Ichimura, N., Robust clustering based on a maximum likelihood method for estimation of the suitable number of clusters. Trans. Inst. Electron. Inf. Commun. Eng. vJ78-D-II i8. 1184-1195.]]Ichimura N. “Robust clustering based on a maximum-likelihood method for estimating a suitable number ...
A nonconvex constrained maximum likelihood (ML) estimation method is proposed for Q-TRPCA. We provide an upper bound on the Frobenius norm of tensor estimation error under this method. Making use of tools in information theory...
Here we present a method for the robust estimation of system parameters based on the censoring of data and employing the maximum likelihood estimation. Several simulated examples show that the modified maximum likelihood method works well in situations where other methods failed. 展开 ...
A maximum likelihood estimation method for denoising magnitude MRI using restricted local neighborhood In this paper, we propose a method to denoise magnitude Magnetic Resonance (MR) images based on the maximum likelihood (ML) estimation method using a restr... J Rajan,M Verhoye,J Sijbers 被引...
In this paper, a novel approach towards horizon-based maximum likelihood (ML) state estimator is proposed that makes the state estimation process more robust against unmodeled and unstructured noise and disturbances in the state-space models. State space models provide a powerful way to perform state...
Use other criteria(loss) than least squares for heavy tail data points. This class ofestimatorscan be regarded as ageneralizationof maximum-likelihoodestimation, hence the term “M”-estimation(Max likelihood):\\ \hat{\beta}=\min \sum_{i=1}^n \rho(y_i-x_i^T\beta) ...
In order to find reliable estimated for the parameter intervals specifying the uncertainty in the considered model class, a sliding-window MLE (maximum-likelihood estimation) approach was used. Parameterization A generalized affine diffusion is a continuous semimartingale X ([definition] Semimartingale: ...
robust estimatorsmaximum likelihood estimatorsGross error detection is crucial for data reconciliation and parameter estimation, as gross errors can severely bias... N Arora,LT Biegler - 《Computers & Chemical Engineering》 被引量: 170发表: 2001年 Robust State Estimator Based on Maximum Normal Measurem...