A robust variable step size fractional least mean square (RVSS-FLMS) algorithm

Shujaat Khan, Muhammad Usman, Imran Naseem, Roberto Togneri, Mohammed Bennamoun

    Research output: Chapter in Book/Conference paperConference paper

    7 Citations (Scopus)

    Abstract

    In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).

    Original languageEnglish
    Title of host publicationProceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017
    EditorsMohd Nasir Taib
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1-6
    Number of pages6
    ISBN (Electronic)9781509011841
    DOIs
    Publication statusPublished - 2017
    Event13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017 - Penang, Malaysia
    Duration: 10 Mar 201712 Mar 2017

    Conference

    Conference13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017
    CountryMalaysia
    CityPenang
    Period10/03/1712/03/17

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