Antonio Guerrero

Autonomous University of Aguascalientes | UAA · Departamento de Estadística

This paper reviews the application of Artificial Neural Network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN architectures considered in the literature for time series forecasting purposes: Feed Forward Neura...

The present work reports on a device for the processing of electric signals and the physical interpretation of the outputs. The aim is to execute actions through external devices by analyzing the bioelectric signals from the human eye or electrooculograms (EOGs). More concretely, an EOG digital controller to work as assistive technology for motor d...

In this work, we present a numerical scheme of the Higgs Boson equation in De Sitter space. One of its main characteristics is its variational form, which translates into the modeling of the energy associated with the continuous case. The equation shown in this work is a generalization that contemplates a potential and a time-dependent diffusion co...

Several academic and budgetary applications in robotics use low-cost encoders which usually present errors inherent to the fabrication of their components or the surrounding environment. However, the data gathered from these sensors could be used successfully if the estimations based on the data are be compensated. This note presents an efficient m...

Background and objective: In this manuscript, we consider a compartmental model to describe the dynamics of propagation of an infectious disease in a human population. The population considers the presence of susceptible, exposed, asymptomatic and symptomatic infected, quarantined, recovered and vaccinated individuals. In turn, the mathematical mo...

BACKGROUND. We provide a compartmental model for the transmission of some contagious illnesses in a population. The model is based on partial differential equations, and takes into account seven sub-populations which are, concretely, susceptible, exposed, infected (asymptomatic or symptomatic), quarantined, recovered and vaccinated individuals alon...

In the present work, decision trees are employed to determine the activation patterns in electromyographic signals in multiple muscles of interest. Due to the interaction of several muscles when performing a movement , it is common for several muscles to activate simultaneously. The problem is to determine if any muscle of interest is active and, i...

In this work, we introduce a template-based computational method to recognize chords through an audio recording of a musical instrument. The algorithm is based on a temporal frequency analysis using Gabor's filter banks. These filters are centered over adjusted frequencies of musical notes in different octaves and the adjustment is accomplished in...

For the first time in the literature, a dissipation-preserving computational technique to approximate the solutions of a dissipative generalization of the Higgs boson equation in the de Sitter space–time is proposed. The model is a multidimensional system which considers a generalized potential and a general time-dependent diffusion coefficient. Th...

In this work, a method to calculate the threshold value in the detection of activity phases of electromyographic signals is introduced. The criterion used by the method is based on the number of runs produced by the threshold process. The novelty of this technique lies in that the threshold value is theoretically determined employing the statistica...

In this work, we introduce an efficient method for lossy compression of digitalized documents. The method uses a dictionary which consists of class representatives defined using a minimum entropy criterion. The algorithm initially identifies the different symbols contained in a document image, and then the symbols are grouped in classes by means of...

In this work, we consider the problem of identifying activity phases in electromyography signals, and various other potential types of electrical and non-electrical biological signals such as electroneurograms, electroencephalograms, voice and ultrasounds. The solution to this problem has been provided under relatively limited scenarios. The purpos...

Electromyograms are biomedical signals which are detected through electrodes. These signals represent measurements of the electric potentials associated to muscles contractions, and they are physically important in view that they provide information on the health of individuals. The computational modeling of electromyograms has been mainly carried...

In this work, we introduce two novel methodologies to compute the envelope of superficial electromyography signals. Our methods are based on the detection of activation and deactivation patterns using a change-point approach on the variances of the sample. More concretely, an iterative algorithms is proposed to select the change-points between two...

We design a numerical method to approximate the solutions of some generalized forms of two-dimensional models of mathematical physics. Concretely, we propose a finite-difference methodology that guarantees that, under certain analytical conditions on the model and computer parameters, estimates within an interval I will evolve into new estimates wh...

In the present work, we develop a computational technique to approximate the changes of phase in temporal series associated to electric signals of muscles which perform activities at three different levels of intensity. We suppose that the temporal series are samples of independent, normally distributed random variables with mean equal to zero, and...

In this work, we present a computational method to approximate the occurrence of the change-points in a temporal series consisting of independent and normally distributed observations, with equal mean and two possible variance values. This type of temporal series occurs in the investigation of electric signals associated to rhythmic activity patter...

In this work, we propose a heteroscedastic method in the detection of activity patterns of electroneurographic and electromyogram signals involved in rhythmic activities of nerves and muscles, respectively. The electric behavior observed in such signals is characterized by phases of activity and silence. The beginning and the length of electrically...