The phrase "adaptive weight" is correct and usable in written English.
It can be used in contexts related to machine learning, statistics, or any field where weights are adjusted based on changing conditions or inputs.
Example: "In our model, we implemented an adaptive weight system to improve accuracy as new data becomes available."
Alternatives: "dynamic weight" or "variable weight".
In order to eliminate the influence of unavoidable outliers in training sample on a model's performance, a novel least square support vector machine regression, which combines outlier detection approach and adaptive weight value for the training sample, is proposed and named as adaptive weighted least square support vector machine regression (AWLS-SVM).
Then the adaptive Legendre filter structure and adaptive weight update algorithm are derived.
Then an adaptive weight distribution method is developed to determine the weight for each variable.
Based on simulation results; one concludes showing the benefits of using an adaptive weight Q rather than a constant one.
Firstly, a new regularization term which adopts Regional Adaptive Weight Coefficients (RAWC) is produced to keep edges and flat regions.
Further, to avoid wireless sensors collision which may result in low accuracy of receiving radio signal, adaptive weight center of gravity localization (AWCG) were proposed.
Instead of adopting a global weight, we allocate adaptive weight to each column of the target patch-image according to its patch structure.
In this paper, we propose adaptive weight matrix design and parameter estimation via sparse modeling to improve the recovery performance for MIMO radar.
We develop a general 2-step detection and sidelobe blanking procedure which can be applied to any kind of adaptive weight vector.
Numerical results demonstrate that significant performance improvement has been achieved by the proposed sensing matrix optimization and adaptive weight matrix design approach.
In addition, a target unlikelihood coefficient is designed based on the steering kernel, serving as the adaptive weight for each column.
