In this paper, new classes of lower bounds on the outage error probability and on the mean-square-error (MSE) in Bayesian parameter estimation are proposed. The minima of the h-outage error probability and the MSE are obtained by the generalized maximum a-posteriori probability and the minimum MSE (MMSE) estimators, respectively. However, computation of these estimators and their corresponding ...

Purpose: Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein’s unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods th...

Multiscale entropy (MSE) analysis provides information about complexity on various time scales. The aim of this study was to test whether MSE is able to detect autonomic dysregulation in young patients with diabetes mellitus (DM). We analyzed heart rate (HR) oscillations, systolic (SBP) and diastolic blood pressure (DBP) signals in 14 patients with DM type 1 and 14 age- and sex-matched healthy ...

A novel data structure that enables the storage and retrieval of linear array numeric with logarithmic time complexity updates, range sums, rescaling is introduced studied. Computing sums ranges arrays numbers a common computational problem encountered in compression, coding, machine learning, vision, finance, among other fields. Efficient structures enabling log n updates underlying (including...

Although the agile software development approaches have gained wide acceptance in practice, the concerns regarding the scalability and integration of agile practices in traditional large-scale system development projects are prevailing. Scaled Agile Framework (SAFe) has emerged as a solution to address some of these concerns. Despite few encouraging results, case studies indicate several challe...

Multi-surface environments (MSE) combine several surfaces in a variety of physical arrangements to form a seamless information space. Large surfaces, such as tabletops and wall-displays are often used as a shared space to coordinate efforts, and handheld devices, such as tablets and smartphones, are generally used as personal spaces supporting individual tasks. MSE have shown benefits for suppo...

Different predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

Diierent predictors and their approximators in nonlinear prediction regression models are studied. The minimal value of the mean squared error (MSE) is derived. Some approximate formulae for the MSE of ordinary and weighted least squares predictors are given.

Scaled Matching refers to the problem of nding all locations in the text where the pattern, proportionally enlarged according to an arbitrary integral scale, appears. Scaled matching is an important problem that was originally inspired by problems in Vision. However, in real life, a more natural model of scaled matching is the Real Scaled Matching model. Real scaled matching is an extended vers...