This correspondence investigates the asymptotic performance of Bayesian target recognition algorithms using deformable-template representations. Rigid computer-aided design (CAD) models represent the underlying targets; low-dimensional matrix Lie-groups (rotation and translation) extend them to particular instances. Remote sensors observing the targets are modeled as projective transformations,...

We consider a sparse high-dimensional regression model where the goal is to recover k-sparse unknown binary vector β∗ from n noisy linear observations of form Y=Xβ∗+W∈Rn X∈Rn×p has i.i.d. N(0,1) entries and W∈Rn N(0,σ2) entries. In high signal-to-noise ratio regime sublinear sparsity regime, while order sample size needed information-theoretically known be n∗:=2klogp/log(k/σ2+1), no polynomial-...

This paper is devoted to study the rate of convergence weak solutions \begin{document}$ {\bf u}_\alpha $\end{document} id="M3">\begin{document}$ \alpha $\end{document}-regularization models solution id="M4">\begin{document}$ u} Navier-Stokes equations in two-dimensional periodi...