Eduardo Hernandez-Pérez

Eduardo Hernandez-Pérez
Universidad de Las Palmas de Gran Canaria | ULPGC · Departamento de Señales y Comunicaciones

PhD

About

21
Publications
9,361
Reads
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119
Citations
Introduction
Skills and Expertise
Additional affiliations
January 1990 - present
Universidad de Las Palmas de Gran Canaria
Position
  • Professor
January 1990 - present
Universidad de Las Palmas de Gran Canaria
Position
  • Professor
January 1990 - present
Universidad de Las Palmas de Gran Canaria
Position
  • Lecturer

Publications

Publications (21)
Conference Paper
We address the problem of estimating the path loss factor and its integration in RSS-based localization algorithms with wireless sensor networks. We propose an algorithm that relies on a stochastic characterization of the uncertainties in the propagation model. Due to that the path loss factor is unknown and the localization is only based on RSS me...
Conference Paper
Full-text available
The methods for measuring the exposure to high noise levels are mainly oriented to the working environment; however, listening to music in personal music players is a source of exposure whose analysis requires other tools. We hereby present the design of a system able to analyze and evaluate this exposure using various methods: the personal headpho...
Article
Full-text available
A diagnostic system for sleep apnea based on oxygen saturation and RR intervals obtained from the EKG (electrocardiogram) is proposed with the goal to detect and quantify minute long segments of sleep with breathing pauses. We measured the discriminative capacity of combinations of features obtained from RR series and oximetry to evaluate improveme...
Article
Full-text available
In this paper the permutation entropy (PE) obtained from heart rate variability (HRV) is analyzed in a statistical model. In this model we also integrate other feature extraction techniques, the cepstrum coefficients derived from the same HRV and a set of band powers obtained from the electrocardiogram derived respiratory (EDR) signal. The aim of t...
Book
The Spanish Thematic Network on Speech Technology (RTTH) and the ISCA-Special Interest Group on Iberian Languages (SIG-IL) present the selected papers of IberSpeech 2014, Joint VIII Jornadas en Tecnologías del Habla and IV Iberian SLTech Workshop, held in Las Palmas de Gran Canaria, Spain, November 19-21. The articles are organized into four differ...
Conference Paper
Full-text available
Permutation entropy obtained from heart rate variability (HRV) is analyzed in a statistical model integrating electrocardiogram derived respiratory (EDR) features and cepstrum coefficients in order to detect obstructive sleep apnea (OSA) events. 70 ECG recordings from Physionet database are divided into a learning set and a test set of equal size....
Article
In this paper, Detrended Fluctuation Analysis (DFA) of Heart Rate Variability (HRV) is applied in order to study the performance of a classification system of Obstructive Sleep Apnea (OSA), that integrates other variables as cepstrum coefficients and filter banks (FBANK) obtained from HR V The database contains 70 records, divided into two equal-si...
Book
Full-text available
This book constitutes the refereed proceedings of the IberSPEECH 2014 Conference, held in Las Palmas de Gran Canaria, Spain, in November 19-21, 2014. The 29 papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on speech production, analysis, coding and synthesis; speaker and languag...
Conference Paper
Full-text available
Two automatic statistical methods for the classification of the obstructive sleep apnoea syndrome based on the cepstrum coefficients of the RR series obtained from the Electrocardiogram (ECG) are presented. We study the effect of working with Linear Discriminant Analysis (LDA) and compare its performance with a reference detector based on Support V...
Conference Paper
Full-text available
We present a new method for DOA estimation that relies on the assumption that the sources can be modelled as ARMA. A matrix formulation is introduced in the frequency domain so that the available information from the sources can be incorporated thus allowing the DOA estimation with a few sensors and achieve good estimates with acceptable computatio...
Article
Full-text available
We address the problem of estimating the path loss factor and its integration in RSS-based localization algorithms with wireless sensor networks. We propose an algorithm that relies on a stochastic characterization of the uncertainties in the propagation model. Due to that the path loss factor is unknown and the localization is only based on RSS me...
Article
Full-text available
This paper presents a sleep stage scoring method based on a Hidden Markov Model (HMM) with the goal of obtaining differences between good and bad sleepers according to the Self Rating Questionnaire for Sleep and Awakening Quality (SSA). For the design of the model, we study several parameterization techniques, the model topology and the training st...
Article
Full-text available
In this paper we propose a classification method in the context of Boosting called Transformed Space Boosting (TSB). Our aim is to develop the idea of using a combination of Gaussian Mixture Models and transformation matrices to design 'non-weak' base learners in Boosting strategies. The use of transformation matrices makes it possible to do a line...
Conference Paper
Full-text available
We present a new method for improving the classification score in the problem of binary hypothesis testing where the classes are modeled by a Gaussian mixture. We define a cost function which is based on the Chernoff distance and from it a transformation matrix is estimated that maximizes the separation between the classes. Once defined the cost fu...
Conference Paper
Full-text available
This paper proposes a marine mammal classification method that relies in the assumption that the sources are autoregressive (AR). By incorporating the AR coefficients of each source the author make explicit their contribution to the signals at array sensors. A logarithmic likelihood function is introduced in the frequency domain so that all availab...
Conference Paper
In this paper we propose a wide-band direction-of-arrival estimation method that relies in the assumption that the sources are autoregressive. A matrix formulation is introduced in the frequency domain so that all available information from the sources can be incorporated thus allowing a new insight in the estimation process. We show that it is pos...

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