This study presents an auditory cortical representation for passive sonar signal and use it to extract features to categorize an unknown signal as being of man-made or natural origin. A ridge partial least squares (RPLS) model is given to establish the decision criterion, and regression coefficients are used to search for salient regions of the auditory cortical representation related to the cl...

selecting a IUDFWLRQDO H[SRQHQWLDO )(;3 model for a Gaussian long-memory time series. A regression approach is used to obtain the least squares estimator of d of the memory parameter, and mean squared error is minimized. The paper overlooks the fact that in the case of regression models, there is a relationship between $NDLNH¶V LQIRUPDWLRQ FULWHULRQ $,& and 0DOORZV¶ / & , which can also be used...

The quality of short-term electricity load forecasting is crucial to the operations and trading activities of market participants in an electricity market. In this paper, a multiple equation time series model for intra-day and day-ahead load forecasting is built. The model uses lagged load and temperature as the primary explanatory variables but makes effective use of diurnal characteristics an...

Recent studies have demonstrated that correntropy is an efficient tool for analyzing higher-order statistical moments in nonGaussian noise environments. Although correntropy has been used with complex data, no theoretical study was pursued to elucidate its properties, nor how to best use it for optimization . This paper presents a probabilistic interpretation for correntropy using complex-value...

This paper introduces and solves a weighted game-type cost criterion for estimation and control purposes that allows for a general class of uncertainties in the model or data. Both structured and unstructured uncertainties are allowed, including some special cases that have been used in the literature. The optimal solution is shown to satisfy an orthogonality condition similar to least-squares ...

We study the degrees of freedom in shrinkage estimation of the regression coefficients. Generalizing the idea of the Lasso, we consider the problem of estimating the coefficients by the projection of the ordinary least squares estimator onto a closed convex set. Then an unbiased estimator of the degrees of freedom is derived in terms of geometric quantities under a smoothness condition on the b...

Recently it has been shown (Afonine et al, 2001; Lunin et al., 2002) that the approximation of the maximum likelihood criterion (ML) by a quadratic functional (Lunin & Urzhumtsev, 1999) allows to understand the features of the ML refinement and its advantages with respect to the traditional least-squares (LS) refinement. In this latter, the magnitudes { } S calc F ∈ s s of structure factors cal...

An adaptive control problem for some continuous-time linear stochastic systems and its solution are presented in this paper. The solution includes showing the strong consistency of a family of maximum likelihood (or, equivalently, least squares) estimates of the unknown parameters and the convergence of the average quadratic costs with control based on these estimates to the optimal cost. The s...

Abstract: This paper establishes that when using a least squares criterion to estimate an output error type model structure, then the measurement noise induced variability of the frequency response estimate depends on the estimated (and hence also on the true) pole positions. This dependence on pole position is perhaps counter to prevailing wisdom that for any ‘shift invariant’ model structure,...

In the last years there has been a growing interest in the construction space-time covariance functions. However, effective estimation methods for these models are somehow unexplored. In this paper we propose a composite likelihood approach and a weighted variant for the space-time estimation problem. The proposed method can be a valid compromise between the computational burdens, induced by th...