Detection and localization performance with signal location uncertainty may be summarized by Figures of Merit (FOM’s) obtained from the LROC curve. We consider model observers that may be used to compute the two LROC FOM’s: ALROC and PCL, for emission tomographic MAP reconstruction. We address the case background-known-exactly (BKE) and signal known except for location. Model observers may be u...

We study Cramér-Rao bounds (CRB’s) for estimation problems on Riemannian manifolds. In (S.T. Smith, Covariance, subspace, and intrinsic Cramér-Rao bounds, IEEE TSP, 53(5):1610–1630, 2005), the author gives intrinsic CRB’s in the form of matrix inequalities relating the covariance of estimators and the Fisher information of estimation problems. We focus on estimation problems whose parameter spa...

Abstract. Rejuvenation in particle filters is necessary to prevent the collapse of weights when number particles insufficient properly sample high-probability regions state space. often implemented a heuristic manner by addition random noise that widens support ensemble. This work aims at improving canonical rejuvenation methodology introduction additional prior information obtained from climat...

We derive concentration inequalities for the spectral measure of large random matrices, allowing for certain forms of dependence. Our main focus is on empirical covariance (Wishart) matrices, but general symmetric random matrices are also considered.

Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible crosscovariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-...

Neurons in primary visual cortex are commonly characterized using linear models, or simple extensions of linear models. Specifically, V1 simple cell responses are often characterized using a rectified linear receptive field, and complex cell responses are often described as the sum of squared responses of two linear subunits. We examined this class of model directly by applying spike-triggered ...

This paper addresses the problem of obtaining a consistent estimate (or upper bound) of the covariance matrix when combining two quantities with unknown correlation. The combination is defined linearly with two gains. When the gains are chosen a priori, a family of consistent estimates is presented in the paper. The member in this family having minimal trace is said to be “family-optimal”. When...

This manuscript presents valuable data on CH4 fluxes from the understudied permafrost region of NE Europe. CH4 fluxes were measured on the plot scale by closed chambers and on the landscape scale by the eddy covariance approach. The combination of these two approaches is a particular strength of this study. Furthermore, the authors present interesting data on stable carbon signatures of pore wa...

Environmental spatial data often show complex spatial-temporal dependency structures that are difficult to model and estimate due to the lack of symmetry and other standard assumptions of the covariance function. In this study, we introduce certain types of symmetry in spatialtemporal processes: axial symmetry in time, axial symmetry in space, and diagonal symmetry in space, and propose new cla...

Belief space planning provides a principled framework to compute motion plans that explicitly gather information from sensing, as necessary, to reduce uncertainty about the robot and the environment. We consider the problem of planning in Gaussian belief spaces, which are parameterized in terms of mean states and covariances describing the uncertainty. In this work, we show that it is possible ...