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    • Thesis & Report, BSc (Computer Science and Engineering)
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    •   BracU IR
    • School of Engineering and Computer Science (SECS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD)

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    12101047, 12101063 & 12101066_CSE.pdf (808.6Kb)
    Date
    2016-08
    Author
    Sultana Nishi, Razia
    Uddin, Md. Burhan
    Islam, Safat
    Metadata
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    URI
    http://hdl.handle.net/10361/6394
    Abstract
    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.
    Keywords
    Intrinsic mode functions; Empirical mode decomposition; Support vector machine
     
    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.
     
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 21-22).
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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