Описание: Medical informatics lies at the intersection of computer science and medicine, and understanding critical aspects of both fields provides for more proficient practitioners. Biomedical Informatics: An Introduction to Information Systems and Software in Medicine and Health supplies a cohesive narrative of the multidisciplinary concepts linking the field.This complete medical informatics textbook begins by reviewing the IT aspects of informatics, including systems architecture, electronic health records, interoperability, privacy and security, cloud computing, mobile healthcare, imaging, data capture, and design issues. Next, the text provides case studies that demonstrate the roll out of electronic health records (EHRs) in hospitals.The third section incorporates four anatomy and physiology lectures that focus on the physiological basis behind data captured in EHRs. Examples include detailed descriptions of the heart and electrical systems, lungs and alveoli, and oxygen exchange.The book includes a primer on the theoretical concepts that underpin the science behind medical informatics, including an Anatomy & Physiology Essentials guide. It also contains a tutorial on application development to help students understand the tools for improving user interfaces for EHRs on mobile platforms.The author uses a student-friendly organizational structure that supplies students with a clear demarcation between essential and optional material. The text supplies clear delineation between Level I, the basic concepts every biomedical informatics professional needs to master; Level II, applied concepts and examples; and Level III, advanced topics. This format allows undergraduate and graduate instructors and professionals in the field to focus quickly on the essential topics, and if interested, delve into Level III advanced topics.The book includes links to documents and standards sources so students can explore each idea described in more detail. Instructor’s manual, solutions manual, videos, figure slides, and lecture slides are available upon qualified course adoption.
This book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results. As such, it is of interest to university researchers, graduate students, and engineers in the fields of automation, computer science, and electrical engineering wishing to learn about the fundamental principles, methods, algorithms, and applications in the field of robust adaptive critic control. In addition, it promotes the development of robust adaptive critic control approaches, and the construction of higher-level intelligent systems.
Автор: Heidar A. Talebi; Farzaneh Abdollahi; Rajni V. Pat Название: Neural Network-Based State Estimation of Nonlinear Systems ISBN: 1441914374 ISBN-13(EAN): 9781441914378 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text offers neural network schemes for state estimation, system identification and fault detection. It covers mathematical proof of stability, experimental evaluation, and robustness against unmolded dynamics, external disturbances and measurement noises.
Автор: Ding Zhengtao Название: Nonlinear and Adaptive Control Systems ISBN: 1849195749 ISBN-13(EAN): 9781849195744 Издательство: Неизвестно Цена: 23335.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An adaptive system for linear systems with unknown parameters is a nonlinear system. The analysis of such adaptive systems requires similar techniques to analysis for nonlinear systems. Therefore it is natural to treat adaptive control as a part of nonlinear control systems.
Nonlinear and Adaptive Control Systems treats nonlinear control and adaptive control in a unified framework, presenting the major results at a moderate mathematical level, suitable to MSc students and engineers with undergraduate degrees. Topics covered include introduction to nonlinear systems; state space models; describing functions for common nonlinear components; stability theory; feedback linearization; adaptive control; nonlinear observer design; backstepping design; disturbance rejection and output regulation; and control applications, including harmonic estimation and rejection in power distribution systems, observer and control design for circadian rhythms, and suppression of flutters in aircraft.
Nonlinear and Adaptive Control Systems is of interest to postgraduate students and senior graduate students in control engineering, and in other engineering disciplines relating to dynamic modelling and control, including electrical and electronic engineering, aerospace engineering, and chemical engineering, as well as researchers and engineers working on nonlinear and adaptive control.
This book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results. As such, it is of interest to university researchers, graduate students, and engineers in the fields of automation, computer science, and electrical engineering wishing to learn about the fundamental principles, methods, algorithms, and applications in the field of robust adaptive critic control. In addition, it promotes the development of robust adaptive critic control approaches, and the construction of higher-level intelligent systems.
Описание: Identification and Adaptive Control for Nonlinear Systems and Applications: Applied Mathematics in Control Engineering introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields. The major contribution of the book includes: (1) The basic concepts of nonlinear systems stability analysis and nonlinear systems control method. (2) The stability analysis of complex nonlinear system with adaptive neural networks control. (3) The nonlinear systems adaptive sliding mode controller design of complex nonlinear systems. (4) Some industrial application. The book gives an introduction to basic nonlinear systems architectures for adaptive control methods. Emphasis is placed on the mathematical analysis of these systems, on methods of controlling them for adaptive control and on their application to practical engineering problems in such areas as aircraft path planning. This book enables audience to understand the basic architectures of control science and engineering, and to master classical and advanced design method for nonlinear system.
Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic architecture of control science and engineering.
Introduces nonlinear systems' basic knowledge, analysis and control methods, along with applications in various fields
Offers instructive examples and simulations, including source codes
Provides the basic architecture of control science and engineering
Описание: Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. . . This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering.
Автор: F W Lewis, S. Jagannathan , A Yesildirak Название: Neural Network Control of Robots and Nonlinear Systems ISBN: 0748405968 ISBN-13(EAN): 9780748405961 Издательство: Taylor&Francis Рейтинг: Цена: 35218.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A graduate text providing an authoritative account of neural network Controllers For Robotics And Non-Linear Systems. It Offers Treatment Of A general and streamlined design procedure for NN controllers and tables and examples illustrate the
Автор: Bongsob Song; J. Karl Hedrick Название: Dynamic Surface Control of Uncertain Nonlinear Systems ISBN: 1447126556 ISBN-13(EAN): 9781447126553 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This rigorous and practical introduction to nonlinear control design was written by the creators of the dynamic surface control algorithm. It discusses a range of problems including DSC design, output feedback, input saturation and fault-tolerant control.
Автор: Wen Yu, Raheleh Jafari Название: Fuzzy Modeling and Control of Uncertain Nonlinear Systems ISBN: 111949155X ISBN-13(EAN): 9781119491552 Издательство: Wiley Рейтинг: Цена: 13298.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An original, systematic-solution approach to uncertain nonlinear systems control and modeling using fuzzy equations and fuzzy differential equations
There are various numerical and analytical approaches to the modeling and control of uncertain nonlinear systems. Fuzzy logic theory is an increasingly popular method used to solve inconvenience problems in nonlinear modeling. Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry using fuzzy equations and fuzzy differential equations.
The first major work to explore methods based on neural networks and Bernstein neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to industry. Readers learn how to use fuzzy techniques to solve scientific and engineering problems and understand intelligent control design and applications. The text assembles the results of four years of research on control of uncertain nonlinear systems with dual fuzzy equations, fuzzy modeling for uncertain nonlinear systems with fuzzy equations, the numerical solution of fuzzy equations with Z-numbers, and the numerical solution of fuzzy differential equations with Z-numbers. Using clear and accessible language to explain concepts and principles applicable to real-world scenarios, this book:
Presents the modeling and control of uncertain nonlinear systems with fuzzy equations and fuzzy differential equations
Includes an overview of uncertain nonlinear systems for non-specialists
Teaches readers to use simulation, modeling and verification skills valuable for scientific research and engineering systems development
Reinforces comprehension with illustrations, tables, examples, and simulations
Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number is suitable as a textbook for advanced students, academic and industrial researchers, and practitioners in fields of systems engineering, learning control systems, neural networks, computational intelligence, and fuzzy logic control.
Автор: Martin Guay, Veronica Adetola and Darryl De Haan Название: Robust And Adaptive Model Predictive Control Of Nonlinear Systems ISBN: 1849195528 ISBN-13(EAN): 9781849195522 Издательство: Неизвестно Рейтинг: Цена: 24944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model.
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