Gilardi Velázquez, Héctor Eduardo
Main Affiliation
Preferred name
Gilardi Velázquez, Héctor Eduardo
Official Name
Gilardi Velázquez, Héctor Eduardo
ORCID
0000-0002-4978-4526
Researcher ID
AAT-3915-2020
Scopus Author ID
57195627627
31 results
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Item type:Publication, Implementation of the cFS framework for the development of software in aerospace missions: first application in an undergraduate program in Mexico(2021); R.A. Gutiérrez-Esparza1 11Scopus© Citations 7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optical Energy Increasing in a Synchronized Motif-Ring Array of Autonomous Erbium-Doped Fiber Lasers(2024)10Scopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Topological Machine Learning Framework for Phase Portrait Classification of Nonlinear Dynamical Systems(MDPI AG, 2026-06-02)7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A comparison study of diffusion properties in Brownian motion models: From the stochastic to discrete and continuous chaotic-based models(AIP Publishing, 2025-04-01)14Scopus© Citations 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Comparative Study of Brownian Dynamics Based on the Jerk Equation Against a Stochastic Process Under an External Force Field(MDPI AG, 2025-02-28); <jats:p>Brownian motion has been studied since 1827, leading to numerous important advances in many branches of science and to it being studied primarily as a stochastic dynamical system. In this paper, we present a deterministic model for the Brownian motion for a particle in a constant force field based on the Ornstein–Uhlenbeck model. By adding one degree of freedom, the system evolves into three differential equations. This change in the model is based on the Jerk equation with commutation surfaces and is analyzed in three cases: overdamped, critically damped, and underdamped. The dynamics of the proposed model are compared with classical results using a random process with normal distribution, where despite the absence of a stochastic component, the model preserves key Brownian motion characteristics, which are lost in stochastic models, giving a new perspective to the study of particle dynamics under different force fields. This is validated by a linear average square displacement and a Gaussian distribution of particle displacement in all cases. Furthermore, the correlation properties are examined using detrended fluctuation analysis (DFA) for compared cases, which confirms that the model effectively replicates the essential behaviors of Brownian motion that the classic models lose.</jats:p>23Scopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, On the Effect of Asymmetric Coupling in Pairs of Chaotic Oscillators for Different Input–Output Combinations(WORLD SCIENTIFIC, 2025-12-11)12 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Novel Method for Designing Multistable Systems with a Hidden AttractorDynamical systems with chaotic attractors are an interesting topic not only for their complex behavior but also due to their potential applications. Along with the chaos, systems can also present interesting features such as multistability, global basin of attractions, entangled basins of attraction, etc. The existence of chaotic systems with multistable hidden attractors increases complexity but also the number of potential applications. Several systems with hidden attractors have already been found by numerical search; however, it is usually not possible to substantially modify their equations or attractor geometry. In this study, an approach to generate multistable systems with a class of hidden attractors is proposed. The approach allows for the control of the amplitude and frequency of the chaotic signals of the different attractors as well as their location in the space by preserving a simple matrix form in the vector field. Particular cases with mono-stability and multistability are shown. Also, chaotic signals obtained through the approach are used in a pseudorandom number generator to obtain binary sequences which are tested under the Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications provided by the National Institute of Standards and Technology (NIST).15 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 1 11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis of particle settlement characteristics in a one-dimensional deterministic model(2025); E. Campos-Cantón<jats:p> In this paper, we investigate how particles settle in a one-dimensional deterministic model. We leverage a model for deterministic Brownian motion and introduce boundary conditions to simulate particle settling. By adjusting parameters in the Jerk equation, we explore how different diffusion, and the size of the settling space affect the particles’ behavior. We analyze how these parameters influence the settling time and its relationship to the dispersion medium. Additionally, we examine statistical properties as follows: the average settling time, the probability distributions for mean displacement, and how the probability distribution of settling times changes with the size of the space. </jats:p>1 10Scopus© Citations 1