Academic literature on the topic 'Error vector'

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Journal articles on the topic "Error vector"

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Yuan, Tianqing, and Dazhi Wang. "Performance Improvement for PMSM DTC System through Composite Active Vectors Modulation." Electronics 7, no. 10 (2018): 263. http://dx.doi.org/10.3390/electronics7100263.

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In this paper, a novel direct torque control (DTC) scheme based on composite active vectors modulation (CVM) is proposed for permanent magnet synchronous motor (PMSM). The precondition of the accurate compensations of torque error and flux linkage error is that the errors can be compensated fully during the entire control period. Therefore, the compensational effects of torque error and flux linkage error in different operating conditions of the PMSM are analyzed firstly, and then, the operating conditions of the PMSM are divided into three cases according to the error compensational effects.
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Kozicki, Sharon, and P. A. Tinsley. "Vector rational error correction." Journal of Economic Dynamics and Control 23, no. 9-10 (1999): 1299–327. http://dx.doi.org/10.1016/s0165-1889(98)00075-x.

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Liu, Ji Ping, and Bo Wang. "An Improved Error Concealment Algorithm for Wireless Video Applications." Advanced Materials Research 171-172 (December 2010): 531–35. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.531.

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This paper develops a new error concealment algorithm for the whole-frame losses in wireless video transmission based on H.264/AVC.At first,we propose a forward motion vector extrapolation algorithm based on variable-size block motion vector estimation to obtain the motion vector field of the loss frame without yielding the hole problems. Then, we partition the missing frame into several object regions by clustering the motion vectors, furthermore, we apply median filter to reconstruct the motion vectors for hole areas based on the reliabilities of neighboring motion vectors. Finally, all macr
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CHAITRALI, S. SHEDGE, and H. MADHAVI RAJENDRA. "THREE-LEVEL INVERTER CONTROLLED BY MEANS OF HYSTERESIS CURRENT CONTROL. APPLICATION TO GRID INTEGRATION." JournalNX - A Multidisciplinary Peer Reviewed Journal 2, no. 9 (2016): 5–9. https://doi.org/10.5281/zenodo.1468160.

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This paper describes the operational analysis results of a grid integration of distributed generation sources with an AC grid using multilevel inverter. The multilevel inverter is a three-level voltage source inverter (VSI), which is controlled by means of a novel vector hysteresis current control (V.H.C.C). The proposed V.H.C.C, which is based on error square areas, controls the three-phase load AC currents. The three load current errors are gathered into a single space vector quantity. In this case, the magnitude of the error vector is limited within boundary areas of a square shape. The con
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Wang, Qi, Yingmin Wang, and Guolei Zhu. "Underwater High Precision Wireless Acoustic Positioning Algorithm Based on L-p Norm." Symmetry 16, no. 7 (2024): 890. http://dx.doi.org/10.3390/sym16070890.

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Underwater wireless acoustic positioning technology uses the geometric relationship between a target and a receiving array to determine the target’s position by measuring distances between the target and the array elements, that the receiving array is usually symmetry in space. It is an indirect measurement approach, so ranging errors can significantly impact positioning accuracy due to error transmission effects. To improve precision, a similarity-matched localization algorithm based on the L-p norm (LPM) is introduced. This algorithm constructs a distance vector model with environmental para
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Wang, Dazhi, Tianqing Yuan, Xingyu Wang, Xinghua Wang, and Wenhui Li. "A Composite Vectors Modulation Strategy for PMSM DTC Systems." Energies 11, no. 10 (2018): 2729. http://dx.doi.org/10.3390/en11102729.

