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Wavelet shrinkage estimators of Calderón-Zygmund operators with odd kernels

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Abstract

Wavelet shrinkage is a strategy to obtain a nonlinear approximation to a given function f and is widely used in data compression, signal processing and statistics, etc. For Calderón-Zygmund operators T, it is interesting to construct estimator of Tf, based on wavelet shrinkage estimator of f. With the help of a representation of operators on wavelets, due to Beylkin et al., an estimator of Tf is presented in this paper. The almost everywhere convergence and norm convergence of the proposed estimators are established.

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References

  1. Abramovich F, Amato U, Angelini C. On optimality of Bayesian wavelet estimators. Scand J Statist, 2004, 31: 217–234

    Article  MATH  MathSciNet  Google Scholar 

  2. Beylkin G. On the representation of operators in bases of compactly supported wavelets. SIAM J Numer Anal, 1992, 29: 1716–1740

    Article  MATH  MathSciNet  Google Scholar 

  3. Beylkin G. Wavelets and fast numerical algorithms. Proc Sympos Appl Math, 1993, 47: 89–117

    Article  MathSciNet  Google Scholar 

  4. Beylkin G, Coifman R R, Rokhlin V. Fast wavelet transforms and numerical algorithms I. Comm Pure Appl Math, 1991, 44: 141–183

    Article  MATH  MathSciNet  Google Scholar 

  5. Chen D R, Meng H T. Convergence of wavelet thresholding estimators of differential operators. Appl Comput Harmon Anal, 2008, 25: 266–275

    Article  MATH  MathSciNet  Google Scholar 

  6. Chen D R, Zhao Y. Wavelet shrinkage estimators of Hilbert transform. J Approx Theory, 2011, 381: 947–951

    MATH  Google Scholar 

  7. Daubechies I. Orthonormal bases of compactly supported wavelets. Comm Pure Appl Math, 1988, 41: 909–996

    Article  MATH  MathSciNet  Google Scholar 

  8. Daubechies I. Ten Lectures on Wavelets. Philadelphia: SIAM, 1992

    Book  MATH  Google Scholar 

  9. Donoho D L. Denoising via soft thresholding. IEEE Trans Inform Theory, 1995, 41: 613–627

    Article  MATH  MathSciNet  Google Scholar 

  10. Donoho D L, Johnstone I M. Ideal spatial adaption via wavelet shrinkage. Biometrika, 1994, 81: 425–455

    Article  MATH  MathSciNet  Google Scholar 

  11. Donoho D L, Johnstone I M. Minimax estimation via wavelet shrinkage. Ann Statist, 1998, 26: 879–921

    Article  MATH  MathSciNet  Google Scholar 

  12. Liu Y, Wang H. Convergence order of wavelet thresholding estimator for differential operators on Besov spaces. Appl Comput Harmon Anal, 2012, 32: 342–356

    Article  MATH  MathSciNet  Google Scholar 

  13. Meyer Y. Ondelettes et Opérateurs. Paris: Hermann, 1990

    Google Scholar 

  14. Stein E. Sigular integrals and differentiability properties of functions. Princeton: Princeton University Press, 1970

    Google Scholar 

  15. Tao T. On the almost everywhere convergence of wavelet summation methods. Appl Comput Harmon Anal, 1996, 3: 384–387

    Article  MATH  MathSciNet  Google Scholar 

  16. Tao T, Vidakovic B. Almost everywhere behavior of general wavelet shrinkage operators. Appl Comput Harmon Anal, 2000, 9: 72–82

    Article  MATH  MathSciNet  Google Scholar 

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Correspondence to Heng Chen.

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Chen, H., Wu, J. Wavelet shrinkage estimators of Calderón-Zygmund operators with odd kernels. Sci. China Math. 57, 1983–1991 (2014). https://doi.org/10.1007/s11425-013-4724-8

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  • DOI: https://doi.org/10.1007/s11425-013-4724-8

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