An adaptive design of an all-zero spectral estimator

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ARMA model maximum entropy power spectral estimation

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An alternative approach to implement a recursive interpolation

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Transformaciones lineales en estimación espectral y sus aplicaciones en hidrografía y medicina

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Aplicación del muestreo enfatizado a la evaluación de transmisiones digitales

The Importance Sampling Technique is a method for reducing the computational effort in Montecarlo simulations for obtaining the relative frequency of an event having a very low probability. While this method is well known in general Operations Research /1//2//3/ and Radar /4//5//6//7//8//9//10/, it has not been considered in digital communication problems. This paper aims to introduce the Importance Sampling concept in this communication context.Peer ReviewedPostprint (published version

Sistemas delta adaptativos con control digital en canales ruidosos

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Further results in designing digital interpolators

One of the two approaches to the design of digital interpolators uses averaged second-order statistics to minimize the mean square interpolation error. This approach has been considered only when the number of samples employed to compute a final interpolated value is even. In the present paper, we generalize systematically this method to consider even or odd numbers of samples in that computation and values of sampling period ratio, with lineal phase non-recursive interpolating filters.Peer ReviewedPostprint (published version

Designing the quantizing step for a digital generalized sign test detector applied to Radar a first approach

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Randomizing ties in a sign radar detector

A general formulation to consider the effects of typical randomization methods (RMs) for a digital application of Generalized Sign Test (GST) detector in Radar is introduced. A first approximation leads us to some basic restrictions to be imposed to RMs. Introducing them, when the approximation is acceptable, our formulation allows to evaluate easily the false alarm and detection probabilities (PFA and PD ) obtainable with the use of each RM in fuction of the quantizing step (q) of the video samples, and, then, to select the most appropriate among them. Besides this, by considering the values of PFA and PD with respect to continuous situations, we can determine the maximum q to obtain small enough variations due to quantization (which has parametric effects). In such a way, a maximum dynamic range and a basically nonparametric behaviour are achieved. An example illustrates the application of the theory.Peer ReviewedPostprint (published version