Esteban Tlelo-Cuautle – författare

Mathematicians have devised different chaotic systems that are modeled by integer or fractional-order differential equations, and whose mathematical models can generate chaos or hyperchaos. The numerical methods to simulate those integer and fractional-order chaotic systems are quite different and their exactness is responsible in the evaluation of characteristics like Lyapunov exponents, Kaplan-Yorke dimension, and entropy. One challenge is estimating the step-size to run a numerical method. It can be done analyzing the eigenvalues of self-excited attractors, while for hidden attractors it is difficult to evaluate the equilibrium points that are required to formulate the Jacobian matrices. Time simulation of fractional-order chaotic oscillators also requires estimating a memory length to achieve exact results, and it is associated to memories in hardware design. In this manner, simulating chaotic/hyperchaotic oscillators of integer/fractional-order and with self-excited/hidden attractors is quite important to evaluate their Lyapunov exponents, Kaplan-Yorke dimension and entropy. Further, to improve the dynamics of the oscillators, their main characteristics can be optimized applying metaheuristics, which basically consists of varying the values of the coefficients of a mathematical model. The optimized models can then be implemented using commercially available amplifiers, field-programmable analog arrays (FPAA), field-programmable gate arrays (FPGA), microcontrollers, graphic processing units, and even using nanometer technology of integrated circuits.

The book describes the application of different numerical methods to simulate integer/fractional-order chaotic systems. These methods are used within optimization loops to maximize positive Lyapunov exponents, Kaplan-Yorke dimension, and entropy. Single and multi-objective optimization approaches applying metaheuristics are described, as well as their tuning techniques to generate feasible solutions that are suitable for electronic implementation. The book details several applications of chaotic oscillators such as in random bit/number generators, cryptography, secure communications, robotics, and Internet of Things.

Mathematicians have devised different chaotic systems that are modeled by integer or fractional-order differential equations, and whose mathematical models can generate chaos or hyperchaos. The numerical methods to simulate those integer and fractional-order chaotic systems are quite different and their exactness is responsible in the evaluation of characteristics like Lyapunov exponents, Kaplan-Yorke dimension, and entropy. One challenge is estimating the step-size to run a numerical method. It can be done analyzing the eigenvalues of self-excited attractors, while for hidden attractors it is difficult to evaluate the equilibrium points that are required to formulate the Jacobian matrices. Time simulation of fractional-order chaotic oscillators also requires estimating a memory length to achieve exact results, and it is associated to memories in hardware design. In this manner, simulating chaotic/hyperchaotic oscillators of integer/fractional-order and with self-excited/hidden attractors is quite important to evaluate their Lyapunov exponents, Kaplan-Yorke dimension and entropy. Further, to improve the dynamics of the oscillators, their main characteristics can be optimized applying metaheuristics, which basically consists of varying the values of the coefficients of a mathematical model. The optimized models can then be implemented using commercially available amplifiers, field-programmable analog arrays (FPAA), field-programmable gate arrays (FPGA), microcontrollers, graphic processing units, and even using nanometer technology of integrated circuits.

The book describes the application of different numerical methods to simulate integer/fractional-order chaotic systems. These methods are used within optimization loops to maximize positive Lyapunov exponents, Kaplan-Yorke dimension, and entropy. Single and multi-objective optimization approaches applying metaheuristics are described, as well as their tuning techniques to generate feasible solutions that are suitable for electronic implementation. The book details several applications of chaotic oscillators such as in random bit/number generators, cryptography, secure communications, robotics, and Internet of Things.

This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of artificial intelligence, cryptography, embedded hardware, electronics, the Internet of Things, and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research.

Features

This book can be used by graduate students, industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling, simulation, and optimization of complex systems, cryptography, electronics, healthcare, control systems, Internet of Things, security, and unmanned systems such as submarines, drones, and robots.

This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of artificial intelligence, cryptography, embedded hardware, electronics, the Internet of Things, and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research.

Features

This book can be used by graduate students, industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling, simulation, and optimization of complex systems, cryptography, electronics, healthcare, control systems, Internet of Things, security, and unmanned systems such as submarines, drones, and robots.

This book presents theory, design methods and novel applications for integrated circuits for analog signal processing.  The discussion covers a wide variety of active devices, active elements and amplifiers, working in voltage mode, current mode and mixed mode.  This includes voltage operational amplifiers, current operational amplifiers, operational transconductance amplifiers, operational transresistance amplifiers, current conveyors, current differencing transconductance amplifiers, etc.  Design methods and challenges posed by nanometer technology are discussed and applications described, including signal amplification, filtering, data acquisition systems such as neural recording, sensor conditioning such as biomedical implants, actuator conditioning, noise generators, oscillators, mixers, etc.

This book details the simulation and optimization of integer and fractional-order chaotic systems, and how they can be implemented in the analog and digital domains using FPAAs and FPGAs. Design guidelines are provided to use commercially available electronic devices, and to perform hardware descriptions of integer/fractional-order chaotic systems programming in VHDL. Finally, several engineering applications oriented to cryptography, internet of things, robotics and chaotic communications, are detailed to highlight the usefulness of FPAA/FPGA based integer/fractional-order chaotic systems.

This book is a compilation of scientific articles written by recognized researchers, and select students, participating in the Second Conference on the Study of Complex Systems and their Applications (EDIESCA 2021). EDIESCA 2021 arose from the need for academic and research groups that carry out this scientific research to disseminate their results internationally. The study and characterization of systems with non-linear and/or chaotic behavior has been of great interest to researchers around the world, for which many important results have been obtained with various applications. The dynamic study of chaotic oscillators of different models, such as Rössler, Lorenz, and Chua, has generated important advances in understanding of chemical reactions, meteorological behavior, design of electronic devices, and other applications. Topics at the event included applications for communications systems by masking techniques, financial behavior, networks analysis, nonlinear lasers, numerical modeling, electronic design, and other interesting topics in the area of complex systems. Additionally, there are results on numerical simulation and electronic designs to generate complex dynamic behaviors.

This book is a compilation of scientific articles written by recognized researchers participating in the Fourth Conference on the Study of Complex Systems and their Applications (EDIESCA 2023), held in Monterrey, Mexico. EDIESCA arose from the need for academic and research groups that carry out this scientific research to disseminate their results internationally. The study and characterization of systems with non-linear and/or chaotic behavior has been of great interest to researchers around the world, for which many important results have been obtained with various applications. The dynamic study of chaotic oscillators of different models, such as Rössler, Lorenz, and Chua, has generated important advances in the understanding of chemical reactions, meteorological behavior, design of electronic devices, and other applications. Topics at the event included applications for communications systems by masking techniques, financial behavior, networks analysis, nonlinear lasers, numerical modeling, electronic design, and other interesting topics in the area of complex systems. Additionally, there are results on numerical simulation and electronic designs to generate complex dynamic behaviors.

This book discusses the details of random number generation (RNG) as a key technology that is used for information security in various fields, such as electronic commerce and authentication. Readers will see how random numbers are used in various applications such as in the generation of keys for data encryption, games, lotteries, sampling, simulations, statistical sampling, search/sort algorithms, and gambling. The authors describe how the classification of RNGs encompasses linear and nonlinear (chaotic) pseudo and truly random number generators, and how they can be evaluated by applying statistical tests.