Pedro Quintana

University of Las Palmas de Gran Canaria | ULPGC · Department of Signals and Communications

This paper presents a new procedure for phase detector measurements that allows the use of generators that share a 10 MHz reference oscillator but do not synchronize in phase, in other words, quasi-synchronized RF generators. The objectives are taking advantage of the benefits of using two generators but recovering lower-cost generators that have w...

This article presents a radio frequency system that can be used to perform precise vertical landings of drones. The system is based on the three-way phase shift detection of a signal transmitted from the landing point. The antenna system is designed by taking into account parameters such as landing tracking area, analog-to-digital converter (ADC) r...

This paper presents a circuit for precise vertical landing of drones based on a three phase-shifts detection of a single frequency transmitted from the landing point. The circuit can be considered as a new navigation sensor that assists in guidance corrections for landing at a specific point. The circuit has three inputs to which the signal transmi...

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...

Rain fall detection has been an important factor under study in a multitude of applications: estimation of floods in order to minimize damage before an environmental risk situation, rain removal from images, agriculture field, etc. Actually, there are numerous methods implemented in order to try to solve this issue. For example, some of them are ba...

En este trabajo se presenta el proyecto de Innovación Educativa Acción Tutorial on-line, concedido al Grupo de Innovación Educativa en Sistemas de Telecomunicación de la Universidad de Las Palmas de Gran Canaria, que tiene como objetivos el proporcionar un estudio sobre herramientas virtuales para tutorías online en ingeniería y usar la herramienta...

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...

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...

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...

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....

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...

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...

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...

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...

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...

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...

The objective of this paper is to propose the use of a speech model with psychoacoustical information to distinguish between the open and closed phases of the vocal folds, in order to monitor formants as phonetic speech characteristics. Taking a frequency warped ARMA model for each one of the phases, the aim is to integrate the information of vario...

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...

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...