Search Results - (( square estimation method algorithm ) OR ( data detection method algorithm ))
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1
Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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2
Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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3
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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4
Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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5
Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…It can be concluded that the modified algorithm decreases the biases, the variances and the mean squared errors of the LTS estimators. …”
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6
Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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7
Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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8
Power System State Estimation In Large-Scale Networks
Published 2010“…SE requires to use various techniques to ensure validity of the results and to detect and identify sources of errors. The Weighted Least Squares (WLS) method is the most popular technique of SE. …”
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9
The largest studentized residual test for bad data identification in state estimation of a power system
Published 2015“…The presence of systematic errors can alter the results of state estimation. The chi-square and normalized residual tests are the common post estimation procedures usually used for detection and identification of gross errors in the estimation algorithm. …”
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10
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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11
Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors
Published 2010“…The ordinary Nonlinear Least Squares (NLLS) and the Maximum Likelihood Estimator (MLE) techniques are often used to estimate the parameters of nonlinear models. …”
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12
Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…Simple mediation model consists of three regression equations. The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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13
Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. …”
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14
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. …”
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15
Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…However, most of existing damage detection methods requires reference data which are not always available. …”
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16
Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. …”
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17
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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18
Benthic habitat mapping and coral bleaching detection using quickbird imagery and Kd algorithm
Published 2013“…Half numbers of these points were selected to determine the mentioned parameters using minimizing the sum of the squared residuals, and the other points were used for accuracy assessment of the applied method. …”
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19
Modified sequential fences for identifying univariate outliers
Published 2016“…In addition, this proposed method also estimates trimmed mean and trimmed standard deviation with smaller bias and smaller root of mean squares error. …”
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20
Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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