activity
20102020
most citedRate region boundary of the SISO Z-interference channel with improper signaling

47 citations · 150 across the 16 of their papers we have counts for

collaborators

18 papers

eess.SP2020★ 1 cited

One-Bit Target Detection in Collocated MIMO Radar and Performance Degradation Analysis

Yu-Hang Xiao, David Ramírez, Peter J. Schreier +2

Target detection is an important problem in multiple-input multiple-output (MIMO) radar. Many existing target detection algorithms were proposed without taking into consideration t…

eess.SP2020

Improper Gaussian Signaling for the -user MIMO Interference Channels with Hardware Impairments

Mohammad Soleymani, Ignacio Santamaria, Peter J. Schreier

This paper investigates the performance of improper Gaussian signaling (IGS) for the -user multiple-input, multiple-output (MIMO) interference channel (IC) with hardware impairm…

cs.CV2019★ 1 cited

Procrustes registration of two-dimensional statistical shape models without correspondences

Alma Eguizabal, Peter J. Schreier, Jürgen Schmidt

Statistical shape models are a useful tool in image processing and computer vision. A Procrustres registration of the contours of the same shape is typically perform to align the t…

eess.SP2019★ 16 cited

Two-Channel Passive Detection Exploiting Cyclostationarity

Stefanie Horstmann, David Ramírez, Peter J. Schreier

This paper addresses a two-channel passive detection problem exploiting cyclostationarity. Given a reference channel (RC) and a surveillance channel (SC), the goal is to detect a t…

cs.IT2019

Determining the Dimension and Structure of the Subspace Correlated Across Multiple Data Sets

Tanuj Hasija, Christian Lameiro, Timothy Marrinan +1

Detecting the components common or correlated across multiple data sets is challenging due to a large number of possible correlation structures among the components. Even more chal…

eess.SP2019★ 23 cited

Improper Signaling for SISO Two-user Interference Channels with Additive Asymmetric Hardware Distortion

Mohammad Soleymani, Christian Lameiro, Ignacio Santamaria +1

Hardware non-idealities are among the main performance restrictions for upcoming wireless communication systems. Asymmetric hardware distortions (HWD) happen when the impairments o…

eess.SP2019

Robust Improper Signaling for Two-user SISO Interference Channels

Mohammad Soleymani, Christian Lameiro, Ignacio Santamaria +1

It has been shown that improper Gaussian signaling (IGS) can improve the performance of wireless interference-limited systems when perfect channel state information (CSI) is availa…

cs.CV2018★ 1 cited

Deep Morphing: Detecting bone structures in fluoroscopic X-ray images with prior knowledge

Aaron Pries, Peter J. Schreier, Artur Lamm +2

We propose approaches based on deep learning to localize objects in images when only a small training dataset is available and the images have low quality. That applies to many pro…

cs.LG2018★ 1 cited

Model-order selection in statistical shape models

Alma Eguizabal, Peter J. Schreier, David Ramírez

Statistical shape models enhance machine learning algorithms providing prior information about deformation. A Point Distribution Model (PDM) is a popular landmark-based statistical…

eess.SP2018★ 18 cited

LMPIT-inspired Tests for Detecting a Cyclostationary Signal in Noise with Spatio-Temporal Structure

Aaron Pries, David Ramírez, Peter J. Schreier

In spectrum sensing for cognitive radio, the presence of a primary user can be detected by making use of the cyclostationarity property of digital communication signals. For the ge…

cs.IT2017★ 12 cited

Improper Gaussian signaling for multiple-access channels in underlay cognitive radio

Christian Lameiro, Ignacio Santamaria, Peter J. Schreier

This paper considers an unlicensed multiple-access channel (MAC) that coexists with a licensed point-to-point user, following the underlay cognitive radio paradigm. We assume that…

cs.CV2017

A weighting strategy for Active Shape Models

Alma Eguizabal, Peter J. Schreier

Active Shape Models (ASM) are an iterative segmentation technique to find a landmark-based contour of an object. In each iteration, a least-squares fit of a plausible shape to some…

cs.IT2017★ 3 cited

Determining the Dimension of the Improper Signal Subspace in Complex-Valued Data

Tanuj Hasija, Christian Lameiro, Peter J. Schreier

A complex-valued signal is improper if it is correlated with its complex conjugate. The dimension of the improper signal subspace, i.e., the number of improper components in a comp…

cs.IT2016★ 47 cited

Rate region boundary of the SISO Z-interference channel with improper signaling

Christian Lameiro, Ignacio Santamaria, Peter J. Schreier

This paper provides a complete characterization of the boundary of an achievable rate region, called the Pareto boundary, of the single-antenna Z interference channel (Z-IC), when…

cs.IT2016★ 4 cited

Canonical correlation analysis of high-dimensional data with very small sample support

Yang Song, Peter J. Schreier, David Ramirez +1

This paper is concerned with the analysis of correlation between two high-dimensional data sets when there are only few correlated signal components but the number of samples is ve…

cs.IT2014

Benefits of improper signaling for underlay cognitive radio

Christian Lameiro, Ignacio Santamaría, Peter J. Schreier

In this letter we study the potential benefits of improper signaling for a secondary user (SU) in underlay cognitive radio networks. We consider a basic yet illustrative scenario i…

cs.IT2013★ 23 cited

Detecting Directionality in Random Fields Using the Monogenic Signal

Sofia Olhede, David Ramírez, Peter J. Schreier

Detecting and analyzing directional structures in images is important in many applications since one-dimensional patterns often correspond to important features such as object cont…

cs.IT2010

On the instantaneous frequency of Gaussian stochastic processes

Patrik Wahlberg, Peter J. Schreier

This paper concerns the instantaneous frequency (IF) of continuous-time, zero-mean, complex-valued, proper, mean-square differentiable nonstationary Gaussian stochastic processes.…