In practice most functional data cannot be recorded on a continuum, but rather at discrete time points. It is also quite common that these measurements come with an additive error, which one would like eliminate for the statistical analysis. When each datum are taken same grid, underlying signal-plus-noise model can viewed as factor model. The signals refer to components of model, noise related...

This paper investigates a problem of broad practical interest, namely, the reconstruction large-dimensional low-rank tensor from highly incomplete and randomly corrupted observations its entries. Although number papers have been dedicated to this completion problem, prior algorithms either are computationally too expensive for large-scale applications or come with suboptimal statistical perform...

Biexponential time-series models commonly find use in biophysics, biochemistry and pharmacokinetics. Indeed, reactions that are described by biexponential functions typical for many biological processes. The kinetics of these modelled transcendental irrational equations interconnecting the reagent concentrations, time rate constants. is apparently a case nonlinear regression, as such, very ofte...

In data-driven control, a central question is how to handle noisy data. this work, we consider the problem of designing stabilizing controller for an unknown linear system using only finite set data collected from system. For problem, many recent works have considered disturbance model based on energy-type bounds. Here, alternative more natural where obeys instantaneous case, existing approache...