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Fusion Estimation of Point Sets from Multiple Stations of Spherical Coordinate Instruments Utilizing Uncertainty Estimation Based on Monte Carlo
2012
Measurement Science Review
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Simulation and experiments prove that the fusion method improves the precision of the measurements of an object's location, due to incorporating the degree of uncertainty for each measurement point. ...
Simulation of the fusion algorithms is performed using laser tracking and laser radar. The fusion algorithm experiments are performed using two laser tracking stations. ...
Two laser tracker stations were used in this experiment. We can conclude that the fusion method provides an improved degree of precision over simply averaging measured values. ...
doi:10.2478/v10048-012-0009-6
fatcat:sxs3dlgdyracrmykounjcq5rk4
Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function
2017
Journal of Control Science and Engineering
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Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. ...
Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. ...
For any state vector, all primitive data has a predictive output after being trained and predicted by LIBSVM, so a nonlinear observation equation can be established as formula (20) . ...
doi:10.1155/2017/3614790
fatcat:almujbijqzemzhp6eqqyuut5eq
Exploration of Neural Activity under Cognitive Reappraisal Using Simultaneous EEG-fMRI Data and Kernel Canonical Correlation Analysis
2018
Computational and Mathematical Methods in Medicine
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A kernel-based canonical correlation analysis is utilized to fuse nonlinear EEG-fMRI data. Results. ...
It is also suitable for other neuroimaging technologies using simultaneous EEG-fMRI data. ...
However, nonlinearity of the EEG-fMRI data may decrease the fusion accuracy. Thus, we improve the CCA fusion with a kernel strategy. It is not very novel but is effective. ...
doi:10.1155/2018/3018356
pmid:30065778
pmcid:PMC6051320
fatcat:hwvmyqd7lvhqvgfnhi6qgmp5uq
Temperature Sequential Data Fusion Algorithm Based on Cluster Hierarchical Sensor Networks
2020
Sensors
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The sequential observation fusion estimator (SOFE) algorithm is embedded in the measurement update to improve the performance of local measurement fusion. ...
of nonlinear modeling errors. ...
to improve the identification of nonlinear modeling errors. ...
doi:10.3390/s20164533
pmid:32823567
fatcat:l2ebicjrlvbahip555zu72kkci
Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion
2015
Mathematical Problems in Engineering
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analysis to effectively integrate observational data from multiple sensors. ...
In order to improve the reliability of measurement data, the multisensor data fusion technology has progressed greatly in improving the accuracy of measurement data. ...
Acknowledgments The authors would like to thank the anonymous reviewers for helpful comments which helped them improve the technical quality of the paper. ...
doi:10.1155/2015/854085
fatcat:udm34yfw3bdrdoez2pbwpcgj5i
Tire Road Friction Coefficient Estimation: Review and Research Perspectives
2022
Chinese Journal of Mechanical Engineering
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These methods are divided into three main categories: off-board sensors-based, vehicle dynamics-based, and data-driven-based methods. ...
Therefore, accurate knowledge of TRFC contributes to the optimization of driver maneuvers for further improving the safety of intelligent vehicles. ...
perceptron neural network [110] 14 Active front steering model Frequency domain data fusion [100] 15 Planar vehicle model Nonlinear observer [108] 16 Three DOF vehicle model Limited-memory adaptive EKF ...
doi:10.1186/s10033-021-00675-z
fatcat:3zxr5ezxy5djrp6pehoobropxm
Fusion Feature Extraction Based on Auditory and Energy for Noise-Robust Speech Recognition
2019
IEEE Access
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Principal component analysis (PCA) is then applied to feature selection and optimization of the feature set, and the final feature set is used in a non-specific persons, isolated words, and smallvocabulary ...
In this paper, a robust fusion feature is proposed that can fully characterize speech information. ...
It can be observed from Table 6 that after the fusion feature is optimized by PCA, the recognition rate is improved. ...
doi:10.1109/access.2019.2918147
fatcat:nru44nprjfhyxplz3zkybfwabm
A Data Fusion Algorithm Based on Neural Network Research in Building Environment of Wireless Sensor Network
2015
International Journal of Future Generation Communication and Networking
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In order to build high performance of data fusion system, a data fusion algorithm using BP neural network to optimize fuzzy prediction and train the membership degree of collecting data is presented, which ...
is used to determine which kind of dividing fusion mechanism is belonged for the sensor's data collected at a given moment. ...
fusion and further improve the accuracy of data fusion. ...
doi:10.14257/ijfgcn.2015.8.4.29
fatcat:ssradz34fncehkmaaspkyeie2y
The Spatial Form of Digital Nonlinear Landscape Architecture Design Based on Computer Big Data
2021
Applied Mathematics and Nonlinear Sciences
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The article uses the colour zoning method to design the actual scene of the garden landscape with nonlinear parameteriszation. ...
