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Journal articles on the topic 'Multivariate filter'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Spangl, Bernhard. "Robust Filtering for Linear State-space Models with Non-propagating Outliers Following a Mixture of Gaussian Distributions." Austrian Journal of Statistics 54, no. 3 (2025): 150–68. https://doi.org/10.17713/ajs.v54i3.2077.

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The problem of recursive filtering in linear state-space models is considered. The solution to this problem is the classical Kalman filter which is optimal in the sense that it minimizes the variance of the estimated states, if the error processes of the state and observation equations are both Gaussian. However, the Kalman filter is well known to be sensitive to outliers, so robustness is an issue. Two approximate conditional-mean (ACM) type filters for vector-valued observations are proposed that generalize existing univariate filters of similar type to the multivariate case.These new ACM-ty

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2

WHITCHER, BRANDON, and PETER F. CRAIGMILE. "MULTIVARIATE SPECTRAL ANALYSIS USING HILBERT WAVELET PAIRS." International Journal of Wavelets, Multiresolution and Information Processing 02, no. 04 (2004): 567–87. http://dx.doi.org/10.1142/s0219691304000652.

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We investigate the use of Hilbert wavelet pairs (HWPs) in the non-decimated discrete wavelet transform for the time-varying spectral analysis of multivariate time series. HWPs consist of two high-pass and two low-pass compactly supported filters, such that one high-pass filter is the Hilbert transform (approximately) of the other. Thus, common quantities in the spectral analysis of time series (e.g., power spectrum, coherence, phase) may be estimated in both time and frequency. Compact support of the wavelet filters ensures that the frequency axis will be partitioned dyadically as with the usu

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3

Vitek, Francis. "A Closed Form Multivariate Linear Filter." IMF Working Papers 18, no. 275 (2018): 1. http://dx.doi.org/10.5089/9781484388785.001.

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4

Chen, Qiuhui, Charles A. Micchelli, Silong Peng, and Yuesheng Xu. "Multivariate Filter Banks Having Matrix Factorizations." SIAM Journal on Matrix Analysis and Applications 25, no. 2 (2003): 517–31. http://dx.doi.org/10.1137/s0895479802412735.

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5

García Infante, Juan Carlos, José de J. Medel Juárez, and Juan Carlos Sánchez García. "Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO)." Ingeniería e Investigación 31, no. 1 (2011): 184–92. http://dx.doi.org/10.15446/ing.investig.v31n1.20569.

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Multivariate identifier filters (multiple inputs and multiple outputs - MIMO) are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948). This paper considers the MIMO digital filter model usi

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Jonsson, Lena, Elzbieta Plaza, and Bengt Hultman. "Experiences of nitrogen and phosphorus removal in deep-bed filters in the Stockholm area." Water Science and Technology 36, no. 1 (1997): 183–90. http://dx.doi.org/10.2166/wst.1997.0042.

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Experimental studies of nutrient removal in a discontinuous downflow two-media filter on a pilot plant scale are described and compared with previously reported results from a continuous upflow filter (DynaSand) studied at full scale. Under controlled conditions both filters show low effluent values of total nitrogen and phosphorus. Removal mechanisms were more complex in the discontinuous downflow filter owing to the use of two media, deposition of sludge on the filter surface, and changes of the biological activity over time after backwashing. The discontinuous downflow filter was much influ

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Kang, Jieun, Heung-Kyu Ko, Ji Hoon Shin, et al. "Practice patterns of retrievable inferior vena cava filters and predictors of filter retrieval in patients with pulmonary embolism." Vascular Medicine 22, no. 6 (2017): 512–17. http://dx.doi.org/10.1177/1358863x17726596.

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Retrievable inferior vena cava (IVC) filters are increasingly used in patients with venous thromboembolism (VTE) who have contraindications to anticoagulant therapy. However, previous studies have shown that many retrievable filters are left permanently in patients. This study aimed to identify the common indications for IVC filter insertion, the filter retrieval rate, and the predictive factors for filter retrieval attempts. To this end, a retrospective cohort study was performed at a tertiary care center in South Korea between January 2010 and May 2016. Electronic medical charts were reviewe

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8

International Monetary Fund. "Estimating Potential Output with a Multivariate Filter." IMF Working Papers 10, no. 285 (2010): 1. http://dx.doi.org/10.5089/9781455210923.001.

