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Its primary goal is to make theoretical and paradigmatic ideas accessible to undergraduate students and to bring the fascination of the field across.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911395799319,"sku":null,"price":5397.75,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783030761943.jpg?v=1781269506"},{"product_id":"optimization-in-banach-spaces-9783031126444","title":"Optimization in Banach Spaces","description":"\u003cp\u003eThe book is devoted to the study of constrained minimization  problems on closed and convex sets in Banach spaces with a Frechet differentiable objective function. Such  problems are well studied in a  finite-dimensional space and in an infinite-dimensional Hilbert space. When the space is Hilbert there are many algorithms for solving optimization problems including the gradient projection algorithm which  is one of the most important tools in the optimization theory, nonlinear analysis and their applications. An optimization problem is described by an  objective function  and a set of feasible points. For the gradient projection algorithm each iteration consists of two steps. The first step is a calculation of a gradient of the objective function while in the second one  we calculate a projection on the feasible  set. In each of these two steps there is a computational error. In our recent research we show that the gradient projection algorithm generates a good approximate solution, if all the computational errors are bounded from above by a small positive constant. It should be mentioned that  the properties of a Hilbert space play an important role. When we consider an optimization problem in a general Banach space the situation becomes more difficult and less understood. On the other hand such problems arise in the approximation theory. The book is of interest for mathematicians working in  optimization. It also can be useful in preparation courses for graduate students.  The main feature of the book which appeals specifically to this audience is the study of algorithms for convex and nonconvex minimization problems in a general Banach space. The book is of interest for experts in applications of optimization to the approximation theory. In this book the goal is to obtain a good approximate solution of the constrained optimization problem in a general Banach space under  the presence of computational errors.  It is shown that the algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a small constant. The book consists of four chapters. In the first we discuss several algorithms which are studied in the book and  prove a convergence result for an unconstrained problem which is a prototype of our results for the constrained problem. In Chapter 2 we analyze convex optimization problems. Nonconvex optimization problems  are studied in Chapter 3. In Chapter 4 we study  continuous   algorithms for minimization problems under the presence of computational errors. The algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a small constant. The book consists of four chapters. In the first we discuss several algorithms which are studied in the book and  prove a convergence result for an unconstrained problemwhich is a prototype of our results for the constrained problem. In Chapter 2 we analyze convex optimization problems. Nonconvex optimization problems  are studied in Chapter 3. 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Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers’ ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow,  demonstrating how readers can apply the most up-to-date methods to their own problems. 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Containing up-to-date methods, this book will provide readers with the tools necessary to compute regularized solutions of inverse problems. A variety of practical examples from geophysics are used to motivate the presentation of abstract mathematical ideas, thus assuring an accessible approach. Beginning with four examples of inverse problems, the opening chapter establishes core concepts, such as formalizing these problems as equations in vector spaces and addressing the key issue of ill-posedness. Chapter Two then moves on to the discretization of inverse problems, which is a prerequisite for solving them on computers. Readers will be well-prepared for the final chapters that present regularized solutions of inverse problems in finite-dimensional spaces, with Chapter Three covering linear problems and Chapter Four studying nonlinear problems. Model problems reflecting scenarios of practical interest in the geosciences, such as inverse gravimetry and full waveform inversion, are fully worked out throughout the book. They are used as test cases to illustrate all single steps of solving inverse problems, up to numerical computations. Five appendices include the mathematical foundations needed to fully understand the material. This second edition expands upon the first, particularly regarding its up-to-date treatment of nonlinear problems. Following the author’s approach, readers will understand the relevant theory and methodology needed to pursue more complex applications. 