This monograph provides the reader with a systematic treatment of robust filter design, a key issue in systems, control and signal processing, because of the fact that the inevitable presence of uncertainty in system and signal models often degrades the filtering performance and may even cause instability. The methods described are therefore not subject to the rigorous assumptions of traditional Kalman filtering. The monograph is concerned with robust filtering for various dynamical systems with parametric uncertainties and focuses on parameter-dependent approaches to filter design. Classical filtering schemes, like "H"2 filtering and "H"Y filtering, are addressed and emerging issues such as robust filtering with constraints on communication channels and signal frequency characteristics are discussed. The text features:

. design approaches to robust filters arranged according to varying complexity level and emphasizing robust filtering in the parameter-dependent framework for the first time;

. guidance on the use of special realistic phenomena or factors to describe problems more accurately and to improve filtering performance;

. a unified linear matrix inequality formulation of design approaches for easy and effective filter design;

. demonstration of the techniques of matrix decoupling technique, the generalized Kalman Yakubovich Popov lemma, the free weighting matrix technique and the delay modelling approach, in robust filtering;

. numerous easy-to-follow simulation examples, graphical and tabular illustrations to help the reader understand the filter design approaches developed; and

. an account of emerging issues on robust filtering for research to inspire future investigation.

"Robust Filtering for Uncertain Systems" will be of interest to academic researchers specializing in linear, robust and optimal control and estimation and to practitioners working in tracking and network control or signal filtering, detection and estimation. Graduate students learning control and systems theory, signal processing or applied mathematics will also find the book to be a valuable resource.

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• Describes machine learning in plain language to a non-technical audience • Explains how to manage machine learning projects to deliver value • Highlights important considerations when deploying machine learning systems in organisations

This book bridges principles and real-world applications, while also providing thorough theory and technology for the development of artificial intelligence and robots. A lack of cross-pollination between AI and robotics research has led to a lack of progress in both fields. Now that both technologies have made significant strides, there is increased interest in combining the two domains in order to create a new integrated AI and robotics trend. In order to achieve wiser urbanization and more sustainable development, AI in smart cities will play a significant part in equipping the cities with advanced features that will allow residents to safely move about, stroll, shop, and enjoy a more comfortable way of life. If you are a student, researcher, engineer, or professional working in this field, or if you are just curious in the newest advancements in robotics and artificial intelligence for cybersecurity, this book is for you!

The rise of the information age and the digital economy has dramatically changed engineering. With tremendous advances in computing and communication systems, causing major organizational upheaval, all fueled by complexity, globalization, short cycle times, and lean supply chains, the functions of engineers have significantly changed. Engineers must be technically savvy and have product management and costing skills all while working in a distributed and often unstable environment. This new edition textbook is updated to cover the integration of cost, risk, value, scheduling, and information technologies going beyond basic engineering economics. Engineering Economics of Life Cycle Cost Analysis, Second Edition offers a systems and life cycle or total ownership cost perspective. It presents advanced costing techniques such as simulation-based costing, decision analysis, complex systems costing, software, big data, and cloud computing estimation. Examples and problems demonstrating these techniques with real-world applications are also included. All engineers will find this book useful, but it is mainly written for systems engineers, engineering management, and industrial engineers along with graduate courses on advanced engineering economic analysis and cost management, and financial analysis for engineers. To assist with classroom teaching, the textbook provides an instructor's manual for qualified course adoption and downloadable Excel solutions.

Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. The various application areas that are image-centric and video are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering CNN, RNN and its types for learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas

This book focuses on and promotes the applications of the diverse tools and techniques of industrial engineering to the design and operation of systems in industry, business, the government, and the military. Industrial engineering is growing rapidly as an educational option and is a practice favorite in Asia, South America, and many parts of Europe. This book will meet the needs of those growth markets. Industrial Engineering in Systems Design: Guidelines, Practical Examples, Tools, and Techniques offers a wide range of engineering tools from checklists to in-depth analysis guidelines for systems design and operation. The book discusses the integration of industrial and systems engineering from both qualitative and quantitative techniques for systems design. In addition, guidelines for operational resiliency for industry in the case of disruptions, such as a pandemic are covered, and the book provides case examples for industries in developing and under-developed nations. The inclusion of practical examples of where industrial engineering has contributed to the advancement and survival of industries makes this book a very interesting and useful resource. This is a practical guide for professional engineers and consultants involved in the design and operation of systems, particularly manufacturing, production, and supply chain systems, and can also be used as a reference for students.