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9

Blagrave, Patrick, Roberto Garcia-Saltos, Douglas Laxton, and Fan Zhang. "A Simple Multivariate Filter for Estimating Potential Output." IMF Working Papers 15, no. 79 (2015): 1. http://dx.doi.org/10.5089/9781475565133.001.

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10

ur Rehman, Naveed, and Danilo P. Mandic. "Filter Bank Property of Multivariate Empirical Mode Decomposition." IEEE Transactions on Signal Processing 59, no. 5 (2011): 2421–26. http://dx.doi.org/10.1109/tsp.2011.2106779.

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11

Chen, Qiuhui, Charles A. Micchelli, and Yuesheng Xu. "Biorthogonal multivariate filter banks from centrally symmetric matrices." Linear Algebra and its Applications 402 (June 2005): 111–25. http://dx.doi.org/10.1016/j.laa.2004.12.028.

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12

Lee, J., and D. W. Kim. "Efficient multivariate feature filter using conditional mutual information." Electronics Letters 48, no. 3 (2012): 161. http://dx.doi.org/10.1049/el.2011.3063.

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13

Chen, Qiuhui, Guangbin Ren, Paula Cerejeiras, and Uwe Kaehler. "Non-separable multivariate filter banks from univariate wavelets." Mathematische Nachrichten 286, no. 10 (2013): 951–69. http://dx.doi.org/10.1002/mana.201000100.

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14

Sum, Stephen T., and Steven D. Brown. "Standardization of Fiber-Optic Probes for Near-Infrared Multivariate Calibrations." Applied Spectroscopy 52, no. 6 (1998): 869–77. http://dx.doi.org/10.1366/0003702981944418.

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The standardization of Fourier transform near-infrared (FT-NIR) spectrometers equipped with fiber-optic probes was investigated. FT-NIR spectra of caustic brines for an industrial process were measured on two different instruments. Calibration transfer across the instruments and probes was studied by employing calibration models built on one instrument to predict properties from spectra measured on the other. The transfer was examined by using spectra without and with preprocessing. The preprocessing methods included a Savitzky–Golay (SG) derivative polynomial filter, a procedure based on a fi

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15

Meierhofer, Regula, Pascal Rubli, Jared Oremo, and Alloyce Odhiambo. "Does Activated Silver Reduce Recontamination Risks in the Reservoirs of Ceramic Water Filters?" Water 11, no. 5 (2019): 1108. http://dx.doi.org/10.3390/w11051108.

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Efforts to provide safe water are challenged by recontamination and regrowth of pathogens in treated water during storage. This study evaluated the potential of metallic silver with a chemically etched surface to reduce recontamination risks during water storage in ceramic water filters. Batch experiments were conducted in the laboratory with water storage buckets containing three configurations of varying amounts of silver. Field trials in a rural area in Kenya assessed the effect of the same configurations in the storage buckets of locally produced ceramic pot filters without colloidal silve

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16

AMMICHE, M., and A. KOUADRI. "False Alarms Rate Reduction Using Filtered Monitoring Indices." Algerian Journal of Signals and Systems 2, no. 1 (2017): 40–50. http://dx.doi.org/10.51485/ajss.v2i1.31.

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False alarms are the major problem in fault detection when using multivariate statistical process monitoring such as principal component analysis (PCA), they affect the detection accuracy and lead to make wrong decisions about the process operation status. In this work, filtering the monitoring indices is proposed to enhance the detection by reducing the number of false alarms. The filters that were used are: Standard Median Filter (SMF), Improved Median Filter (IMF) and fuzzy logic based filter. Signal to Noise Ratio (SNR), False Alarms Rate (FAR) and the detection time of the fault were used

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17

Azevedo, João Valle e. "A multivariate band-pass filter for economic time series." Journal of the Royal Statistical Society: Series C (Applied Statistics) 60, no. 1 (2010): 1–30. http://dx.doi.org/10.1111/j.1467-9876.2010.00734.x.

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18

Poloni, Federico, and Giacomo Sbrana. "MULTIVARIATE TREND–CYCLE EXTRACTION WITH THE HODRICK–PRESCOTT FILTER." Macroeconomic Dynamics 21, no. 6 (2016): 1336–60. http://dx.doi.org/10.1017/s1365100515000887.

