A residual type a posteriori error estimator is presented and analyzed for Weak Galerkin finite element methods for second order elliptic problems. The error estimator is proved to be efficient and reliable through two estimates, one from below and the other from above, in terms of an H1-equivalent norm for the exact error. Two numerical experiments are conducted to demonstrate the effectivenes...

This paper presents an adaptive visualization for helping the needle insertion task for RF liver ablation under CT-fluoroscopy (CTfluoro) guidance. It shows slices of the 3D CT-volume that are resulting from the out-of-plane motion parameters along weighted isosurfaces in the convergence basin of the employed cost function. The visualization is coupled to the uncertainty in estimating the defor...

An adaptive channel estimator for frequency selective fading channels is proposed for the uplink in Code Division Multiple Access (CDMA) mobile communication systems. The proposed scheme is well suited for both linear and nonlinear multiuser detectors. In this paper we will show the importance of channel estimator adaptivity especially to synchronization of weak users. A simple Least Mean Squar...

Hierarchical modeling allows for two appealing characteristics in shrinkage estimation. First, it leads to a more natural way of taking into account the uncertainty in the estimates than simply summarizing the result of each test in a p-value. Second, as the data are treated as exchangeable rather than independent, this allows for feedback as each data point informs the distributions of the res...

Hierarchical modeling allows for two appealing characteristics in a design for false discovery rate control in multiple hypothesis testing. First, it leads to a more natural way of taking into account the uncertainty in the estimates than simply summarizing the result of each test in a p-value. Second, as the data are treated as exchangeable rather than independent, this allows for feedback as ...

We describe a non-parametric estimator for the differential entropy of a multidimensional distribution, given a limited set of data points, by a recursive rectilinear partitioning. The estimator uses an adaptive partitioning method and runs in Θ ( N log N ) time, with low memory requirements. In experiments using known distributions, the estimator is several orders of magnitude faster than othe...

We propose a procedure to handle the problem of Gaussian regression when the variance is unknown. We mix least-squares estimators from various models according to a procedure inspired by that of Leung and Barron [17]. We show that in some cases the resulting estimator is a simple shrinkage estimator. We then apply this procedure in various statistical settings such as linear regression or adapt...

[1] A proper understanding of the sources and effects of uncertainty is needed to achieve the goals of reliability and sustainability in water resource management and planning. Many studies have focused on uncertainties relating to climate inputs (e.g., precipitation and temperature), as well as those related to supply and demand relationships. In the end-to-end projection of the hydrological i...

Due to some key state parameters of vehicle handling stability control are difficult to measure directly, the state optimization estimation algorithm of multi-sensor linear combination based on Strong Tracking Filter (STF) was proposed. Four degrees of freedom vehicle nonlinear dynamics model including longitudinal, lateral and roll motion were established. With the estimator of multi-sensors i...

In this paper, a new neural network enhanced synchronized control approach is proposed for multiple robotic manipulators systems (MRMS) based on leader-follower network communication topology. The justification of introducing two adaptive Radial Basis Function Neural Networks (RBF NN), also called neuro agents, is to facilitate the whole control system design and analysis. Otherwise such design...