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The operation performance of permanent magnet synchronous motors (PMSMs) driven by direct torque control (DTC) are affected by torque error compensation and flux error compensation in each control period. The error compensational effects provided by different vectors under different control strategies are analyzed in this paper. The precondition of accurate error compensation is applied to the proposed novel composite vectors modulation strategy (CVM) for a PMSM DTC system. In CVM-DTC, the operating conditions of PMSM are divided into three cases according to the relationships between the erro
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Wang, Peng, Yujun Kong, and Mingxing Zhang. "Error Self-Calibration Algorithm for Acoustic Vector Sensor Array." Journal of Sensors 2019 (September 4, 2019): 1–10. http://dx.doi.org/10.1155/2019/9052547.

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In this paper, the errors of acoustic vector sensor array are classified, the impact factor of each error for the array signal model is derived, and the influence of each type of error on the direction-of-arrival (DOA) estimation performance of the array is compared by Monte Carlo experiments. Converting the directional error and location error to amplitude and phase errors, the optimization model and error self-calibration algorithm for acoustic vector sensor array are proposed. The simulation experiments and field experiment data processing of MEMS vector sensor array show that the proposed
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Butcher, Daniel, and Adrian Spencer. "Spurious PIV Vector Correction Using Linear Stochastic Estimation." Fluids 4, no. 3 (2019): 139. http://dx.doi.org/10.3390/fluids4030139.

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Techniques for the experimental determination of velocity fields such as particle image velocimetry (PIV) can often be hampered by spurious vectors or sparse regions of measurement which may occur due to a number of reasons. Commonly used methods for detecting and replacing erroneous values are often based on statistical measures of the surrounding vectors and may be influenced by further poor data quality in the region. A new method is presented in this paper using Linear Stochastic Estimation for vector replacement (LSEVR) which allows for increased flexibility in situations with regions of
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Turner, A. J., and D. J. Jacob. "Balancing aggregation and smoothing errors in inverse models." Atmospheric Chemistry and Physics Discussions 15, no. 1 (2015): 1001–26. http://dx.doi.org/10.5194/acpd-15-1001-2015.

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Abstract. Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a
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Turner, A. J., and D. J. Jacob. "Balancing aggregation and smoothing errors in inverse models." Atmospheric Chemistry and Physics 15, no. 12 (2015): 7039–48. http://dx.doi.org/10.5194/acp-15-7039-2015.

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Abstract. Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a
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Dissertations / Theses on the topic "Error vector"

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Sharp, Gary David. "Lag length selection for vector error correction models." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1002808.

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This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong supp
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Ren, Yueming Carleton University Dissertation Geography. "Vector data topological encoding error handling and generalization." Ottawa, 1992.

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DONELLI, NICOLA. "Bayesian semiparametric analysis of vector Multiplicative Error Models." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/95879.

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The purpose of our research is to generalize the semiparametric Bayesian MEM of Mira and Solgi (2013) to a multivariate setting, namely vector MEM (vMEM). In the proposed vMEM, given the information set available at time t-1, the positive data vector at time t is modeled as the element-by-element product of a conditional mean vector and a random vector of innovations. In our approach, the process of innovations is an i.i.d. vector process from a unit mean multivariate distribution supported on the positive orthant. We model this distribution nonparametrically, using a Dirichlet process mixture
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Molin, Simon. "House Price Dynamics in Sweden : Vector error-correction model." Thesis, Umeå universitet, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172367.

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Movements in house prices can have effects on individuals, financial markets, and the whole economy. After the rapid increase in house prices worldwide since the mid-1990s and after the financial crisis in 2008, many studies have investigated house price dynamics. Furthermore, real house prices in Sweden have increased by more than 200 % since the mid-1990s up until today. This study takes a closer look at the fundamental determinants of house prices to investigate both the long- and short-run dynamics of Swedish house prices. The method of use includes a vector error-correction model, which e
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Lau, Cidney. "Support Vector Machine Algorithm applied to Industrial Robot Error Recovery." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172331.

