The ship model test was believed to be one of the effective methods for figuring out boundaries and reliability ship's horsepower. form factor determines a full-scale Determination value can done experimentally through Prohaska method. new method proposed in this study is employed regression Iteratively Reweighted Least Squares (IRLS) by utilizing principle dimension ship, such as LWL, B, CB, C...

Recently, compressed sensing has been widely applied to various areas such as signal processing, machine learning, and pattern recognition. To find the sparse representation of a vector w.r.t. a dictionary, an l1 minimization problem, which is convex, is usually solved in order to overcome the computational difficulty. However, to guarantee that the l1 minimizer is close to the sparsest solutio...

In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagrangian formalism, we derive an algorithm that we call Simultaneous Multiple Robust Fitting (SMRF), which extends the classical Iterative Reweighted Least Squares algorithm (IRLS). Compared to the IRLS, it features an ex...

In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagrangian formalism, we derive an algorithm that we call SMRF, which extends the classical Iterative Reweighted Least Squares algorithm (IRLS). Compared to the IRLS, it features an extra probability ratio, which is classic...

This paper is concerned with the alternating minimization (AM) method for solving convex minimization problems where the decision variables vector is split into two blocks. The objective function is a sum of a differentiable convex function and a separable (possibly) nonsmooth extended real-valued convex function, and consequently constraints can be incorporated. We analyze the convergence rate...

Distorted sensors could occur randomly and may lead to the breakdown of a sensor array system. We consider an model within which small number are distorted by unknown gain phase errors. With such model, problem joint direction-of-arrival (DOA) estimation detection is formulated under framework low-rank row-sparse decomposition. derive iteratively reweighted least squares (IRLS) algorithm solve ...

The use of Iteratively Reweighted Least Squares (IRLS) for detecting design points where structural optimizations give poor designs is demonstrated. Since most optimization error is one sided with poor results producing an overweight objective value, a nonsymmetrical version of IRLS (NIRLS) that takes into account the asymmetry in optimization errors is also developed. Optimization studies with...