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The phrase "a few coefficients" is correct and usable in written English
It can be used when referring to a small number of coefficients in a mathematical or statistical context. Example: "In this equation, we need to adjust a few coefficients to improve the model's accuracy."
Exact(11)
With only a few coefficients to be identified by regression, the approach is robust against random measurements errors and paves the way for flexible on-line δ13C metabolic measurements with NDIR technology under increased O2 content.
Since most of the image information is concentrated in a few coefficients, the high-frequencies subbands are processed with hard- or soft-thresholding operations.
In this contribution, we have considered an ad hoc feedforward data-aided phase noise estimation algorithm that is based on the estimation of only a few coefficients of the DCT basis expansion of the time-varying phase.
The fundamental premise in CS is that certain classes of signals, such as natural images, have a succinct representation in terms of a sparsity inducing basis, or frame, such that only a few coefficients are significant and the remaining coefficients are negligibly small.
The 2D forward DCT in (2) is implemented by first applying a butterfly-based 1D DCT [15] to each row of the residual block, that is, Y=C N X T, followed by the 1D column DCT F=C N Y T. In such an implementation, even if only a few coefficients are predicted as non-zero, the 1D row and column transforms cannot be skipped.
Only a few coefficients showed extreme values.
Similar(49)
As an orthogonal transform, the 1D DCT has a tendency to distribute a large fraction of the signal energy into a relatively few coefficients.
As an orthogonal transform, the 1D row DCT has a tendency to pack a large fraction of the signal energy into a relatively few coefficients.
Thus we start by considering a single audio frame and its spectrum is modeled by a vector of few coefficients, for reducing the information flow of the audio signal.
For example, almost sparse signals (compressible signals) are more likely to occur in applications than exactly k-sparse vectors, (e.g., the wavelet transform of an image consists mostly of small coefficients and a few large coefficients).
Furthermore, an imposed l1-regularized least square optimization is used to calculate an SR coefficient vector with only a few significant coefficients.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com