Numerical Methods Using MATLAB®, Fifth Edition continues to provide a clear and rigorous introduction to a wide range of numerical methods that have practical applications. The authors’ approach is to integrate MATLAB with numerical analysis in a way which adds clarity to the numerical analysis and develops familiarity with MATLAB. MATLAB graphics and numerical output are used extensively to clarify complex problems and give a deeper understanding of their nature. The text provides an extensive reference providing numerous useful and important numerical algorithms that are implemented in MATLAB to help researchers analyze a particular outcome.By using MATLAB it is possible for the readers to tackle some large and difficult problems and deepen and consolidate their understanding of problem solving using numerical methods. Many worked examples are given together with exercises and solutions to illustrate how numerical methods can be used to study problems that have applications in the biosciences, chaos, optimization and many other fields. The text will be a valuable aid to people working in a wide range of fields, such as engineering, science and economics.
MATLAB Scientific Plotting and Data Analysis combines the author's extensive experience in data analysis and scientific plotting to provide detailed explanations of the methods and techniques for using MATLAB in creating scientific charts and conducting data analysis. The book is divided into three parts, comprising a total of 12 chapters. The first part mainly covers the basics of MATLAB, including the operating environment, data types and basic operations, file operations, and programming. The second part focuses on MATLAB's data visualization capabilities, providing detailed explanations of topics such as figure window information, 2D plotting, 3D plotting, specialized plotting, and handle graphics objects. The third part covers topics such as descriptive data analysis, interpolation and fitting, regression analysis, and optimization problem solving. The book also provides links to over 200 examples of teaching videos and hands-on exercise resource files to help readers improve their learning efficiency.
Introduction to Python and Spice for Electrical and Computer Engineers introduces freshman and sophomore engineering students to programming in Python and Spice through engaged, problem-based learning and dedicated Electrical and Computer Engineering content. This book draws its problems and examples specifically from Electrical and Computer Engineering, covering such topics as matrix algebra, complex exponentials and plotting using examples drawn from circuit analysis, signal processing, and filter design. It teaches relevant computation techniques in the context of solving common problems in Electrical and Computer Engineering.This book is unique among Python textbooks for its dual focus on introductory-level learning and discipline-specific content in Electrical and Computer Engineering. No other textbook on the market currently targets this audience with the same attention to discipline-specific content and engaged learning practices. Although it is primarily an introduction to programming in Python, the book also has a chapter on circuit simulation using Spice. It also includes materials helpful for ABET-accreditation, such information on professional development, ethics, and lifelong learning.
Management and Engineering of Critical Infrastructures focuses on two important aspects of CIS, management and engineering. The book provides an ontological foundation for the models and methods needed to design a set of systems, networks and assets that are essential for a society's functioning, and for ensuring the security, safety and economy of a nation. Various examples in agriculture, the water supply, public health, transportation, security services, electricity generation, telecommunication, and financial services can be used to substantiate dangers. Disruptions of CIS can have serious cascading consequences that would stop society from functioning properly and result in loss of life.Malicious software (a.k.a., malware), for example, can disrupt the distribution of electricity across a region, which in turn can lead to the forced shutdown of communication, health and financial sectors. Subsequently, proper engineering and management are important to anticipate possible risks and threats and provide resilient CIS. Although the problem of CIS has been broadly acknowledged and discussed, to date, no unifying theory nor systematic design methods, techniques and tools exist for such CIS.
Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases.
Intelligent Edge Computing for Cyber Physical Applications introduces state-of-the-art research methodologies, tools and techniques, challenges, and solutions with further research opportunities in the area of edge-based cyber-physical systems. The book presents a comprehensive review of recent literature and analysis of different techniques for building edge-based CPS. In addition, it describes how edge-based CPS can be built to seamlessly interact with physical machines for optimal performance, covering various aspects of edge computing architectures for dynamic resource provisioning, mobile edge computing, energy saving scenarios, and different security issues. Sections feature practical use cases of edge-computing which will help readers understand the workings of edge-based systems in detail, taking into account the need to present intellectual challenges while appealing to a broad readership, including academic researchers, practicing engineers and managers, and graduate students.
Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT.
Essential MATLAB for Engineers and Scientists, Eighth Edition provides a concise and balanced overview of MATLAB's functionality, covering both fundamentals and applications. The essentials are illustrated throughout, featuring complete coverage of the software's windows and menus. Program design and algorithm development are presented, along with many examples from a wide range of familiar scientific and engineering areas. This edition has been updated to include the latest MATLAB versions through 2021a. This is an ideal book for a first course on MATLAB, but is also ideal for an engineering problem-solving course using MATLAB.
Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering.
The Feature-Driven Method for Structural Optimization details a novel structural optimization method within a CAD framework, integrating structural optimization and feature-based design. The book presents cutting-edge research on advanced structures and introduces the feature-driven structural optimization method by regarding engineering features as basic design primitives. Consequently, it presents a method that allows structural optimization and feature design to be done simultaneously so that feature attributes are preserved throughout the design process. The book illustrates and supports the effectiveness of the method described, showing potential applications through numerical modeling techniques and programming. This volume presents a high-performance optimization method adapted to engineering structures—a novel perspective that will help engineers in the computation, modeling and design of advanced structures.