A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD)
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
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| 语言: | English |
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2016
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| 在线阅读: | http://hdl.handle.net/10361/6394 |
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10361-63942022-01-26T10:13:14Z A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) Sultana Nishi, Razia Uddin, Md. Burhan Islam, Safat Uddin, Dr. Jia Department of Computer Science and Engineering, BRAC University Intrinsic mode functions Empirical mode decomposition Support vector machine This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. Cataloged from PDF version of thesis report. Includes bibliographical references (page 21-22). In the field of signal processing an adaptive algorithm for the selection of Intrinsic Mode Functions (IMF) of Empirical Mode Decomposition (EMD) is a time demand. In this paper, we propose an effective model for adaptive selection of IMFs after decomposition. This proposed algorithm decomposes an input signal using EMD, then the resultant IMF’s are passed through a trained Support Vector Machine (SVM) for the separation of relevant and irrelevant IMF’s. The irrelevant IMF’s are then de-noised. And all IMFs are then reconstructed. The proposed model selects IMF adaptively without any human supervision and helps achieving higher Signal to Noise Ratio (SNR) while keeping Percentage RMS Difference (PRD) and Max Error low. Experiment results show up to 36.16% SNR value, PRD and Max Error are reduced to 1.557% and 0.085%, respectively. Razia Sultana Nishi Md. Burhan Uddin Safat Islam B. Computer Science and Engineering 2016-09-08T06:03:08Z 2016-09-08T06:03:08Z 2016 2016-08 Thesis ID 12101047 ID 12101063 ID 12101066 http://hdl.handle.net/10361/6394 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 22 pages application/pdf |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Intrinsic mode functions Empirical mode decomposition Support vector machine |
| spellingShingle |
Intrinsic mode functions Empirical mode decomposition Support vector machine Sultana Nishi, Razia Uddin, Md. Burhan Islam, Safat A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. |
| author2 |
Uddin, Dr. Jia |
| author_facet |
Uddin, Dr. Jia Sultana Nishi, Razia Uddin, Md. Burhan Islam, Safat |
| format |
Thesis |
| author |
Sultana Nishi, Razia Uddin, Md. Burhan Islam, Safat |
| author_sort |
Sultana Nishi, Razia |
| title |
A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) |
| title_short |
A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) |
| title_full |
A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) |
| title_fullStr |
A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) |
| title_full_unstemmed |
A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD) |
| title_sort |
new approach to select adaptive intrinsic mode functions (imfs) of empirical mode decomposition (emd) |
| publishDate |
2016 |
| url |
http://hdl.handle.net/10361/6394 |
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