Описание: As technology continues to advance in today's global market, practitioners are targeting systems with significant levels of applicability and variance. Instrumentation is a multidisciplinary subject that provides a wide range of usage in several professional fields, specifically engineering. Instrumentation plays a key role in numerous daily processes and has seen substantial advancement in recent years. It is of utmost importance for engineering professionals to understand the modern developments of instruments and how they affect everyday life.
Advancements in Instrumentation and Control in Applied System Applications is a collection of innovative research on the methods and implementations of instrumentation in real-world practices including communication, transportation, and biomedical systems. While highlighting topics including smart sensor design, medical image processing, and atrial fibrillation, this book is ideally designed for researchers, software engineers, technologists, developers, scientists, designers, IT professionals, academicians, and post-graduate students seeking current research on recent developments within instrumentation systems and their applicability in daily life.
Описание: Provides a framework for conceptual, theoretical, and applied research in regards to the relationship between technology and humans. This book is unique in the sense that it does not only cover technology, but also science, research, and the relationship between these fields and individuals` experience.
Автор: Tai-hoon Kim; Adrian Stoica; Wai-chi Fang; Thanos Название: Computer Applications for Security, Control and System Engineering ISBN: 3642352634 ISBN-13(EAN): 9783642352638 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the International Conferences on Security Technology, SecTech 2012, on Control and Automation, CA 2012, and CES-CUBE 2012, the International Conference on Circuits, Control, Communication, Electricity, Electronics, Energy, System, Signal and Simulation;
Автор: Johnson I. Agbinya Название: Applied Data Analytics - Principles and Applications ISBN: 8770220964 ISBN-13(EAN): 9788770220965 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very lage data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications and stock market data, health records and business analytics data are but a few areas of interest. Applications and platforms including R, RapidMiner and Weka provide the basis for analysis, often used by practitioners who pay little to no attention to the underlying mathematics and processes impacting the data. This often leads to an inability to explain results or correct mistakes, or to spot errors.
Applied Data Analytics - Principles and Applications seeks to bridge this missing gap by providing some of the most sought after techniques in big data analytics. Establishing strong foundations in these topics provides practical ease when big data analyses are undertaken using the widely available open source and commercially orientated computation platforms, languages and visualisation systems. The book, when combined with such platforms, provides a complete set of tools required to handle big data and can lead to fast implementations and applications.
The book contains a mixture of machine learning foundations, deep learning, artificial intelligence, statistics and evolutionary learning mathematics written from the usage point of view with rich explanations on what the concepts mean. The author has thus avoided the complexities often associated with these concepts when found in research papers. The tutorial nature of the book and the applications provided are some of the reasons why the book is suitable for undergraduate, postgraduate and big data analytics enthusiasts.
This text should ease the fear of mathematics often associated with practical data analytics and support rapid applications in artificial intelligence, environmental sensor data modelling and analysis, health informatics, business data analytics, data from Internet of Things and deep learning applications.
Описание: How does a machine learn a new concept on the basis of examples? This second edition takes account of important new developments in the field. It also deals extensively with the theory of learning control systems, now comparably mature to learning of neural networks.
Автор: Nikolaos Voros; Michael Huebner; Georgios Keramida Название: Applied Reconfigurable Computing. Architectures, Tools, and Applications ISBN: 3319788892 ISBN-13(EAN): 9783319788890 Издательство: Springer Рейтинг: Цена: 12578.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 14th International Conference on Applied Reconfigurable Computing, ARC 2018, held in Santorini, Greece, in May 2018. The 29 full papers and 22 short presented in this volume were carefully reviewed and selected from 78 submissions. In addition, the volume contains 9 contributions from research projects. The papers were organized in topical sections named: machine learning and neural networks; FPGA-based design and CGRA optimizations; applications and surveys; fault-tolerance, security and communication architectures; reconfigurable and adaptive architectures; design methods and fast prototyping; FPGA-based design and applications; and special session: research projects.
Автор: Erdal Kayacan Название: Fuzzy Neural Networks for Real Time Control Applications ISBN: 0128026871 ISBN-13(EAN): 9780128026878 Издательство: Elsevier Science Рейтинг: Цена: 12294.00 р. Наличие на складе: Поставка под заказ.
Описание:
AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS
Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book
Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book.
A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis.
You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are:
- Gradient descent
- Levenberg-Marquardt
- Extended Kalman filter
In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced.
The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully.
Описание: Presents coverage of the fundamentals of two-valued logic, multivalued logic, and fuzzy logic. Exploring the parallels between classical and fuzzy mathematical logic, this book examines the use of logic in computer science, addresses questions in automatic deduction, and describes efficient computer implementation of proof techniques.
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