A Regularised Total Least Squares Approach for 1D Inverse Scattering

We study the inverse scattering problem for a Schrödinger operator related to a static wave operator with variable velocity, using the GLM (Gelfand–Levitan–Marchenko) integral equation. We assume to have noisy scattering data, and we derive a stability estimate for the error of the solution of the GLM integral equation by showing the invertibility of the GLM operator between suitable function spaces. To regularise the problem, we formulate a variational total least squares problem, and we show that, under certain regularity assumptions, the optimisation problem admits minimisers. Finally, we compute numerically the regularised solution of the GLM equation using the total least squares method in a discrete sense.

Symmetrical Augmented System of Equations for the Parameter Identification of Discrete Fractional Systems by Generalized Total Least Squares

This paper is devoted to the identification of the parameters of discrete fractional systems with errors in variables. Estimates of the parameters of such systems can be obtained using generalized total least squares (GTLS). A GTLS problem can be reduced to a total least squares (TLS) problem. A total least squares problem is often ill-conditioned. To solve a TLS problem, a classical algorithm based on finding the right singular vector or an algorithm based on an augmented system of equations with complex coefficients can be applied. In this paper, a new augmented system of equations with real coefficients is proposed to solve TLS problems. A symmetrical augmented system of equations was applied to the parameter identification of discrete fractional systems. The simulation results showed that the use of the proposed symmetrical augmented system of equations can shorten the time for solving such problems. It was also shown that the proposed system can have a smaller condition number.

INTRODUCTION OF EIO MODEL IN TLS METHOD TO CALCULATE THE COORDINATES TRANSFORMATION BY HELMERT’S FORMULA

The EIO (Errors In Observations) model is used in the total least squares method to calculate, process geodetic data. Next to the classical least squares method, it is applied to solve more solutions. When we use the EIO model in calculus and process, performing a matrix inverse has a large dimension will be avoided. Moreover, the calculation and accuracy evaluation steps are based on the iterative algorithm to get the results. In this paper, the authors use the procedure of calculating and evaluating the accuracy of the EIO model in the experimental calculation of the coordinate transformation according to the Helmert formula