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The Hodrick–Prescott filter represents one of the most popular methods for trend–cycle extraction in macroeconomic time series. In this paper we provide a multivariate generalization of the Hodrick–Prescott filter, based on the seemingly unrelated time series approach. We first derive closed-form expressions linking the signal–noise matrix ratio to the parameters of the VARMA representation of the model. We then show that the parameters can be estimated using a recently introduced method, called “Moment Estimation Through Aggregation (META).” This method replaces traditional multivariate likel

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19

Luong, Van Su, Minhhuy Le, Khoa Dang Nguyen, Dang-Khanh Le, and Jinyi Lee. "Electromagnetic Testing of Moisture Separation Reheater Tube based on Multivariate Singular Spectral Analysis." Applied Sciences 10, no. 11 (2020): 3954. http://dx.doi.org/10.3390/app10113954.

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Moisture separator reheater (MSR) tubing systems are an important part of a pressurized-water power plant to increase the efficiency of the heat transfer rate. The MSR tubes are finned tubes which are made of ferritic stainless steel (SS439) with a high strength and corrosion resistance characteristics. However, corrosion can appear along with the fins after a long period of operation of the MSR tubes that requires nondestructive testing (NDT) of the MSR tubes’ periodically. Electromagnetic testing (ET) is an efficient NDT method for the inspection of far-side corrosion in the MSR tubes. Howev

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20

Barginear, M. F., M. L. Lesser, M. Strakhan, et al. "Anticoagulation vs. vena caval filters in cancer patients with venous thromboembolism: Improved survival with anticoagulation." Journal of Clinical Oncology 24, no. 18_suppl (2006): 8553. http://dx.doi.org/10.1200/jco.2006.24.18_suppl.8553.

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8553 Background: Cancer patients (pts) have an increased incidence of venous thromboembolism (VTE). Inferior vena caval (IVC) filters are used extensively in the US; over 40,000 are inserted annually. The impact on survival of cancer pts receiving IVC filters has not been studied. Methods: A retrospective study examined 154 consecutive cancer pts with VTE in order to compare the effects of IVC filter placement with anticoagulation (AC) therapy on overall survival (OS), as measured from the time of VTE. Pts were classified into three treatment groups: AC (n=58), IVC filter (73), or combination

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21

Marhaba, Bassel, and Mourad Zribi. "A Novel Combination Method for Image Restoration Based on Bootstrap Filter and DWT." MATEC Web of Conferences 261 (2019): 06002. http://dx.doi.org/10.1051/matecconf/201926106002.

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In our paper, we propose a novel combination of two methods based on the bootstrap filter. We will use the fusion technique to combine the restored images from the bootstrap multivariate kernel density filter and the bootstrap kernel-diffeomorphism filter. Experimental results have shown that our method has proved the image restoration results.

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22

Singh, Omkar. "Physiological Time Series Processing via Empirical Wavelet Transform." Advanced Science, Engineering and Medicine 12, no. 5 (2020): 582–87. http://dx.doi.org/10.1166/asem.2020.2557.

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This paper presents the efficacy of empirical wavelet transform (EWT) for physiological time series processing. At first, EWT is applied to multivariate heterogeneous physiological time series. Secondly, EWT is used for the removal of fast temporal scales in multiscale entropy analysis. Empirical mode decomposition is an adaptive data analysis method in the sense that it does not require prior information about the signal statistics and tend to decompose a signal into various constituent modes. The utility of Standard EMD algorithm is however limited to single channel data as it suffers from t

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23

Cheng, Xiaoyu, Maoxing Wen, Cong Gao, and Yueming Wang. "Hyperspectral Anomaly Detection Based on Wasserstein Distance and Spatial Filtering." Remote Sensing 14, no. 12 (2022): 2730. http://dx.doi.org/10.3390/rs14122730.

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Since anomaly targets in hyperspectral images (HSIs) with high spatial resolution appear as connected areas instead of single pixels or subpixels, both spatial and spectral information of HSIs can be exploited for a hyperspectal anomaly detection (AD) task. This article proposes a hyperspectral AD method based on Wasserstein distance (WD) and spatial filtering (called AD-WDSF). Based on the assumption that both background and anomaly targets obey the multivariate Gaussian distribution, background and anomaly target distributions are estimated in the local regions of HSIs. Subsequently, the ano

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24

HAN, Min, and Ya-Nan WANG. "Multivariate Time Series Online Predictor with Kalman Filter Trained Reservoir." Acta Automatica Sinica 36, no. 1 (2010): 169–73. http://dx.doi.org/10.3724/sp.j.1004.2010.00169.

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25

Alichi, Ali, Olivier Bizimana, Douglas Laxton, et al. "Multivariate Filter Estimation of Potential Output for the United States." IMF Working Papers 17, no. 106 (2017): 1. http://dx.doi.org/10.5089/9781475598384.001.

