The phrase "adapt the weight" is correct and usable in written English.
It can be used in contexts where adjustments or modifications to weight are necessary, such as in fitness, engineering, or scientific discussions.
Example: "To ensure the safety of the structure, we need to adapt the weight of the materials used in the construction."
Alternatives: "adjust the weight" or "modify the weight".
We adapt the weights of particles in the move step of the EPMCMC filter specified in Section 3.1.
All the previously mentioned algorithms are generally based on a non-constrained optimization technique, except in[8] which uses constrained optimization to adapt the weights only.
In order to adapt the weighting coefficients to varying noise and image statistics, we introduce a methodology, which achieves an optimal trade-off between smoothing and detail preserving characteristics.
In the following, we will discuss a metric of group dispersion that we adopted to quantify this perceived distance and then we will show how it can be used to adapt the weights of the different components of the movement utility computation to preserve group cohesion.
Consequently, we can simply study the effects of pose normalization in the visual domain and transfer the improvements into the audio-visual task by adapting the weight associated to the visual stream.
This is achieved by adapting the weights of the demixing filters to force the output signals to become statistically independent.
For conventional array beamforming, the a priori information required for adapting the weights is either the direction vector or the waveform of the signal of interest (SOI) [1].
The WAP method adapts the weights γ d (k) according to the performance of a learning algorithm on each specific class k under study.
Additionally, the smoothness may be optimized for each interface by adapting the weights α and β of the level set method in Eq. (13).
Besides, an original method is proposed to dynamically adapt the relative weight of these two pieces of information.
