#### Filter Results:

- Full text PDF available (9)

#### Publication Year

2003

2017

- This year (2)
- Last 5 years (5)
- Last 10 years (9)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Yonina C. Eldar, Arye Nehorai, Patricio S. La Rosa
- IEEE Transactions on Signal Processing
- 2007

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)

- Elad Gilboa, Patricio S. La Rosa, Arye Nehorai
- Annals of Biomedical Engineering
- 2012

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)

- Patricio S. La Rosa, Arye Nehorai, Hari Eswaran, Curtis Lowery, Hubert Preissl
- IEEE Trans. Biomed. Engineering
- 2008

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)

- Patricio S. La Rosa, Alexandre Renaux, Carlos H. Muravchik, Arye Nehorai
- IEEE Transactions on Signal Processing
- 2010

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 estimator, which is still valid for discrete parameters.… (More)

- Yonina C. Eldar, Arye Nehorai, Patricio S. La Rosa
- IEEE Signal Processing Letters
- 2006

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)

- Patricio La Rosa, Hiro Mukai, +4 authors Arye Nehorai
- 2015

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)

- Johan Wahlström, Isaac Skog, Patricio S. La Rosa, Peter Händel, Arye Nehorai
- IEEE Transactions on Signal Processing
- 2017

We study the maximum-likelihood estimator in a setting where the dependent variable is a random graph and covariates are available on a graph level. The model generalizes the well-known <inline-formula><tex-math notation="LaTeX"> $\beta$</tex-math></inline-formula>-model for random graphs by replacing the constant model parameters with regression functions.… (More)

- Johan Wahlström, Isaac Skog, Patricio S. La Rosa, Peter Händel, Arye Nehorai
- IEEE Trans. Signal Processing
- 2017

- Yanjiao Zhou, Hongyu Gao, +14 authors Erica Sodergren
- 2012

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)