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Interactive processing of data together with interactive visualization is a powerful combination which has in the recent years become possible due to hardware and algorithm advances in. The combination enables the user to perform interactive exploration and filtering of datasets while simultaneously visualizing the results so that insights can be made immediately. This makes it possible to quickly form hypotheses and draw conclusions. Case studies from the geosciences are not as often presented in the scientific visualization and computer graphics community as e.g., studies on medical, biological or chemical data. This book will give researchers in the field of visualization and computer graphics valuable insight into theopen visualization challenges in the geosciences, and how certain problems are currently solved using domain specific processing and visualization techniques. Conversely, readers from the geosciences will gain valuable insight into relevant visualization and interactive processing techniques. Subsurface data has interesting characteristics such as its solid nature, large range of scales and high degree of uncertainty, which makes it challenging to visualize with standard methods. It is also noteworthy that parallel fields of research have taken place in geosciences and in computer graphics, with different terminology when it comes to representing geometry, describing terrains, interpolating data and (example-based) synthesis of data. The domains covered in this book are geology, digital terrains, seismic data, reservoir visualization and CO2 storage. The technologies covered are 3D visualization, visualization of large datasets, 3D modelling, machine learning, virtual reality, seismic interpretation and multidisciplinary collaboration. 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Considerable emphasis is placed on practical issues of computational methods. The last section of each project contains the solutions to all proposed exercises and guides the reader in using the MATLAB scripts. The mathematical framework provides a basic foundation in numerical analysis of partial differential equations and main discretization techniques, such as finite differences, finite elements, spectral methods and wavelets.   The book is primarily intended as a graduate-level textin applied mathematics, but it may also be used by students in engineering or physical sciences. It will also be a useful reference for researchers and practicing engineers.   The second edition builds upon its earlier material (revised and updated) with three all-new chapters intended to reinforce the presentation of mathematical aspects on numerical methods: Fourier approximation, high-order finite difference methods, and basic tools for numerical optimization. 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For several centuries the main scientific challenge concerned the mechanics of planetary dynamics, and the book describes the basic numerical methods of that time.  In turn, at the end of the Second World War scientific computing took a giant step forward with the advent of electronic computers, which greatly accelerated the development of numerical methods. As a result, scientific computing became established as a third scientific method in addition to the two traditional branches: theory and experimentation. The book traces numerical methods’ journey back to their origins and to the people who invented them, while also briefly examining the development of electronic computers over the years. Featuring 163 references and more than 100 figures, many of them portraits or photos of key historical figures, the book provides a unique historical perspective on the general field of scientific computing – making it a valuable resource for all students and professionals interested in the history of numerical analysis and computing, and for a broader readership alike.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911451242775,"sku":null,"price":5397.75,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783319698472.jpg?v=1781270305"},{"product_id":"space-engineering-9783319415086","title":"Space Engineering","description":"\u003cp\u003eThis book presents a selection of advanced case studies that cover a substantial range of issues and real-world challenges and applications in space engineering. Vital mathematical modeling, optimization methodologies and numerical solution aspects of each application case study are presented in detail, with discussions of a range of advanced model development and solution techniques and tools. Space engineering challenges are discussed in the following contexts: •Advanced Space Vehicle Design •Computation of Optimal Low Thrust Transfers •Indirect Optimization of Spacecraft Trajectories •Resource-Constrained Scheduling, •Packing Problems in Space •Design of Complex Interplanetary Trajectories •Satellite Constellation Image Acquisition •Re-entry Test Vehicle Configuration Selection •Collision Risk Assessment on Perturbed Orbits •Optimal Robust Design of Hybrid Rocket Engines •Nonlinear Regression Analysis in Space Engineering •Regression-Based Sensitivity Analysis and Robust Design•Low-Thrust Multi-Revolution Orbit Transfers •Modeling and Optimization of Balance Layout Problems •Pilot-Induced Oscillations Alleviation •Modeling and Optimization of Hybrid Transfers to Near-Earth Objects •Probabilistic Safety Analysis of the Collision Between Space Debris and Satellite •Flatness-based Low-thrust Trajectory Optimization for Spacecraft Proximity Operations The contributing authors are expert researchers and practitioners in either the space engineering and\/or in the applied optimization fields. Researchers and practitioners working in various applied aspects of space engineering will find this book practical and informative. Academics, graduate and post-graduate students in aerospace engineering, applied mathematics, operations research, optimization, and optimal control, will find this book useful.