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A Machine Learning approach for error recovery in an industrial robot for the plastic mold industry isproposed in this master thesis project. The goal was to improve the present error recovery method byproviding a learning algorithm to the system instead of using the traditional algorithm-based control.The chosen method was the Support Vector Machine (SVM) due to the robustness and the goodgeneralization performance in real-world applications. Furthermore, SVM generates good classifierseven with a minimal number of training examples. In production, there will be no need for a humanoperator to
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Love, Kimberly R. "Modeling Error in Geographic Information Systems." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/29900.

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Geographic information systems (GISs) are a highly influential tool in today's society, and are used in a growing number of applications, including planning, engineering, land management,and environmental study. As the field of GISs continues to expand, it is very important to observe and account for the error that is unavoidable in computerized maps. Currently, both statistical and non-statistical models are available to do so, although there is very little implementation of these methods. In this dissertation, I have focused on improving the methods available for analyzing error in GIS ve
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Bozantzis, Vasilios. "Integrated vector encoding-decoding designs for non-stationary sources and noisy channels." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366056.

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Damera-Venkata, Niranjan. "Analysis and design of vector error diffusion systems for image halftoning /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004247.

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Eidestedt, Richard, and Stefan Ekberg. "Evaluating forecast accuracy for Error Correction constraints and Intercept Correction." Thesis, Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-194423.

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This paper examines the forecast accuracy of an unrestricted Vector Autoregressive (VAR) model for GDP, relative to a comparable Vector Error Correction (VEC) model that recognizes that the data is characterized by co-integration. In addition, an alternative forecast method, Intercept Correction (IC), is considered for further comparison. Recursive out-of-sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VEC models cons
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Silber, Frank. "Makroökonometrische Anpassungsanalyse im Vector-Error-Correction-Model (VECM) : Untersuchungen an ausgewählten Arbeitsmärkten /." Frankfurt am Main: Lang, 2003. http://www.gbv.de/dms/zbw/362076561.pdf.

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Books on the topic "Error vector"

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Cipollini, Fabrizio. Vector multiplicative error models: Representation and inference. National Bureau of Economic Research, 2006.

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Stark, Tom. A Bayesian vector error corretions model of the U.S. economy. Federal Reserve Bank of Philadelphia, Economic Research Division, 1998.

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Vlaar, P. J. G. Monetary transmission and controllability of money in Europe: A structural vector error correction approach. De Nederlandsche Bank NV, 1999.

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Hyder, Kalim. Crowding out hypothesis in a vector error correction frame work, a case study of Pakistan. Social Policy and Development, 2002.

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Anderson, Richard G. Analysis of panel vector error correction models using maximum likelihood, the bootstrap, and canonical-correlation estimators. Federal Reserve Bank of St. Louis, 2006.

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Lloyd, Tim. Testing a capital pricing model of land values: Cointegration and error correction in a vector auto-regression. Department of Economics, University of Nottingham, 1992.

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Mohey-ud-din, Ghulam. The Macroeconomic Analysis of Foreign Capital Inflows in Pakistan: A Re-Examination Using Vector Error Correction Approach. Grin Verlag, 2011.

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S, Madheswaran, and Institute for Social and Economic Change, eds. Casuality between energy consumption and output growth in Indian cement industry: An application of panel vector error correction model. Institute for Social and Economic Change, 2010.

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F, Huang Y., Stevenson Robert L, and United States. National Aeronautics and Space Administration., eds. [An efficient system for reliably transmitting image and video data over low bit rate noise]: An interim report. National Aeronautics and Space Administration, 1994.

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Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluati
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Book chapters on the topic "Error vector"

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Beenstock, Michael, and Daniel Felsenstein. "Spatial Vector Error Correction." In Advances in Spatial Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03614-0_9.

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Lütkepohl, Helmut. "Vector Error Correction Models." In New Introduction to Multiple Time Series Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-27752-1_6.

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Hautsch, Nikolaus. "Vector Multiplicative Error Models." In Econometrics of Financial High-Frequency Data. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21925-2_7.

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Maitra, Sarit. "Vector Auto Regression and Vector Error Correction Model." In Contributions to Economics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86862-7_7.