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26

Rutan, Sarah C., Eric Bouveresse, Kevin N. Andrew, Paul J. Worsfold, and D. L. Massart. "Correction for drift in multivariate systems using the Kalman filter." Chemometrics and Intelligent Laboratory Systems 35, no. 2 (1996): 199–211. http://dx.doi.org/10.1016/s0169-7439(96)00052-4.

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27

Chen, Qiuhui, Charles A. Micchelli, and Yuesheng Xu. "On the matrix completion problem for multivariate filter bank construction." Advances in Computational Mathematics 26, no. 1-3 (2007): 173–204. http://dx.doi.org/10.1007/s10444-005-7535-9.

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28

Qiaofang, Lian, Xiao Hongying, and Chen Qiuhui. "Some properties on multivariate filter banks with a matrix factorization." Progress in Natural Science 15, no. 2 (2005): 115–25. http://dx.doi.org/10.1080/10020070512331341860.

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29

Haibach, Frederick G., Ashley E. Greer, Maria V. Schiza, Ryan J. Priore, Olusola O. Soyemi, and Michael L. Myrick. "On-line reoptimization of filter designs for multivariate optical elements." Applied Optics 42, no. 10 (2003): 1833. http://dx.doi.org/10.1364/ao.42.001833.

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30

Buss, Ginters. "Real-Time Signal Extraction with Regularized Multivariate Direct Filter Approach." Journal of Forecasting 35, no. 3 (2015): 206–16. http://dx.doi.org/10.1002/for.2352.

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31

Jin, Qi Bing, and Rong Li. "A V-Norm Decoupling IMC Method with Filters Based on Inverted Decoupling." Applied Mechanics and Materials 197 (September 2012): 311–15. http://dx.doi.org/10.4028/www.scientific.net/amm.197.311.

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A V-norm Decoupling internal model control (IMC) method with filters based on inverted decoupling for multivariate stable object is proposed in this paper. The actual industrial process is very difficult to obtain an accurate model, which makes the control effect not satisfactory. To solve this problem, the V-norm decoupling controller is designed on the basis of the inverted decoupling, and a filter is added in front of the controller to reduce coupling and increase robustness. Compared with traditional multivariable controller designed method, the method of designing the internal model contr

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32

Solomon, Khmelnik, and Gelfand Alexander. "Discrete filtration of Multivariate Correlated Nonstationary Processes." Papers of Independent Authors, ISSN 2225-6717 7 (March 16, 2008): 6–18. https://doi.org/10.5281/zenodo.3828873.

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We consider a vector stochastic process with stationary increments of a predetermined order, whose components are linearly dependent, i.e. in the absence of noise vector process components are constrained by a system of linear equations (constraints). The interdependence of stochastic processes can be determined by a static or a dynamic model. The constraints can be maintained rigidly or with a specified error. We offer a method allowing in these conditions synthesis of an optimum filter structure. This method works in cases where no information about signal and noise static properties is avai

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Shcherban, O. G., D. M. Lazurenko, I. V. Shcherban, and N. E. Kirilenko. "The Synthesis of an Adaptive Filter for Automatic Detection and Time Localization of Premotor EEG Patterns of the Human Brain." INFORMACIONNYE TEHNOLOGII 27, no. 9 (2021): 484–93. http://dx.doi.org/10.17587/it.27.484-493.

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An adaptive low-pass filter has been synthesized for automatic patterns detection of arbitrary mental movements in records of multidimensional electroencephalograms (EEG). The filter is based on the multivariate singular spectrum analysis. The effective bandwidth of the filter corresponds to the spectrum of the sought patterns of mental activity on the observed EEG time interval. The use of the synthesized filter provided a reliable automatic search for patterns and the correct determination of their time boundaries. The correctness of the results has been confirmed in experiments with 24 volu

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34

Rice, P. M., K. B. Alexander, and I. M. Anderson. "Multivariate Statistical Analysis of Spectrum Lines From Si3N4 Grain Boundaries." Microscopy and Microanalysis 3, S2 (1997): 945–46. http://dx.doi.org/10.1017/s1431927600011612.

