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A First Course in Numerical Methods
Offers students a practical knowledge of modern techniques in scientific computing.
An Introduction to Compressed Sensing
Compressed sensing is a relatively recent area of research that refers to the recovery of high-dimensional but low-complexity objects from a limited number of measurements. The topic has applications to signal/image processing and computer algorithms, and it draws from a variety of mathematical techniques such as graph theory, probability theory, linear algebra, and optimization. The author presents significant concepts never before discussed as well as new advances in the theory, providing an in-depth initiation to the field of compressed sensing. An Introduction to Compressed Sensing contains substantial material on graph theory and the design of binary measurement matrices, which is missi...
Design Engineering Refocused
The contents of the book will highlight the differences between the design and engineering disciplines – strengths and flaws. It will also illustrate examples of interdisciplinary interactions. Any false dichotomies will be revealed and the many non-linear processes borne out of challenging conventions between traditional and new modes of practice will be revealed. Projects based on a body of experience spanning many years will be selected to support experimentation that goes beyond an undisciplined search for originality, innovation and creativity. In addition to writings from Hanif Kara and Daniel Bosia contributions will be sought from specialists in the field who have played a role in ...
Applications
An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.
Mastering Frequency Domain Techniques for the Stability Analysis of LTI Time Delay Systems
In many dynamical systems, time delays arise because of the time it takes to measure system states, perceive and evaluate events, formulate decisions, and act on those decisions. The presence of delays may lead to undesirable outcomes; without an engineered design, the dynamics may underperform, oscillate, and even become unstable. How to study the stability of dynamical systems influenced by time delays is a fundamental question. Related issues include how much time delay the system can withstand without becoming unstable and how to change system parameters to render improved dynamic characteristics, utilize or tune the delay itself to improve dynamical behavior, and assess the stability an...
Context
Demonstrates how a building's setting should inform and inspire rather than constrain architectural design Context-Architecture and the Genius of Place is a highly engaging, informative discussion of context in architectural theory and practice. Eric Parry, one of the UK's most highly regarded architects — whose work has been widely lauded for its innovative response to its setting — addresses the contemporary definition of context and its importance for sustainable everyday living and urban design. Looking beyond the formal agenda to explore the fundamentals that give new social and cultural perspective to this vital point of departure for designers, this book turns the urban statistici...
Virtual You
The visionary science behind the digital human twins that will enhance our health and our future Virtual You is a panoramic account of efforts by scientists around the world to build digital twins of human beings, from cells and tissues to organs and whole bodies. These virtual copies will usher in a new era of personalized medicine, one in which your digital twin can help predict your risk of disease, participate in virtual drug trials, shed light on the diet and lifestyle changes that are best for you, and help identify therapies to enhance your well-being and extend your lifespan—but thorny challenges remain. In this deeply illuminating book, Peter Coveney and Roger Highfield reveal wha...
Interpolatory Methods for Model Reduction
Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Int...
Basics and Trends in Sensitivity Analysis: Theory and Practice in R
This book provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. The authors use a practical point of view and real case studies as well as numerous examples, and applications of the different approaches are illustrated throughout using R code to explain their usage and usefulness in practice. Basics and Trends in Sensitivity Analysis: Theory and Practice in R covers a lot of material, including theoretical aspects of Sobol’ indices as well as sampling-based formulas, spectral methods, and metamodel-based approaches for estimation purposes; screening techniques devoted to identifying influential and noninfl...
Uncertainty Quantification
Uncertainty quantification serves a fundamental role when establishing the predictive capabilities of simulation models. This book provides a comprehensive and unified treatment of the mathematical, statistical, and computational theory and methods employed to quantify uncertainties associated with models from a wide range of applications. Expanded and reorganized, the second edition includes advances in the field and provides a comprehensive sensitivity analysis and uncertainty quantification framework for models from science and engineering. It contains new chapters on random field representations, observation models, parameter identifiability and influence, active subspace analysis, and s...
