Comparison of the MM algorithm and least squares deconvolution method for the recognition of thin layers

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Pakmanesh Parvaneh; goudarzi alireza; Kourki Meisam

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Journal: JOURNAL OF RESEARCH ON APPLIED GEOPHYSICS Year:2018 | Volume:4 | Issue:1 Page(s): 15-26

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Title

Comparison of the MM algorithm and least squares deconvolution method for the recognition of thin layers

Author(s)

Pakmanesh Parvaneh | goudarzi alireza | Kourki Meisam | Issue Writer Certificate

Keywords

Deconvolution

MM Algorithm

Inversion

Sparse

LTI System

Regularization

Least Squares Resolution

Abstract

Summary: Deconvolution problems involve estimating an unknown input when the signal and the response of an LTI System are known and lead to wavelet compression and increase the temporal resolution. However, in practice, the output signal is noisy. For some systems, the Deconvolution problem is simple, but for the non-invertible or almost non-invertible systems, the problem is more complex. The use of the exact inverse of the systems leads to the amplification of the noise. The reflectivity sequence is the representation of the layers of the earth. The resulted compression leads to a high-resolution image of the earth. The outcomes exhibit that the reflection coefficient significantly improves after application of the MM Algorithm on synthetic and real data, compared to the least squares and the frequency spectrum methods after the application of the algorithm. ...

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APA: Copy

Pakmanesh, Parvaneh, goudarzi, alireza, & Kourki, Meisam. (2018). Comparison of the MM algorithm and least squares deconvolution method for the recognition of thin layers. JOURNAL OF RESEARCH ON APPLIED GEOPHYSICS, 4(1 ), 15-26. SID. https://sid.ir/paper/268561/en

Vancouver: Copy

Pakmanesh Parvaneh, goudarzi alireza, Kourki Meisam. Comparison of the MM algorithm and least squares deconvolution method for the recognition of thin layers. JOURNAL OF RESEARCH ON APPLIED GEOPHYSICS[Internet]. 2018;4(1 ):15-26. Available from: https://sid.ir/paper/268561/en

IEEE: Copy

Parvaneh Pakmanesh, alireza goudarzi, and Meisam Kourki, “Comparison of the MM algorithm and least squares deconvolution method for the recognition of thin layers,” JOURNAL OF RESEARCH ON APPLIED GEOPHYSICS, vol. 4, no. 1 , pp. 15–26, 2018, [Online]. Available: https://sid.ir/paper/268561/en

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