR (EO/IR, target acquisition and designation sights (TADS, or forward looking IR (FLIR. However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC and scene-based NUC (SBNUC. However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA. In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR and long wave infrared (LWIR images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

Science.gov (United States)

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-01-01

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC. PMID:29280970

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

Science.gov (United States)

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-12-27

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions Based on a Bank of Norm-Inequality-Constrained Epoch-State Filters