We present a method, called iRRT, for processing Diffusion Ordered Spectroscopy (DOSY) data, that can produce results even in overlapping regions of the spectrum. From the results we obtain diffusion constants for camphene, geraniol, and quinine of 12× 10−6cm2s−1, 9× 10−6cm2s−1, and 6× 10−6cm2s−1 respectively. We compare the results from this method to those obtained using a mono-exponential no...

In order to improve the estimation accuracy of battery state charge (SOC) based on equivalent circuit model, a lithium-ion SOC method adaptive forgetting factor least squares and unscented Kalman filtering is proposed. The Thevenin model established. Through simulated annealing optimization algorithm, adaptively changed in real-time according demand, realized by combining least-squares online i...

. The method of flexi-Weighted Least Squares on evolutionary trees uses simple polynomial or exponential functions of the evolutionary distance in place of model-based variances. This has the advantage that unexpected deviations from additivity can be modeled in a more flexible way. At present, only polynomial weights have been used. However, a general family of exponential weights is desirable...

We study the approach to obtaining least squares solutions to systems of linear algebraic equations over networks by using distributed algorithms. Each node has access to one of the linear equations and holds a dynamic state. The aim for the node states is to reach a consensus as a least squares solution of the linear equations by exchanging their states with neighbors over an underlying intera...

We study the nonlinear round-off error accumulation system of the conventional recursive least squares algorithm, and we derive bounds for the relative precision of the computations in terms of the conditioning of the problem and the exponential forgetting factor, which guarantee the numerical stability of the finite-precision implementation of the algorithm; the positive definiteness of the fi...

During the last decades, the use of information theoretic criteria (ITC) for selecting the order of autoregressive (AR) models has increased constantly. Because the ITC are derived under the strong assumption that the measured signals are stationary, it is not straightforward to employ them in combination with the forgetting factor least-squares algorithms. In the previous literature, the attem...

In this paper, we deal with deterministic dominance of stochastic equations. The obtained results lead to the evaluation of tight upper-bounds upon the parameter tracking error of the forgetting factor recursive least squares (RLS) algorithm applied to the identiication of time-varying systems.