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911896559895,"sku":null,"price":14780.04,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783319415086.jpg?v=1781501521"},{"product_id":"finite-volumes-for-complex-applications-viii-methods-and-theoretical-aspects-9783319573977","title":"Finite Volumes for Complex Applications VIII - Methods and Theoretical Aspects","description":"\u003cp\u003eThis first volume of the proceedings of the 8th conference on \"Finite Volumes for Complex Applications\" (Lille, June 2017) covers various topics including convergence and stability analysis, as well as investigations of these methods from the point of view of compatibility with physical principles. It collects together the focused invited papers comparing advanced numerical methods for Stokes and Navier–Stokes equations on a benchmark, as well as reviewed contributions from internationally leading researchers in the field of analysis of finite volume and related methods, offering a comprehensive overview of the state of the art in the field. The finite volume method in its various forms is a space discretization technique for partial differential equations based on the fundamental physical principle of conservation, and recent decades have brought significant advances in the theoretical understanding of the method. Many finite volume methods preserve further qualitative or asymptotic properties, including maximum principles, dissipativity, monotone decay of free energy, and asymptotic stability. 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The number of hypoxic zones has been increasing at an exponential rate since the 1960s; there are currently more than 600 documented hypoxic zones in the estuarine and coastal waters worldwide. Hypoxia develops as a synergistic product of many physical and biological factors that affect the balance of dissolved oxygen in seawater, including temperature, solar radiation, wind, freshwater discharge, nutrient supply, and the production and decay of organic matter. A number of modeling approaches have been increasingly used in hypoxia research, along with the more traditional observational and experimental studies. Modeling is necessary because of rapidly changing coastal circulation and stratification patterns that affect hypoxia, the large spatial extent over which hypoxia develops, and limitations on our capabilities to directly measure hypoxia over large spatial and temporal scales. This book consists of 15 chapters that are broadly organized around three main topics: (1) Modeling of the physical controls on hypoxia, (2) Modeling of biogeochemical controls and feedbacks, and, (3) Modeling of the ecological effects of hypoxia. 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Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. This clear, friendly, and rigorous exposition discusses the theory behind the nonlinear optimization algorithms for understanding their properties and their convergence, enabling the reader to prove the convergence of his\/her own algorithms. It covers cases and computational performances of the most known modern nonlinear optimization algorithms that solve collections of unconstrained and constrained optimization test problems with different structures, complexities, as well as those with large-scale real applications. The book is addressed to all those interested in developing and using new advanced techniques for solving large-scale unconstrained or constrained complex optimization problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master in mathematical programming will find plenty of recent information and practical approaches for solving real large-scale optimization problems and applications.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911928181015,"sku":null,"price":17479.59,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783031087202.jpg?v=1781502396"},{"product_id":"solid-mechanics-and-its-applications-9783319627526","title":"Solid Mechanics and Its Applications","description":"\u003cp\u003eThis book is based on 40 years of research and teaching in the fields of fracture mechanics and plasticity. 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Using the classification system defined in the EU Framework Programme for Research and Innovation H2020, several of the topics covered belong to the challenge climate action, environment, resource efficiency and raw materials; and some to health, demographic change and wellbeing; while others belong to Europe in a changing world - inclusive, innovative and reflective societies.The 19th European Conference on Mathematics for Industry, ECMI2016, was held in Santiago de Compostela, Spain in June 2016. The proceedings of this conference include the plenary lectures, ECMI awards and special lectures, mini-symposia (including the description of each mini-symposium) and contributed talks.The ECMI conferences are organized by the European Consortium for Mathematics in Industry with the aim of promoting interaction between academy and industry, leading to innovation in both fields and providing unique opportunities to discuss the latest ideas, problems and methodologies, and contributing to the advancement of science and technology. They also encourage industrial sectors to propose challenging problems where mathematicians can provide insights and fresh perspectives. 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