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Cites:

Information Journal Paper

Title

AN ADAPTIVE WAVELET-BASED SIGNAL DENOISING SCHEME

Pages

  15-24

Abstract

 In this paper, a new class of nonlinear thresholding functions with a tunable shape parameter for wavelet-based SIGNAL DENOISING is presented. In addition, a new learning technique for training of THRESHOLDING NEURAL NETWORK is introduced. Unlike to existing methods, both the shape and the threshold parameters are tuned simultaneously using LMS rule. This permits us to consider the effects of both the threshold and the shape parameters on denoising. The proposed functions are tested in both universal-threshold and subband-adaptive denoising and compared with conventional functions. In addition, to evaluate the proposed TRAINING METHOD, several numerical examples are performed. The experimental results obtained from denoising of several standard benchmark signals confirm the efficiency and effectiveness of the proposed methods.

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  • Cite

    APA: Copy

    NASRI, MOHAMMAD, NEZAMABADI POUR, H., & SAR YAZDI, S.. (2008). AN ADAPTIVE WAVELET-BASED SIGNAL DENOISING SCHEME. NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN), 6(1), 15-24. SID. https://sid.ir/paper/53717/en

    Vancouver: Copy

    NASRI MOHAMMAD, NEZAMABADI POUR H., SAR YAZDI S.. AN ADAPTIVE WAVELET-BASED SIGNAL DENOISING SCHEME. NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN)[Internet]. 2008;6(1):15-24. Available from: https://sid.ir/paper/53717/en

    IEEE: Copy

    MOHAMMAD NASRI, H. NEZAMABADI POUR, and S. SAR YAZDI, “AN ADAPTIVE WAVELET-BASED SIGNAL DENOISING SCHEME,” NASHRIYYAH-I MUHANDESI-I BARQ VA MUHANDESI-I KAMPYUTAR-I IRAN (PERSIAN), vol. 6, no. 1, pp. 15–24, 2008, [Online]. Available: https://sid.ir/paper/53717/en

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