The concept of the smart grid promises the world an efficient and intelligent approach of managing energy production, transportation, and consumption by incorporating intelligence, efficiency, and optimality into the power grid. Both energy providers and consumers can take advantage of the convenience, reliability, and energy savings achieved by real-time and intelligent energy management. To this end, the current power grid is experiencing drastic changes and upgrades. For instance, more significant green energy resources such as wind power and solar power are being integrated into the power grid, and higher energy storage capacity is being installed in order to mitigate the intermittency issues brought about by the variable energy resources. At the same time, novel power electronics technologies and operating strategies are being invented and adopted. For instance, Flexible AC transmission systems and phasor measurement units are two promising technologies for improving the power system reliability and power quality. Demand side management will enable the customers to manage the power loads in an active fashion. As a result, modeling and control of modern power grids pose great challenges due to the adoption of new smart grid technologies. In this book, chapters regarding representative applications of smart grid technologies written by world-renowned experts are included, which explain in detail various innovative modeling and control methods.

The book focuses on new theoretical results and techniques in the field of intelligent systems and control. It provides in-depth studies on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. Given its scope, the book will benefit all researchers, engineers, and graduate students who want to learn about cutting-edge advances in intelligent systems, intelligent control, and artificial intelligence.

An introduction to the model-based approach and the mclust R package A detailed description of mclust and the underlying modeling strategies An extensive set of examples, color plots and figures along with the R code for reproducing them Supported by a companion website including the R code to reproduce the examples and figures presented in the book, errata, and other supplementary material

This book provides readers to the vision of Society 5.0, which was originally proposed in the fifth Basic Science and Technology Plan by Japan's government for a technology-based, human-centered society, emerging from the 4th industrial revolution (Industry 4.0). The implementation of AI and other modern techniques in a smart society requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. Features Provides an overview of basic concepts of Society 5.0 as well as the main pillars that supports the implementation of Society 5.0. Contains the most recent research analysis in the domain of computer vision, signal processing and computing sciences for facilitating the smart homes, buildings, transport, facilities, environmental conditions and cities, and the benefits these offer to a nation. Presents the readers with practical approaches of using AI and other algorithms for smart ecosystem to deals with human dynamics, the social objects, and their relations. Deals with the utilization of AI tools and other modern techniques for smart society as well as the current challenging issues and its solutions for transformation to Society 5.0. This book is aimed at graduate and post graduate students, researchers, academicians working in the field of computer science, artificial intelligence, and machine learning.

This book introduces readers to numerous multiplicative inverse functional equations and their stability results in various spaces. This type of functional equation can be of use in solving many physical problems and also has significant relevance in various scientific fields of research and study. In particular, multiplicative inverse functional equations have applications in electric circuit theory, physics, and relations connecting the harmonic mean and arithmetic mean of several values. Providing a wealth of essential insights and new concepts in the field of functional equations, the book is chiefly intended for researchers, graduate schools, graduate students, and educators, and can also used for seminars in analysis covering topics of functional equations.

This book introduces the reader to a novel method of mathematical description, analysis and design of digital control systems, which makes it possible to take into account, in the most complete form, specific features of interaction between continuous-time and discrete time processes.

Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB (R) and Simulink (R). This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino (R). The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB (R) and Simulink (R) codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com.

i. This book will contain AI, ML, DL, big data and security never before considered ii. Innovative artificial intelligence techniques and algorithms iii. Only emerging from recent research and development, e.g. AI for big data from security perspective, which are not covered in any existing texts iv. Artificial Intelligence for big data and security Applications with advanced features v. Key new finding of machine learning and deep learning for Security Applications

Artificial intelligence (AI) and digital engineering have become prevalent in business, industry, government, and academia. However, the workforce still has a lot to learn on how to leverage them. This handbook presents the preparatory and operational foundations for the efficacy, applicability, risk, and how to take advantage of these tools and techniques. "Handbook of Mathematical and Digital Engineering Foundations for Artificial Intelligence: A Systems Methodology" provides a guide for using digital engineering platforms for advancing AI applications. The book discusses an interface of education and research in the pursuit of AI developments and highlights the facilitation of advanced education through AI and digital engineering systems. It presents an integration of soft and hard skills in developing and using AI and offers a rigorous systems approach to understanding and using AI. This handbook will be the go-to resource for practitioners and students on applying systems methodology to the body of knowledge of understanding, embracing, and using digital engineering tools and techniques.

