The noise contained in data measured by imaging instruments is often primarily of Poisson type. This motivates, in many cases, the use of the Poisson likelihood functional in place of the ubiquitous least squares data fidelity when solving image deblurring problems. We assume that the underlying blurring operator is compact, so that, as in the least squares case, the resulting minimization prob...

When GPS signal measurements have outliers, using least squares (LS) estimation is likely to give poor position estimates. One of the typical approaches to handle this problem is to use robust estimation techniques. We study the computational issues of Huber’s M-estimation applied to relative GPS positioning. First for code-based relative positioning, we use simulation results to show that Newt...

Recent XMM-Newton and Chandra observations of the high mass X-ray binary LS 5039 / RX J1826.2-1450 caught the source in a faint X-ray state. In contrast with previous RXTE observations, we fail to detect any evidence of iron line emission. We also fail to detect X-ray pulsations. The X-ray spectrum can be well fitted by a simple powerlaw, slightly harder than in previous observations, and does ...

An interior point approach for medium and large nonnegative linear least-squares problems is proposed. Global and locally quadratic convergence is shown even if a degenerate solution is approached. Viable approaches for implementation are discussed and numerical results are provided.

In this paper we consider a recursive least squares (RLS) adaptive ltering problem where the input signal can be modelled as the output of a low order autoregressive (AR) process. We will show how a good estimate of the Kalman gain vector can be obtained using a small least squares lattice (LSL) lter. This estimate can then be used in the normal way to determine the optimum lter coe cients. The...

Newton-Cotes quadrature rules are based on polynomial interpolation in a set of equidistant points. They are very useful in applications where sampled function values are only available on a regular grid. Yet, these rules rapidly become unstable for high orders. In this paper we review two techniques to construct stable high-order quadrature rules using equidistant quadrature points. The stabil...

This paper describes a robust method for local selflocalization using point–to–point and point–to–line matching with a Lorentzian estimator. A 2-D laser telemeter is used to obtain distance measurements around the mobile robot within a range. The goal is to find the rigid transformation (displacement and rotation) that match two consecutive laser scans despite noisy measurements (outliers). In ...

Tensor computations are increasingly prevalent numerical techniques in data science, but pose unique challenges for high-performance implementation. We provide novel algorithms and systems infrastructure which enable efficient parallel implementation of tensor completion with generalized loss functions. Specifically, we consider alternating minimization, coordinate a quasi-Newton (generalized G...

We introduce and analyze a space-time least-squares method associated with the unsteady Navier–Stokes system. Weak solution in two dimensional case regular three are considered. From any initial guess, we construct minimizing sequence for functional which converges strongly to of After finite number iterations related value viscosity coefficient, convergence is quadratic. Numerical experiments ...

Stability limits place restrictions on the available transfer capability (ATC) of power systems. Calculation of these limits is therefore very important, but has traditionally been quite difficult. This paper proposes an iterative algorithm for determining parameter values which result in marginal stability of a system. (A system is marginally stable for a particular disturbance if the postdist...