Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) geneâ€¦ (More)

We consider low-rank approximation of affinely structured matrices with missing elements. The method proposed is based on reformulation of the problem as inner and outer optimization. The innerâ€¦ (More)

Singular Spectrum Analysis is a nonparametric method, which allows one to solve problems like decomposition of a time series into a sum of interpretable components, extraction of periodic components,â€¦ (More)

A software package is presented that computes locally optim al solutions to low-rank approximation problems with the following features: â€¢ mosaic Hankel structure constraint on the approximatingâ€¦ (More)

We consider the problem of approximating an affinely structured matrix, for example a Hankel matrix, by a low-rank matrix with the same structure. This problem occurs in system identification, signalâ€¦ (More)

In this paper, we study a polynomial decomposition model that arises in problems of system identification, signal processing and machine learning. We show that this decomposition is a special case ofâ€¦ (More)

Singular Spectrum Analysis (SSA) has been approved as a model-free technique to analyse time series. SSA can solve different problems such as decomposition into a sum of trend, periodicities, andâ€¦ (More)

In this paper, we present and analyze the performance of multidimensional ESPRIT (<inline-formula> <tex-math notation="LaTeX">$N$</tex-math></inline-formula>-D ESPRIT) method for estimatingâ€¦ (More)