Walking-Age Estimator Based on Gait Parameters Using Kernel Regression by Tomohito Kuroda, Shogo Okamoto, Yasuhiro Akiyama

Subjects: “…kernel regression…”
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Asymptotic Normality of Nonparametric Kernel Regression Estimation for Missing at Random Functional Spatial Data by Fatimah Alshahrani, Ibrahim M. Almanjahie, Tawfik Benchikh, Omar Fetitah, Mohammed Kadi Attouch

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MODELING GENDER DEVELOPMENT INDEX IN SOUTHEAST SULAWESI PROVINCE USING SEMIPARAMETRIC KERNEL REGRESSION by Andi Tenri Ampa, Lilis Laome, Muhammad Ridwan, Baharuddin Baharuddin, Makkulau Makkulau

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Predictive modelling of graphene-enhanced greases using classical feedback control and quantum kernel regression by Ethan Stefan-Henningsen, Amirkianoosh Kiani

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Fault Detection Method Using Auto-Associative Shared Nearest Neighbor Kernel Regression for Industrial Processes by Minseok Kim, Eunkyeong Kim, Seunghwan Jung, Baekcheon Kim, Jinyong Kim, Sungshin Kim

Subjects: “…auto-associative kernel regression…”
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KLASIFIKASI DATA PERKAWINAN ANAK DI MALUKU UTARA DENGAN METODE KERNEL REGRESSION DAN SUPPORT VECTOR MACHINE by Arifin M Kahar

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Limit Theorems for Kernel Regression Estimator for Quasi-Associated Functional Censored Time Series Within Single Index Structure by Said Attaoui, Oum Elkheir Benouda, Salim Bouzebda, Ali Laksaci

Subjects: “…kernel regression estimation…”
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A Hybrid Fault Detection Method of Independent Component Analysis and Auto-Associative Kernel Regression for Process Monitoring in Power Plant by Seunghwan Jung, Jonggeun Kim, Sungshin Kim

Subjects: “…auto-associative kernel regression…”
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Radiation Mapping: A Gaussian Multi-Kernel Weighting Method for Source Investigation in Disaster Scenarios by Songbai Zhang, Qi Liu, Jie Chen, Yujin Cao, Guoqing Wang

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APPROXIMATELY SINGULAR WAVELET by V. M. Romanchak

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Singular wavelets on a finite interval by V. M. Romanchak

Subjects: “…nadaraya -watson kernel regression…”
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Wavelet transformation on a finite interval by V. M. Romanchak

Subjects: “…nadaraya − watson kernel regression…”
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Compressive Superresolution Imaging Based on Local and Nonlocal Regularizations by Yicheng Sun, Guohua Gu, Xiubao Sui, Yuan Liu

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Local transformations with a singular wavelet by V. M. Romanchak

Subjects: “…nadaraya − watson kernel regression…”
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Estimation for spatial semi-functional partial linear regression model with missing response at random by Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi

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COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) by Yuniar Farida, Ida Purwanti, Nurissaidah Ulinnuha

“…This study aims to predict the value of ISSI using nonparametric kernel regression. The kernel regression method is one of the nonparametric regression methods used to estimate conditional expectations using kernel functions. …”
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Kernel Density Estimated Linear Regression by Roshan Kalpavruksha, Rohan Kalpavruksha, Teryn Cha, Sung-Hyuk Cha

“… Regression analysis is a cornerstone of predictive modeling, with linear regression and kernel regression standing as two of its most prominent paradigms. …”
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Toward Smart Condition Monitoring of Rotatory Machines: An Optimized Probabilistic Signal Reconstruction Methodology for Fault Prediction With Multisource Uncertainties by Xiaomo Jiang, Weijian Tang, Haixin Zhao, Xueyu Cheng

“…The bandwidth parameter in the auto-associative kernel regression approach was optimized to represent the health status of the rotatory machine. …”
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Approach of target tracking combining particle filter and metric learning by Hongyan WANG, Libin ZHANG, Guoqiang CHEN, Zumin WANG, Zhiyuan GUAN

“…Focusing on the issue of the significant degradation of target tracking performance caused by adverse factors in complex environment, a target tracking method based on particle filtering and metric learning was proposed.First of all, a convolutional neural network (CNN) was offline-trained via the proposed method to effectively obtain the target characteristics.After that, the distance measurement matrix optimization model to minimize the prediction error could be constructed on the basis of the metric learning for kernel regression (MLKR) method, and the resultant model could be handled via using the gradient descent approach to obtain the optimal solution of the candidate target.Moreover, based on the predicted value of the optimal candidate target, the reconstruction error was calculated to construct the target observation model.Finally, a long-short-term update strategy was introduced to achieve the effective target tracking under the particle filter tracking framework.The experiment results show that the proposed method has higher tracking accuracy and better robustness in complex environments.…”
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Approach of target tracking combining particle filter and metric learning by Hongyan WANG, Libin ZHANG, Guoqiang CHEN, Zumin WANG, Zhiyuan GUAN

“…Focusing on the issue of the significant degradation of target tracking performance caused by adverse factors in complex environment, a target tracking method based on particle filtering and metric learning was proposed.First of all, a convolutional neural network (CNN) was offline-trained via the proposed method to effectively obtain the target characteristics.After that, the distance measurement matrix optimization model to minimize the prediction error could be constructed on the basis of the metric learning for kernel regression (MLKR) method, and the resultant model could be handled via using the gradient descent approach to obtain the optimal solution of the candidate target.Moreover, based on the predicted value of the optimal candidate target, the reconstruction error was calculated to construct the target observation model.Finally, a long-short-term update strategy was introduced to achieve the effective target tracking under the particle filter tracking framework.The experiment results show that the proposed method has higher tracking accuracy and better robustness in complex environments.…”
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