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Che-Shing, Chen, Chen Mei-Juan, Huang Chin-Hui, and Sun Shih-Ching. "Motion Vector Based Error Concealment Algorithms." In Advances in Multimedia Information Processing — PCM 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36228-2_53.

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Das, Panchanan. "Cointegration, Error Correction and Vector Autoregression." In Econometrics in Theory and Practice. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9019-8_12.

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Reynoso Hernández, J. Apolinar, and Manuel Alejandro Pulido Gaytan. "Error Models for Vector Network Analyzers." In Principles and Applications of Vector Network Analyzer Calibration Techniques. River Publishers, 2024. http://dx.doi.org/10.1201/9788770046350-2.

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Lütkepohl, Helmut. "Estimation of Vector Error Correction Models." In New Introduction to Multiple Time Series Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-27752-1_7.

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Sakata, Shojiro. "Finding a minimal polynomial vector set of a vector of nD arrays." In Applied Algebra, Algebraic Algorithms and Error-Correcting Codes. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54522-0_129.

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Gherghina, Ştefan Cristian. "A Vector Error Correction Model (VECM) Approach." In Sustainable Finance. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-43864-6_3.

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Conference papers on the topic "Error vector"

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Yu, Xiaoyu, Hao Zeng, Lianping Guo, et al. "Research and application of intelligent vector signal error calibration method." In 2024 IEEE AUTOTESTCON. IEEE, 2024. http://dx.doi.org/10.1109/autotestcon47465.2024.10697508.

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Li, Peijiong, Mingyang Huang, Zhangjun Yu, and Jun Yang. "Polarization adjustment-free optical vector analyzer using cascade polarization maintaining interferometers." In Optical Fiber Sensors. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/ofs.2023.tu3.51.

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To eliminate the polarization misalignment error of a conventional optical vector analyzer, we proposed a polarization-maintaining configuration and a suppression algorithm for polarization crosstalk-induced error. The method’s validity and repeatability are verified and evaluated, respectively.
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Gerhardt, Jérémie, and Jon Y. Hardeberg. "Controlling the error in spectral vector error diffusion." In Electronic Imaging 2007, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 2007. http://dx.doi.org/10.1117/12.703816.

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Pervere, Michael, and John Barr. ""Advances in Vector Error Correction"." In 29th ARFTG Conference Digest. IEEE, 1987. http://dx.doi.org/10.1109/arftg.1987.323859.

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Fan, Zhigang. "Analysis of color error diffusion with vector error filters." In Electronic Imaging 2006, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 2006. http://dx.doi.org/10.1117/12.646380.

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Suh, Jae-Won, Eung-Tae Kim, Seung-Jong Choi, Hee-Bok Park, and Yo-Sung Ho. "Motion vector recovery for error concealment." In Electronic Imaging '99, edited by Kiyoharu Aizawa, Robert L. Stevenson, and Ya-Qin Zhang. SPIE, 1998. http://dx.doi.org/10.1117/12.334717.

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Manurkar, Paritosh, Christopher P. Silva, Joshua Kast, Robert D. Horansky, Dylan F. Williams, and Kate A. Remley. "Reference Measurements of Error Vector Magnitude." In 2022 IEEE/MTT-S International Microwave Symposium - IMS 2022. IEEE, 2022. http://dx.doi.org/10.1109/ims37962.2022.9865278.

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Scholkopf, B. "Kernel-dependent support vector error bounds." In 9th International Conference on Artificial Neural Networks: ICANN '99. IEE, 1999. http://dx.doi.org/10.1049/cp:19991092.

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Thepade, Sudeep D., Vandana Mhaske, and Vedant Kurhade. "Thepade's Hartley Error Vector Rotation for codebook generation in Vector Quantization." In 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2013. http://dx.doi.org/10.1109/icacci.2013.6637490.

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Lu, Shuxia, Pu Shi, and Ming Chen. "Support Vector Machine for Suppressing Error Method." In 2009 First International Conference on Information Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/icise.2009.1149.

