The finite-length minimum mean square error decision-feedback equalizer (MMSE-DFE) is an efficient structure mitigating intersymbol interference (ISI) introduced by practically all communication channels at high-enough symbol rates. The filters constituting the MMSE-DFE, as well as related performance measures, can be computed by assuming perfect knowledge of the channel impulse response and th...

Accounting for the borefield long-term dynamic behavior in optimal control applications can lead to substantial savings. To that end, a controller model covers time scale (i.e., interactions between boreholes) is necessary. However, direct use of an analytical may result computational burden increase due high number required states. This paper presents novel loworder resistance-capacity (RC) ne...

While the conditional mean is known to provide the minimum mean square error (MSE) forecast – and hence is optimal under a squared-error loss function – it must often in practice be replaced by a noisy estimate when model parameters are estimated over a small sample. Here two results are obtained, both of which motivate the use of forecasts biased toward zero (shrinkage forecasts) in such setti...

This paper proposes a novel adaptive filtering algorithm which converges faster than the Krylov proportionate normalized least mean square (KPNLMS) algorithm. KPNLMS is known to exhibit faster convergence than the standard NLMS algorithm for all unknown systems. Our algorithm is named Krylov proportionate normalized least mean fourth (KPNLMF) and it deals with mean fourth minimization of the er...

In this paper, a generalization of the Misspecified Cramér-Rao Bound (MCRB) and of the Constrained MCRB (CMCRB) to complex parameter vectors is presented. Our derivation aims at providing lower bounds on the Mean Square Error (MSE) for both circular and non-circular, MS-unbiased, mismatched estimators. A simple toy example is also presented to clarify the theoretical findings.

Interpolations are among the most important tools for image processing. However, whether they are used for image compression and reconstruction purposes or for the increase of the image resolution along vertical, horizontal or both dimensions, the induced interpolation errors are often only qualitatively and a posteriori described. In this paper, we propose to extend a method used in an OFDM co...

We propose a new ratio estimator using two auxiliary variables in simple random sampling. We obtain mean square error (MSE) equation of this estimator and theoretically show that our proposed estimator is more efficient than the traditional multivariate ratio estimator under a defined condition. In addition, we support this theoretical result with the aid of a numerical example.

Abstract Difference methods have been routinely used to compute velocity and acceleration from precise positioning with global navigation satellite systems (GNSS). A low sampling rate (say a not greater than 1 Hz, for example) has always implicitly assumed applicability of the methods, because random measurement errors are significantly amplified, either proportional in case or square-proportio...

AbstructThis paper presents two classes of adaptive blind algorithms based on secondand higher order statistics. The first class contains fast recursive algorithms whose cost functions involve second and thirdor fourth-order cumulants. These algorithms are stochastic gradient-based but have structures similar to the fast transversal filters (FTF) algorithms. The second class is composed of two ...

Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS) algorithm, as a popular tool, achieves excellent performance for sparse system identification. In previous studies, most of the cost functions used in proportionate-type sparse adaptive algorithms are based on the mean square error (MSE) crit...