Introduction to Digital Communications, written especially for upper-level undergraduate courses, explores the basic principles in the analysis and design of digital communication systems, including design objectives, constraints and trade-offs. After portraying the big picture and laying the background material, this book lucidly progresses to a comprehensive and detailed discussion of all critical elements and key functions in digital communications. The second edition has been fully revised, with timely new chapters on wireless enabling systems and encryption, more practical examples, more application-focused real-world end of chapter exercises, and a more crisp and concise approach to the content.
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.
Foundations of Mathematical Modeling and Analysis for Engineering is designed for first-year graduate and advanced undergraduate engineering students. The book explores linear system theory and demonstrates its application in developing analytical solutions to various equations, essential for describing physical systems through mathematical modeling. This foundation is crucial for learning and research in engineering and various scientific fields. It equips students with the mathematical tools needed to solve entire classes of linear algebraic, ordinary-, and partial-differential equations, while also teaching principles for formulating, organizing, and solving linear subsystems, all of which are vital components of both linear and nonlinear mathematical models. This knowledge prepares students for advanced studies in engineering, applied mathematics, and foundational sciences.
Polymer Nanoparticle Technologies for Gene Delivery and Gene Therapy focuses on the concept of polymer nanoparticles applications in gene delivery and gene therapy. Gene therapy is a relatively young branch of medicine that has the potential to relieve and treat numerous illnesses that are resistant to standard treatment. Polymers used to form nanoparticles can be both synthetic and natural polymers. These nanocarriers have been demonstrated for use as a variety of applications: such as drug delivery, imaging, and detection of apoptosis. This book covers many of the cationic polymers have been studied both in vitro and in vivo for gene delivery.
Computational Biomechanics of Human Joints delves deep into each joint, covering the anatomical, mechanical, pathological, and therapeutic aspects. Each chapter is dedicated to a specific joint, providing an in-depth understanding of its anatomical structure, biomechanical mechanisms, associated diseases and pathologies, available treatments, surgical interventions, as well as imaging-based modelling and numerical simulation techniques using the finite element method. By integrating modelling and numerical simulation techniques into the exploration of joint biomechanics, this book offers readers an innovative perspective and a thorough understanding of the possibilities afforded by these technological advances. It also highlights the advantages and limitations of these methods and discusses their potential to improve clinical decision-making, optimize personalized treatments, design medical devices, and enhance understanding of the intricate mechanisms of joints.
Up and Running with AutoCAD 2026: 2D and 3D Drawing, Design and Modeling presents a combination of step-by-step instructions, examples, and insightful explanations. The book emphasizes core concepts and practical application of AutoCAD in engineering, architecture, and design. Equally useful in instructor-led classroom training, self-study, or as a professional reference, the book is written by a long-time AutoCAD professor and instructor with the user in mind.
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.
Deep Learning: From Algorithmic Essence to Industrial Practice introduces the fundamental theories of deep learning, engineering practices, and their deployment and application in the industry. It provides a detailed explanation of classic convolutional neural networks, recurrent neural networks, and transformer networks based on self-attention mechanisms, along with their variants, combining code demonstrations. Additionally, it covers the applications of these models in areas such as image classification, object detection, semantic segmentation, etc. The book also considers the advancements in deep reinforcement learning and generative adversarial networks.
Composite Disturbance Rejection Control (CDRC) for Complex Dynamic Systems introduces a range of innovative composite disturbance rejection control methods, integrating DOB, ADRC, and other advanced control algorithms. These methods are poised to enhance the control performance of diverse practical control systems in the presence of disturbances. Disturbances are pervasive in modern engineering systems, exerting a nonnegligible negative influence on system performance, and conventional control methods like PID exhibit limited efficacy in managing disturbances, while certain advanced control approaches face practical implementation challenges in real-world control systems for a multitude of reasons.
Prediction of the Future Pandemic: Artificial Intelligence and Nanotechnology Approaches provides a comprehensive account of the applications, challenges, and breakthroughs in using AI and nanotechnology for pandemic prediction. The book emphasizes interdisciplinary collaboration among experts and a global perspective on the prediction of future pandemics. Sections provide a comprehensive exploration of cutting-edge methodologies that leverage AI and nanotechnology to predict, analyze, and combat future pandemics. This book aims to bridge the gap between theoretical concepts and practical applications, offering insights into the integration of these advanced technologies for more accurate, timely, and ethical pandemic predictions.