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Reports on the topic "Error vector"

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Smith, D. L., and L. P. Geraldo. A vector model for error propagation. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/6402022.

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Cipollini, Fabrizio, Robert Engle, and Giampiero Gallo. Vector Multiplicative Error Models: Representation and Inference. National Bureau of Economic Research, 2006. http://dx.doi.org/10.3386/t0331.

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Cipollini, Fabrizio, Robert Engle, and Giampiero Gallo. Vector Multiplicative Error Models: Representation and Inference. National Bureau of Economic Research, 2006. http://dx.doi.org/10.3386/w12690.

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Anderson, Richard G., Dennis Hoffman, and Robert H. Rasche. A Vector Error-Correction Forecasting Model of the U.S. Economy. Federal Reserve Bank of St. Louis, 1998. http://dx.doi.org/10.20955/wp.1998.008.

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Hoffman, Dennis, and Robert H. Rasche. STLS/US-VECM 6.1: A Vector Error-Correction Forecasting Model of the US Economy. Federal Reserve Bank of St. Louis, 1997. http://dx.doi.org/10.20955/wp.1997.008.

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Han, Jieying, Brett T. Walkenhorst, and Enkuang D. Wang. Adaptive Modulation Schemes for OFDM and SOQPSK Using Error Vector Magnitude (EVM) and Godard Dispersion. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada619898.

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Anderson, Richard G., Hailong Qian, and Robert H. Rasche. Analysis of Panel Vector Error Correction Models Using Maximum Likelihood, the Bootstrap, and Canonical Correlation Estimators. Federal Reserve Bank of St. Louis, 2006. http://dx.doi.org/10.20955/wp.2006.050.

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Lunsford, Kurt G. Business Cycles and Low-Frequency Fluctuations in the US Unemployment Rate. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202319.

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I show that business cycles can generate most of the low-frequency movements in the unemployment rate. First, I provide evidence that the unemployment rate is stationary, while its flows have unit roots. Then, I model the log unemployment rate as the error correction term of log labor flows in a vector error correction model (VECM) with intercepts that change over the business cycle. Feeding historical expansions and recessions into the VECM generates large low-frequency movements in the unemployment rate. Frequent recessions from the late 1960s to the early 1980s interrupt labor market recove
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Ahwireng-Obeng, Asabea Shirley, and Frederick Ahwireng-Obeng. Private Philanthropic Cross-Border Flows and Sustainable Development in Africa. Centre on African Philanthropy and Social Investment, 2011. http://dx.doi.org/10.47019/2021.ra1.

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The paper examines the simultaneous impact of private philanthropic cross-border funding from international foundations on the economic, social, and environmental dimensions of sustainable development in Africa. The vector error correction model (VECM) was used, and contrary to expectations drawn from past studies, funding from this source improves economic growth, advances human development, and enhances environmental quality. Causality test results also disconfirmed the assumption that interactions among the three dimensions were positive and complementary in the long term. The environment v
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Salazar-Díaz, Andrea, Aaron Levi Garavito Acosta, Sergio Restrepo-Ángel, and Leidy Viviana Arcila-Agudelo. Real Equilibrium Exchange Rate in Colombia: Thousands of VEC Models Approach. Banco de la República Colombia, 2022. http://dx.doi.org/10.32468/be.1221.

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Behavioral Equilibrium Exchange Rate (BEER) models suggest many variables as potential drivers of equilibrium real exchange rates (ERER). This gives rise to model uncertainty issues, as ERER depends and varies, often drastically, on a particular set of chosen variables. We address this issue by estimating thousands of Vector Error Correction (VEC) specifications for Colombian data between 2000Q1-2019Q4. According to an extensive literature review, we employ thirty-five proxies categorized among five fixed groups of economic fundamentals that underlie the ERER: Indebtedness, Fiscal sector, Prod
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