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To overcome this problem, we propose a modified sifting process based on a smoothing technique.
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Modified sifting at the first level: The modified sifting can be employed to extract further IMFs beyond the firstly extracted mode h1,λ.
The role of the smoothing parameter λ: The performance of the modified sifting depends on the choice of λ.
Wang et al. [18] proposed modified sift feature extraction algorithm with shape-context descriptor (MSSCD).
We also would like to modify SIFT to more suitable speech data.
This paper proposes a soft sifting stopping criterion that enables LMD to achieve a self-adaptive stop for each sifting process.
(3) Identifying criteria for stopping the sifting process.
Thus, a precise criterion is required to identify the appropriate stage to conclude the sifting process.
The IMFs are obtained through an iterative process called the sifting process.
The proposed method reduces the spatial resolution of the original image during the sifting process.
Obtaining a mode from the original signal is called the sifting process.
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