Ponce, Hiram
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Ponce, Hiram
Official Name
Ponce Espinosa, Hiram Eredín
Alternative Name
hponce
Main Affiliation
ORCID
Scopus Author ID
54911890000
Researcher ID
K-7593-2019

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Challenges and trends in multimodal fall detection for healthcare

2020 , Ponce, Hiram , Brieva, Jorge , Martinez-Villaseñor, Lourdes , Moya-Albor, Ernesto , HIRAM EREDIN PONCE ESPINOSA;376768 , JORGE EDUARDO BRIEVA RICO;121435

This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human–machine interaction, among others.

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Robótica aplicada con LabVIEW y LEGO

2015 , Ponce, Hiram , HIRAM EREDIN PONCE ESPINOSA;376768 , Campus Ciudad de México

El objetivo de esta obra es mostrar de forma teórica y práctica las técnicas más importantes utilizadas en la academia y la industria para el desarrollo de sistemas robóticos, y para esto se exponen desde los conceptos básicos de robótica hasta los algoritmos de control y las técnicas de planificación de trayectorias. En especial, se hace uso de los sistemas robóticos LEGO Mindstorms NXT junto con la plataforma de desarrollo LabVIEW. Aprenda qué es un robot LEGO NXT y cual es el entorno de programación NXT. Conozca los sistemas de control empleando robots NXT, así como el entorno de programación de los LEGO Mindstorms. Desarrolle sus propias aplicaciones de planificación de ruta de planificación de trayectorias con espacios variantes en el tiempo. ©2015 Alfaomega.

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Artificial organic networks : artificial intelligence based on carbon networks

2014 , Ponce, Hiram , HIRAM EREDIN PONCE ESPINOSA;376768 , Campus Ciudad de México

This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · classification; and · audio-signal filtering. The text finishes with a consideration of directions in which AHNs could be implemented and developed in future. A complete LabVIEW™ toolkit, downloadable from the book’s page at springer.com enables readers to design and implement organic neural networks of their own. The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks. ©2014 Springer.

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Preface

2024-01-01 , Ponce, Hiram

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Nature-inspired computing for control systems

2016 , Ponce, Hiram

The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practitioners in the field of control engineering. ©2016 © 2022 Springer Nature Switzerland AG. Part of Springer Nature.

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