Search Results - (( data estimation based algorithm ) OR ( data detection method algorithm ))

Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The proposed algorithm has been applied to detect outliers in the high dimensional data. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

“…This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

“…This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. …”
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Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion by Alam, Mir Suhail, Morshidi, Malik Arman, Gunawan, Teddy Surya, Olanrewaju, Rashidah Funke, Arifin, Fatchul

“…After extensive experiments, the validity of the proposed method was superior to the existing vision-based pose estimation algorithms. …”
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The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

“…This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

“…The predicted and residual values are obtained from an ordinary least squares fit of the data. The algorithm is described and is shown to perform well on classic multiple outlier data sets. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

“…This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

“…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid by Khalid, Nurul Syafiqah

“…The study is to categorize and evaluates methods for automatic tree counting detection. For the methodology of this study, object-based image analysis (OBIA), watershed transformation segmentation and local maxima algorithm are applied. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

“…This research addressed severe contamination or occlusion presence in a face recognition based on image data. A modified version of the existing least trimmed square, LTS method with genetic algorithm (LTS with GAs) was proposed to cater the problem of noise or occlusion and improve the performance of face recognition. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

“…We propose a novel algorithm to estimate heart rate. Also, it can differentiate between a photo of a human face and an actual human face meaning that it can detect false signals and skip them. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

“…When there are missing data in the dataset, TSP may use TSE for estimation of missing data and then performs prediction. …”
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Improved robust principal component analysis based on minimum regularized covariance determinant for the detection of high leverage points in high dimensional data by Habshah Midi, Jaaz Suhaiza, Mohd Aslam, Hani Syahida, Emi Amielda

“…The IRPCA employs the Principal Component Analysis (PCA) to reduce the dimension of the data set and subsequently a robust location and scatter estimates of the PC scores are obtained based on the Minimum Regularized Covariance Determinant (MRCD). …”
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A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets by A. Baba, Ishaq, Midi, Habshah, June, Leong W., Ibragimov, Gafurjan

“…Outlier detection and classification algorithms play a critical role in statistical analysis. …”
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Improved robust principal component analysis based on minimum regularized covariance determinant for the detection of high leverage points in high dimensional data (penambahbaikan... by Midi, Habshah, Suhaiza, Jaaz, Mohd Aslam, ., Hani Syahida, ., Emi Amielda, .

“…The IRPCA employs the Principal Component Analysis (PCA) to reduce the dimension of the data set and subsequently a robust location and scatter estimates of the PC scores are obtained based on the Minimum Regularized Covariance Determinant (MRCD). …”
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