The simulation result analyses that the proposed nonlinear algorithm has realised the efficiency improvement purpose of landscape architecture design. ...
This paper proposes a multi-dimensional nonlinear landscape design method based on parameterised models to improve the quantitative analysis ability. 2 Multi-dimensional nonlinear landscape image analysis ...
doi:10.2478/amns.2021.1.00069
fatcat:w6sjtu75lfh6zhkueiqvnviwqm
Research on Data Fusion of Photoelectric Measuring Instrument Based on UKF Algorithm
2022
Security and Communication Networks
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The UKF algorithm-based data fusion technique was researched in this work in order to tackle the issues of conventional data fusion methods such as lengthy fusion processes, high recall rates of findings ...
On the basis of UKF filtering operation on the data sample set, the fusion processing of photoelectric measurement instrument is completed through the steps of data pretreatment, vertical and horizontal ...
It is important to detect the parameter states in the data source used for matching and to assess the differences between various kinds of data by adjusting the difference degree of longitudinal data fusion ...
doi:10.1155/2022/1384366
fatcat:xphnnxut3bhexcef74e6u6cmgi
A Novel Algorithm for Satellite Images Fusion Based on Compressed Sensing and PCA
2013
Mathematical Problems in Engineering
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In the algorithm we use Hama Da matrix as the measurement matrix and SAMP as the reconstruction algorithm and adopt an improved fusion rule based on the local variance. ...
Based on the classic fusion algorithms on remote sensing image fusion, the PCA (principal component analysis) transform, and discrete wavelet transform, we carry out in-depth research. ...
Traditional sampling recovery uses linear interpolation of SINC function to obtain signal, but CS theory turns to solve highly nonlinear optimization problem from the current observed data to get signal ...
doi:10.1155/2013/708985
fatcat:y3twl3n735dibdafh3h6josgvm
Multi-resolution analysis techniques and nonlinear PCA for hybrid pansharpening applications
2015
Multidimensional systems and signal processing
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Finally the inverse projection is used to obtain the enhanced image in the original data space. ...
In general, in a hybrid approach a CS technique is used to project the original data into a low dimensionality space. Thus, the PAN image is fused with one or more features by means of MRA approach. ...
As it can be clearly seen, the use of NLPCA extremely improves the computational efficiency of the fusion process. ...
doi:10.1007/s11045-015-0359-y
fatcat:d6fbfhqxo5ejtgprfg3z4f5hw4
Research on the B2C Online Marketing Effect Based on the LS-SVM Algorithm and Multimodel Fusion
2021
Mathematical Problems in Engineering
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through data collection and verification. ...
Through verification, it shows that the lower the correlation degree, the better the model prediction effect. ...
discriminant analysis with multiple observation samples and multiple model fusion. ...
doi:10.1155/2021/8186849
fatcat:ektuadsqgrbpbo7qz7445s3eze
A New View of Multisensor Data Fusion: Research on Generalized Fusion
2021
Mathematical Problems in Engineering
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Firstly, the development and definition of multisensor data fusion are analyzed and the definition of multisensor data generalized fusion is given. ...
Then, the principle and architecture of multisensor data fusion are analyzed, and a generalized multisensor data fusion model is presented based on the JDL model. ...
algorithms are still missing. e development and improvement of the basic theory of data fusion are key factors for the rapid development of this field. ( 6 ) Improve the fusion algorithm to improve the ...
doi:10.1155/2021/5471242
fatcat:irxnbl65nvao5g4o4ywkj6jazu
Sensor Data Fusion by Support Vector Regression Methodology—A Comparative Study
2015
IEEE Sensors Journal
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Multi-sensor data fusion can be considered as a strong nonlinear system. ...
This paper presents the Support Vector Regression (SVR) methodology for sensor fusion to improve tracking ability. ...
An algorithm which combines a fuzzy adaptive system and wavelet analysis to form a data fusion technique for the target tracking system was presented in [4] . ...
doi:10.1109/jsen.2014.2356501
fatcat:3iczysgu45cafkgpxso6nyozo4
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