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It is well known that the high-temperature properties of polycrystalline Si3N4 ceramics are strongly influenced by the nanometer-scale glassy phase at the grain boundaries. We have recently analyzed the variation of the near-edge fine structure (ELNES) of the Si-L2,3 edges using a combination of TEM spectrum-line acquisition with an imaging filter and multivariate statistical analysis.The glassy phase at the Si3N4 grain boundaries is easily damaged by the the fine probes usually used in scanning transmission electron microscopy to acquire ELNES data. Thus an alternative method using a Gatan im

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35

Perrot, Antoine, Olivier Pannekoucke, and Vincent Guidard. "Toward a multivariate formulation of the parametric Kalman filter assimilation: application to a simplified chemical transport model." Nonlinear Processes in Geophysics 30, no. 2 (2023): 139–66. http://dx.doi.org/10.5194/npg-30-139-2023.

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Abstract. This contribution explores a new approach to forecasting multivariate covariances for atmospheric chemistry through the use of the parametric Kalman filter (PKF). In the PKF formalism, the error covariance matrix is modellized by a covariance model relying on parameters, for which the dynamics are then computed. The PKF has been previously formulated in univariate cases, and a multivariate extension for chemical transport models is explored here. This contribution focuses on the situation where the uncertainty is due to the chemistry but not due to the uncertainty of the weather. To

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36

Qin, Ke, Raofen Wang, and Yu Zhang. "Filter Bank-Driven Multivariate Synchronization Index for Training-Free SSVEP BCI." IEEE Transactions on Neural Systems and Rehabilitation Engineering 29 (2021): 934–43. http://dx.doi.org/10.1109/tnsre.2021.3073165.

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37

Dong, Wenhui, and Xingbao Gao. "Error estimate for the approximate solution to multivariate feedback particle filter." Pure and Applied Mathematics Quarterly 18, no. 3 (2022): 1113–46. http://dx.doi.org/10.4310/pamq.2022.v18.n3.a9.

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38

Dong, Qi, and Xiangbo Liu. "Multivariate filter estimation and ARDL model analysis of China’s potential output." Applied Economics Letters 25, no. 18 (2017): 1327–32. http://dx.doi.org/10.1080/13504851.2017.1420873.

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39

Wu, Wen, Sarah C. Rutan, Antonietta Baldovin, and Désiré-Luc Massart. "Feature selection using the Kalman filter for classification of multivariate data." Analytica Chimica Acta 335, no. 1-2 (1996): 11–22. http://dx.doi.org/10.1016/s0003-2670(96)00347-9.

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40

KOH, MIN-SUNG, DANILO P. MANDIC, and ANTHONY G. CONSTANTINIDES. "THEORY OF DIGITAL FILTER BANKS REALIZED VIA MULTIVARIATE EMPIRICAL MODE DECOMPOSITION." Advances in Adaptive Data Analysis 06, no. 01 (2014): 1450001. http://dx.doi.org/10.1142/s1793536914500010.

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Undecimated and decimated multivariate empirical mode decomposition filter banks (MEMDFBs) are introduced in order to incorporate MEMD equipped with downsampling into any arbitrary tree structure and provide flexibility in the choice of frequency bands. Undecimated MEMDFBs show the same results as those of original MEMD for an octave tree structure. Since the exact cut-off frequencies of MEMD are not known (i.e. due to data-driven decomposition), employing just simple downsampling in MEMD might cause aliasing. However, decimated MEMDFBs in this paper achieve perfect reconstruction with aliasin

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41

Borowski, Matthias, Karen Schettlinger, and Ursula Gather. "Multivariate Real-Time Signal Extraction by a Robust Adaptive Regression Filter." Communications in Statistics - Simulation and Computation 38, no. 2 (2009): 426–40. http://dx.doi.org/10.1080/03610910802514972.

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42

Prats-Montalbán, José Manuel, Marina Cocchi, and Alberto Ferrer. "N-way modeling for wavelet filter determination in multivariate image analysis." Journal of Chemometrics 29, no. 6 (2015): 379–88. http://dx.doi.org/10.1002/cem.2717.

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Huang, Wei, Hongpo Fu, Yu Li, and Weiguo Zhang. "A Gaussian-multivariate Laplacian mixture distribution based robust cubature Kalman filter." Measurement 213 (May 2023): 112732. http://dx.doi.org/10.1016/j.measurement.2023.112732.

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Lim, Jong Gwan, Mi-hye Kim, and Sahngwoon Lee. "Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/280140.