This edited volume on "Recent Advances in Renewable Energy" presents a selection of refereed papers presented at the 1st International Conference on Electrical Systems and Automation. The book provides rigorous discussions, the state of the art, and recent developments in the field of renewable energy sources supported by examples and case studies, making it an educational tool for relevant undergraduate and graduate courses. The book will be a valuable reference for beginners, researchers, and professionals interested in renewable energy.

This book provides insights on how to approach and utilize data science tools, technologies and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI-technologies, and their inter-connections. Description of various technology and methodology approaches, and their purpose and benefits when developing AI-solution in industrial contexts is included. In addition, it summarizes experiences from AI technology deployment projects from several industrial sectors. Features: Presents compendium of methodologies and technologies in Industrial AI and digitalization. Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept. Covers a broad range of academic and industrial issues within the field of asset management. Discusses impact of Industry 4.0 in other sectors. Includes a dedicated chapter on real-time case studies. This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and ML, engineering managers, operational and maintenance specialists, asset managers, digital and AI manufacturing specialists.

Focuses on several core aspects of Industry 4.0 on computer vision & imaging. Highlights several exciting techniques for disease prediction, NLP, image captioning, flood level assessment, crop classifications, and fabrication of smart wheelchairs. Covers several chapters on Natural Language Processing (NLP), focusing on Bangla language. Chapters presented in a step-by-step manner so that young minds can understand and implement easily.

The text focuses on mathematical modeling and applications of advanced techniques of machine learning, and artificial intelligence, including artificial neural networks, evolutionary computing, data mining, and fuzzy systems to solve performance and design issues more precisely. Intelligent computing encompasses technologies, algorithms, and models in providing effective and efficient solutions to a wide range of problems including the airport's intelligent safety system. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including industrial engineering, manufacturing engineering, computer engineering, and mathematics. The book- Discusses mathematical modeling for traffic, sustainable supply chain, vehicular Ad-Hoc networks, internet of things networks with intelligent gateways. Covers advanced machine learning, artificial intelligence, fuzzy systems, evolutionary computing, data mining techniques for real-world problems. Presents applications of mathematical models in chronic diseases such as kidney and coronary artery diseases. Highlights advances in mathematical modeling, strength, and benefits of machine learning and artificial intelligence, including driving goals, applicability, algorithms, and processes involved. Showcases emerging real-life topics on mathematical models, machine learning, and intelligent computing using an interdisciplinary approach. The text presents emerging real-life topics on mathematical models, machine learning, and intelligent computing in a single volume. It will serve as an ideal text for senior undergraduate, graduate students, and researchers in diverse fields domains including industrial and manufacturing engineering, computer engineering, and mathematics.

Gives broad perspective on 5G communications with a focus on smart cities Discusses artificial intelligence in future wireless communication and its applications Provides a systemic and comprehensive coverage of 6G technologies, challenges and use cases Explores role of future wireless in safety, health, and transport in smart cities Includes case studies of future wireless communications

This book presents a differential geometric method for designing nonlinear observers for multiple types of nonlinear systems, including single and multiple outputs, fully and partially observable systems, and regular and singular dynamical systems. It is an exposition of achievements in nonlinear observer normal forms. The book begins by discussing linear systems, introducing the concept of observability and observer design, and then explains the difficulty of those problems for nonlinear systems. After providing foundational information on the differential geometric method, the text shows how to use the method to address observer design problems. It presents methods for a variety of systems. The authors employ worked examples to illustrate the ideas presented. Observer Design for Nonlinear Dynamical Systems will be of interest to researchers, graduate students, and industrial professionals working with control of mechanical and dynamical systems.

Stochastic modeling is a set of quantitative techniques for analyzing practical systems with random factors. This area is highly technical and mainly developed by mathematicians. Most existing books are for those with extensive mathematical training; this book minimizes that need and makes the topics easily understandable. Fundamentals of Stochastic Models offers many practical examples and applications and bridges the gap between elementary stochastics process theory and advanced process theory. It addresses both performance evaluation and optimization of stochastic systems and covers different modern analysis techniques such as matrix analytical methods and diffusion and fluid limit methods. It goes on to explore the linkage between stochastic models, machine learning, and artificial intelligence, and discusses how to make use of intuitive approaches instead of traditional theoretical approaches. The goal is to minimize the mathematical background of readers that is required to understand the topics covered in this book. Thus, the book is appropriate for professionals and students in industrial engineering, business and economics, computer science, and applied mathematics.

Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web.