In many geodetic applications a large number of observations are being measured to estimate the unknown parameters. The unbiasedness property of the estimated parameters is only ensured if there is no bias (e.g. systematic effect) or falsifying observations, which are also known as outliers. One of the most important steps towards obtaining a coherent analysis for the parameter estimation is th...

In this paper, a novel extended kernel recursive least squares algorithm is proposed combining the kernel recursive least squares algorithm and the Kalman filter or its extensions to estimate or predict signals. Unlike the extended kernel recursive least squares (Ex-KRLS) algorithm proposed by Liu, the state model of our algorithm is still constructed in the original state space and the hidden ...

In this paper, a 2-D robust recursive least squares lattice algorithm is introduced and is applied to defect detection problem in textured images. The algorithm combines concepts of 1-D robust regression with the recursive least squares lattice algorithm. The philosophy of using different optimization functions that results in weighted least-squares solutions in the theory of 1-D robust regress...

Some recursive least-squares algorithms for multichannel active noise control have recently been introduced, including computationally efficient (i.e. “fast”) versions. However, these previously published algorithms suffer from numerical instability due to finite precision computations. In this paper, numerically robust recursive least-squares algorithms for multichannel active noise control sy...