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Recent change in evaluation criteria from accuracy alone to trade-off with time delay has inspired multivariate energy-based approaches in motion segmentation using acceleration. The essence of multivariate approaches lies in the construction of highly dimensional energy and requires feature subset selection in machine learning. Due to fast process, filter methods are preferred; however, their poorer estimate is of the main concerns. This paper aims at empirical validation of three objective functions for filter approaches, Fisher discriminant ratio, multiple correlation (MC), and mutual infor

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45

Li, Mingai, Ruotu Wang, Jinfu Yang, and Lijuan Duan. "An Improved Refined Composite Multivariate Multiscale Fuzzy Entropy Method for MI-EEG Feature Extraction." Computational Intelligence and Neuroscience 2019 (March 28, 2019): 1–12. http://dx.doi.org/10.1155/2019/7529572.

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Feature extraction of motor imagery electroencephalogram (MI-EEG) has shown good application prospects in the field of medical health. Also, multivariate entropy-based feature extraction methods have been gradually applied to analyze complex multichannel biomedical signals, such as EEG and electromyography. Compared with traditional multivariate entropies, refined composite multivariate multiscale fuzzy entropy (RCmvMFE) overcomes the defect of unstable entropy values caused by the scale factor increase and is beneficial towards obtaining richer feature information. However, the coarse-grained

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Burtseva, Tatyana, Nataliya Mironova, Elena Volk, and Alexey Chaykovskiy. "Marketing assessment of innovation potential of water filter manufacturers." E3S Web of Conferences 258 (2021): 06067. http://dx.doi.org/10.1051/e3sconf/202125806067.

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The study focuses on analyzing the products of water filter manufacturers using marketing tools. In the course of the study, factorial, cluster, regression analysis, as well as multivariate scaling were used. As a result, it was revealed that 65% of buyers rely on 4 main factors when buying filter products: price-value ratio, assortment depth, assortment saturation, and advertising support.

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Vezzulli, Fosca, Gabriele Rocchetti, Milena Lambri, and Luigi Lucini. "Metabolomics Combined with Sensory Analysis Reveals the Impact of Different Extraction Methods on Coffee Beverages from Coffea arabica and Coffea canephora var. Robusta." Foods 11, no. 6 (2022): 807. http://dx.doi.org/10.3390/foods11060807.

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An untargeted metabolomics approach combined with sensory analysis was used to depict the impact of different traditional Italian extraction methods (i.e., Espresso, Neapolitan, Moka) along with Filter, on Coffea arabica and Coffea canephora var. robusta beverages. To this aim, polyphenols, Maillard reaction products, and coffee metabolites were screened by high resolution mass spectrometry and elaborated through both unsupervised and supervised multivariate statistical approaches. Multivariate statistics showed a distinctive chemical profile for Espresso preparation, while Moka and Neapolitan

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48

Tropp, Joshua, Michael H. Ihde, Abagail K. Williams, et al. "A sensor array for the discrimination of polycyclic aromatic hydrocarbons using conjugated polymers and the inner filter effect." Chemical Science 10, no. 44 (2019): 10247–55. http://dx.doi.org/10.1039/c9sc03405f.

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Jing, Lili, Lei Yang, Wentao Yang, et al. "Robust Kalman Filter Soil Moisture Inversion Model Using GPS SNR Data—A Dual-Band Data Fusion Approach." Remote Sensing 13, no. 19 (2021): 4013. http://dx.doi.org/10.3390/rs13194013.

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This article aims to attempt to increase the number of satellites that can be used for monitoring soil moisture to obtain more precise results using GNSS-IR (Global Navigation Satellite System-Interferometric Reflectometry) technology to estimate soil moisture. We introduce a soil moisture inversion model by using GPS SNR (Signal-to-Noise Ratio) data and propose a novel Robust Kalman Filter soil moisture inversion model based on that. We validate our models on a data set collected at Lamasquère, France. This paper also compares the precision of the Robust Kalman Filter model with the conventio

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Metref, S., E. Cosme, C. Snyder, and P. Brasseur. "A non-Gaussian analysis scheme using rank histograms for ensemble data assimilation." Nonlinear Processes in Geophysics 21, no. 4 (2014): 869–85. http://dx.doi.org/10.5194/npg-21-869-2014.

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Abstract. One challenge of geophysical data assimilation is to address the issue of non-Gaussianities in the distributions of the physical variables ensuing, in many cases, from nonlinear dynamical models. Non-Gaussian ensemble analysis methods fall into two categories, those remapping the ensemble particles by approximating the best linear unbiased estimate, for example, the ensemble Kalman filter (EnKF), and those resampling the particles by directly applying Bayes' rule, like particle filters. In this article, it is suggested that the most common remapping methods can only handle weakly non

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