In this paper, the tri-percentile estimators are proposed to estimate the inverse shape parameter and scale parameter of K-distributions from data with outliers ...

Tri-percentile estimators are proposed to estimate the parameters of K-distributed sea clutter data. The optimal parameter setup of the tri-percentile ...

This paper proposes an outlier-robust tri-percentile parameter estimator of K-distributions. It is shown that the ratio of two percentiles is a monotonically ...

This paper proposes an outlier-robust tri-percentile parameter estimator of K-distributions. It is shown that the ratio of two percentiles is a monotonically ...

In this letter, an outlier-robust estimation method using the generalized regression neural network (GRNN) and multiple sample percentiles and truncated ...

Outlier-robust Tri-percentile Parameter Estimation Method of Compound-Gaussian Clutter with Inverse Gaussian Textures · Abstract · References · Proportional views.

Existing estimators, such as moment-based and [zlog(z)]-based ones, are sensitive to outliers and fail to use in practical radars. In this paper, an outlier- ...

Oct 22, 2024 · In this paper, an outlier-robust tri-percentile estimator is proposed to realize the robust parameter estimation of the CG-LNT model of sea ...

Jul 31, 2024 · An outlier-robust estimation method using the generalized regression neural network (GRNN) and multiple sample percentiles and truncated moments is proposed.

In this paper, an outlier-robust truncated maximum likelihood (TML) estimation method is proposed to mitigate the effect of outliers of high amplitude in data.