Daubechies

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Hermann Render - One of the best experts on this subject based on the ideXlab platform.

Bakri Abdul Karim - One of the best experts on this subject based on the ideXlab platform.

  • Solar radiation data analysis by using Daubechies wavelets
    2011 IEEE International Conference on Control System Computing and Engineering, 2011
    Co-Authors: Samsul Ariffin Abdul Karim, Balbir Singh Mahinder Singh, Radzuan Razali, Noorhana Yahya, Bakri Abdul Karim
    Abstract:

    The aim of this paper is to study the possibility of using wavelet transform method for solar radiation data compression. The Daubechies wavelets were utilized for analyzing the transient nature of solar radiation. The measured solar radiation was subjected to the wavelets techniques for smoothing and filtering of data that was decomposed up to level 5. The findings from this study show that the Daubechies wavelets method can be used for filtering and smoothing of solar radiation. The results presented indicate that Daubechies 10 (D10) wavelet approach is suitable for data filtering and smoothing of the solar radiation data.

  • ICCSCE - Solar radiation data analysis by using Daubechies wavelets
    2011 IEEE International Conference on Control System Computing and Engineering, 2011
    Co-Authors: Samsul Ariffin Abdul Karim, Balbir Singh Mahinder Singh, Radzuan Razali, Noorhana Yahya, Bakri Abdul Karim
    Abstract:

    The aim of this paper is to study the possibility of using wavelet transform method for solar radiation data compression. The Daubechies wavelets were utilized for analyzing the transient nature of solar radiation. The measured solar radiation was subjected to the wavelets techniques for smoothing and filtering of data that was decomposed up to level 5. The findings from this study show that the Daubechies wavelets method can be used for filtering and smoothing of solar radiation. The results presented indicate that Daubechies 10 (D10) wavelet approach is suitable for data filtering and smoothing of the solar radiation data.

T. Aboulnasr - One of the best experts on this subject based on the ideXlab platform.

  • ISCAS - A mixed Butterworth/Daubechies wavelet analysis/synthesis system
    Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94, 1
    Co-Authors: T. Aboulnasr
    Abstract:

    This paper discusses the close relationship between the FIR Daubechies wavelet filters and the IIR Butterworth wavelet filters. The frequency responses of both types of filters are first compared. An "almost equivalent" Daubechies/Butterworth pair is then identified. To demonstrate the "equivalence" of these two filters, a wavelet-based filter bank using a combination of Daubechies/Butterworth filters is proposed. This relationship is used to implement a fully causal, more efficient filter bank. An example to verify the performance of the proposed hybrid system is given. >

Michael Unser - One of the best experts on this subject based on the ideXlab platform.

  • Generalized Daubechies Wavelet Families
    IEEE Transactions on Signal Processing, 2007
    Co-Authors: Cedric Vonesch, Michael Unser
    Abstract:

    We present a generalization of the orthonormal Daubechies wavelets and of their related biorthogonal flavors (Cohen-Daubechies-Feauveau, 9/7). Our fundamental constraint is that the scaling functions should reproduce a predefined set of exponential polynomials. This allows one to tune the corresponding wavelet transform to a specific class of signals, thereby ensuring good approximation and sparsity properties. The main difference with the classical construction of Daubechies is that the multiresolution spaces are derived from scale-dependent generating functions. However, from an algorithmic standpoint, Mallat's fast wavelet transform algorithm can still be applied; the only adaptation consists in using scale-dependent filter banks. Finite support ensures the same computational efficiency as in the classical case. We characterize the scaling and wavelet filters, construct them and show several examples of the associated functions. We prove that these functions are square-integrable and that they converge to their classical counterparts of the corresponding order.

  • generalized biorthogonal Daubechies wavelets
    Proceedings of SPIE, 2005
    Co-Authors: Cedric Vonesch, Thierry Blu, Michael Unser
    Abstract:

    We propose a generalization of the Cohen-Daubechies-Feauveau (CDF) and 9⁄7 biorthogonal wavelet families. This is done within the framework of non-stationary multiresolution analysis, which involves a sequence of embedded approximation spaces generated by scaling functions that are not necessarily dilates of one another. We consider a dual pair of such multiresolutions, where the scaling functions at a given scale are mutually biorthogonal with respect to translation. Also, they must have the shortest-possible support while reproducing a given set of exponential polynomials. This constitutes a generalization of the standard polynomial reproduction property. The corresponding refinement filters are derived from the ones that were studied by Dyn et al. in the framework of non-stationary subdivision schemes. By using different factorizations of these filters, we obtain a general family of compactly supported dual wavelet bases of $ L _{ 2 } $ . In particular, if the exponential parameters are all zero, one retrieves the standard CDF B-spline wavelets and the 9⁄7 wavelets. Our generalized description yields equivalent constructions for E-spline wavelets. A fast filterbank implementation of the corresponding wavelet transform follows naturally; it is similar to Mallat's algorithm, except that the filters are now scale-dependent. This new scheme offers high flexibility and is tunable to the spectral characteristics of a wide class of signals. In particular, it is possible to obtain symmetric basis functions that are well-suited for image processing.

Nira Dyn - One of the best experts on this subject based on the ideXlab platform.

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