Empirical Mode Decomposition Combined with Local Linear Quantile Regression for Automatic Boundary Correction
Empirical mode decomposition (EMD) is particularly useful in analyzing nonstationary and nonlinear time series. However, only partial data within boundaries are available because of the bounded support of the underlying time series. Consequently, the application of EMD to finite time series data r...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Hindawi Publishing Corporation
2014
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| Online Access: | http://eprints.usm.my/38950/ http://eprints.usm.my/38950/1/Empirical_Mode_Decomposition_Combined_with_Local_Linear_Quantile_Regression_for_Automatic_Boundary_Correction.pdf |
| _version_ | 1848878610667012096 |
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| author | M. Jaber, Abobaker Ismail, Mohd Tahir M. Altaher, Alssaidi |
| author_facet | M. Jaber, Abobaker Ismail, Mohd Tahir M. Altaher, Alssaidi |
| author_sort | M. Jaber, Abobaker |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Empirical mode decomposition (EMD) is particularly useful in analyzing nonstationary and nonlinear time series. However, only
partial data within boundaries are available because of the bounded support of the underlying time series. Consequently, the
application of EMD to finite time series data results in large biases at the edges by increasing the bias and creating artificial wiggles.
This study introduces a newtwo-stagemethod to automatically decrease the boundary effects present inEMD.At the first stage, local
polynomial quantile regression (LLQ) is applied to provide an efficient description of the corrupted and noisy data.The remaining
series is assumed to be hidden in the residuals. Hence, EMD is applied to the residuals at the second stage. The final estimate is
the summation of the fitting estimates from LLQ and EMD. Simulation was conducted to assess the practical performance of the
proposed method. Results show that the proposed method is superior to classical EMD. |
| first_indexed | 2025-11-15T17:34:05Z |
| format | Article |
| id | usm-38950 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:34:05Z |
| publishDate | 2014 |
| publisher | Hindawi Publishing Corporation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-389502018-02-15T00:38:41Z http://eprints.usm.my/38950/ Empirical Mode Decomposition Combined with Local Linear Quantile Regression for Automatic Boundary Correction M. Jaber, Abobaker Ismail, Mohd Tahir M. Altaher, Alssaidi QA1-939 Mathematics Empirical mode decomposition (EMD) is particularly useful in analyzing nonstationary and nonlinear time series. However, only partial data within boundaries are available because of the bounded support of the underlying time series. Consequently, the application of EMD to finite time series data results in large biases at the edges by increasing the bias and creating artificial wiggles. This study introduces a newtwo-stagemethod to automatically decrease the boundary effects present inEMD.At the first stage, local polynomial quantile regression (LLQ) is applied to provide an efficient description of the corrupted and noisy data.The remaining series is assumed to be hidden in the residuals. Hence, EMD is applied to the residuals at the second stage. The final estimate is the summation of the fitting estimates from LLQ and EMD. Simulation was conducted to assess the practical performance of the proposed method. Results show that the proposed method is superior to classical EMD. Hindawi Publishing Corporation 2014 Article PeerReviewed application/pdf en http://eprints.usm.my/38950/1/Empirical_Mode_Decomposition_Combined_with_Local_Linear_Quantile_Regression_for_Automatic_Boundary_Correction.pdf M. Jaber, Abobaker and Ismail, Mohd Tahir and M. Altaher, Alssaidi (2014) Empirical Mode Decomposition Combined with Local Linear Quantile Regression for Automatic Boundary Correction. Abstract and Applied Analysis, 2014 (731827). pp. 1-8. ISSN 1085-3375 http://dx.doi.org/10.1155/2014/731827 |
| spellingShingle | QA1-939 Mathematics M. Jaber, Abobaker Ismail, Mohd Tahir M. Altaher, Alssaidi Empirical Mode Decomposition Combined with Local Linear Quantile Regression for Automatic Boundary Correction |
| title | Empirical Mode Decomposition Combined with Local Linear
Quantile Regression for Automatic Boundary Correction |
| title_full | Empirical Mode Decomposition Combined with Local Linear
Quantile Regression for Automatic Boundary Correction |
| title_fullStr | Empirical Mode Decomposition Combined with Local Linear
Quantile Regression for Automatic Boundary Correction |
| title_full_unstemmed | Empirical Mode Decomposition Combined with Local Linear
Quantile Regression for Automatic Boundary Correction |
| title_short | Empirical Mode Decomposition Combined with Local Linear
Quantile Regression for Automatic Boundary Correction |
| title_sort | empirical mode decomposition combined with local linear
quantile regression for automatic boundary correction |
| topic | QA1-939 Mathematics |
| url | http://eprints.usm.my/38950/ http://eprints.usm.my/38950/ http://eprints.usm.my/38950/1/Empirical_Mode_Decomposition_Combined_with_Local_Linear_Quantile_Regression_for_Automatic_Boundary_Correction.pdf |