Patricio S. La Rosa

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—We treat the problem of beamforming for signal estimation where the goal is to estimate a signal amplitude from a set of array observations. Conventional beamforming methods typically aim at maximizing the signal-to-interference-plus-noise ratio (SINR). However, this does not guarantee a small mean-squared error (MSE), so that on average the resulting(More)
We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which(More)
Finding the electrical conductivity of tissue is highly important for understanding the tissue’s structure and functioning. However, the inverse problem of inferring spatial conductivity from data is highly ill-posed and computationally intensive. In this paper, we propose a novel method to solve the inverse problem of inferring tissue conductivity from a(More)
—We treat the problem of beamforming for signal estimation in the presence of steering vector uncertainties, where the goal is to estimate a signal amplitude from a set of array observations. Conventional beamforming methods typically aim at maximizing the signal-to-interference-plus-noise ratio (SINR). Recently, a maximum likelihood (ML) approach was(More)
—We compute lower bounds on the mean-square error of multiple change-point estimation. In this context, the parameters are discrete and the Cramér-Rao bound is not applicable. Consequently, we focus on computing the Barankin bound (BB), the greatest lower bound on the covariance of any unbiased esti-mator, which is still valid for discrete parameters. In(More)
This peer-reviewed article can be downloaded, printed and distributed freely for any purposes (see copyright notice below). which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is(More)
We derive the Barankin bound on the mean-squared error for multiple change-point estimation of an independent measurement sequence. We first derive a general form of this bound and give the structure of the so-called Barankin information matrix (BIM). We show that the BIM for the change-point parameters has a tri-diagonal structure which means that one(More)
We propose a single-channel two-stage detector of uterine magnetomyogram (MMG) contractions during pregnancy. In the first stage, we assume that the measurements are modeled by a zero-mean Gaussian random variable with time-varying piecewise constant variance. Therefore, we apply a model-based segmentation procedure which detects multiple change points in(More)
In this paper we investigate the observer design for Single-Input Single-Output (SISO) systems with unknown input. We find that the design conditions proposed by several authors in the past lead to unity relative degree of the plant and zeros of the plant in the open left half of the complex plane, for SISO systems. In other words an observer for a SISO(More)
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