Two and Three Dimensional Calculus

Two-Dimensional and M-Mode Echocardiography for the Small Animal Practitioner provides a concise, accessible manual of basic two-dimensional and m-mode echocardiography. Offers fast access to practical advice on obtaining and evaluating echocardiograms using two-dimensional and m-mode techniques Provides easy reference to the common features of the most common acquired cardiac diseases Designed for ease of use, with concise, bulleted text and 165 images Presents updated generic and normalized reference ranges with a bibliography of breed specific reference articles Includes access to a website with video clips showing techniques and disease features

This book develops concepts and a methodology for a rational description of the organization of three-dimensional flows considering, in particular, the case where the flow is the place of separations. The descriptive analysis based on the critical point theory of Poincar? develops conventional but rather unfamiliar considerations from aerodynamicists, who face the understanding of complex flows including multiple separation lines and vortices. These problems concern industrial sectors where aerodynamics plays a key role, such as aerospace, ground vehicles, buildings, etc. Contents 1. Skin Friction Lines Pattern and Critical Points. 2. Separation Streamsurfaces and Vortex Structures. 3. Separated Flow on a Body. 4. Vortex Wake of Wings and Slender Bodies. 5. Separation Induced by an Obstacle or a Blunt Body. 6. Reconsideration of the Two-Dimensional Separation. 7. Concluding Remarks. About the Authors Jean D?lery is a Supaero (French National Higher School of Aeronautics and Space) engineer who has worked at Onera (French national aerospace research center) since 1964. He has participated in several major French and European aerospace programs, is the author of many scientific publications, and has occupied various teaching positions particularly at Supaero, the University of Versailles-Saint-Quentin, Ecole polytechnique in France and “La Sapienza” University in Rome, Italy. He is currently emeritus adviser at Onera.

Volume 2 of the classic advanced calculus text Richard Courant's Differential and Integral Calculus is considered an essential text for those working toward a career in physics or other applied math. Volume 2 covers the more advanced concepts of analytical geometry and vector analysis, including multivariable functions, multiple integrals, integration over regions, and much more, with extensive appendices featuring additional instruction and author annotations. The included supplement contains formula and theorem lists, examples, and answers to in-text problems for quick reference.

The classic introduction to the fundamentals of calculus Richard Courant's classic text Differential and Integral Calculus is an essential text for those preparing for a career in physics or applied math. Volume 1 introduces the foundational concepts of «function» and «limit», and offers detailed explanations that illustrate the «why» as well as the «how». Comprehensive coverage of the basics of integrals and differentials includes their applications as well as clearly-defined techniques and essential theorems. Multiple appendices provide supplementary explanation and author notes, as well as solutions and hints for all in-text problems.

First course calculus texts have traditionally been either “engineering/science-oriented” with too little rigor, or have thrown students in the deep end with a rigorous analysis text. The How and Why of One Variable Calculus closes this gap in providing a rigorous treatment that takes an original and valuable approach between calculus and analysis. Logically organized and also very clear and user-friendly, it covers 6 main topics; real numbers, sequences, continuity, differentiation, integration, and series. It is primarily concerned with developing an understanding of the tools of calculus. The author presents numerous examples and exercises that illustrate how the techniques of calculus have universal application. The How and Why of One Variable Calculus presents an excellent text for a first course in calculus for students in the mathematical sciences, statistics and analytics, as well as a text for a bridge course between single and multi-variable calculus as well as between single variable calculus and upper level theory courses for math majors.

Mathematical finance requires the use of advanced mathematical techniques drawn from the theory of probability, stochastic processes and stochastic differential equations. These areas are generally introduced and developed at an abstract level, making it problematic when applying these techniques to practical issues in finance. Problems and Solutions in Mathematical Finance Volume I: Stochastic Calculus is the first of a four-volume set of books focusing on problems and solutions in mathematical finance. This volume introduces the reader to the basic stochastic calculus concepts required for the study of this important subject, providing a large number of worked examples which enable the reader to build the necessary foundation for more practical orientated problems in the later volumes. Through this application and by working through the numerous examples, the reader will properly understand and appreciate the fundamentals that underpin mathematical finance. Written mainly for students, industry practitioners and those involved in teaching in this field of study, Stochastic Calculus provides a valuable reference book to complement one’s further understanding of mathematical finance.

Brownian Motion Calculus presents the basics of Stochastic Calculus with a focus on the valuation of financial derivatives. It is intended as an accessible introduction to the technical literature. A clear distinction has been made between the mathematics that is convenient for a first introduction, and the more rigorous underpinnings which are best studied from the selected technical references. The inclusion of fully worked out exercises makes the book attractive for self study. Standard probability theory and ordinary calculus are the prerequisites. Summary slides for revision and teaching can be found on the book website.

Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and challenges in advances in imaging sciences and engineering such as 3D image sensing, 3D holographic imaging, imaging applications for bio-photonics and 3D image recognition. Advanced imaging systems incorporate knowledge from various fields. It is a complex technology that combines physics, optics, signal processing, and image capture techniques. Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field. Integrates the background, introductory material with new advances in 3D imaging and applications. Covers the most recent technologies such as high speed digital holography, compressive sensing, real-time 3D integral imaging, 3D TV, photon counting imaging. To be available as an enhanced ebook with added functionality of colour films showing the effects of advanced 3D applications such as 3D microscopy, 3D biomedical imaging and 3D for security and defense applications. Acts as a single source reference to the rapidly developing field of 3D imaging technology. Provides supplementary material on a companion website including video clips, examples, numerical simulations, and experimental results to show the theoretical concepts. With contributions from leading researchers from across these fields, Multi-dimensional Imaging is a comprehensive reference for the imaging technology research community.

With physical properties that often may not be described by the transposition of physical laws from 3D space across to 2D or even 1D space, low-dimensional solids exhibit a high degree of anisotropy in the spatial distribution of their chemical bonds. This means that they can demonstrate new phenomena such as charge-density waves and can display nanoparticulate (0D), fibrous (1D) and lamellar (2D) morphologies. This text presents some of the most recent research into the synthesis and properties of these solids and covers: Metal Oxide Nanoparticles Inorganic Nanotubes and Nanowires Biomedical Applications of Layered Double Hydroxides Carbon Nanotubes and Related Structures Superconducting Borides Introducing topics such as novel layered superconductors, inorganic-DNA delivery systems and the chemistry and physics of inorganic nanotubes and nanosheets, this book discusses some of the most exciting concepts in this developing field. Additional volumes in the Inorganic Materials Book Series: Molecular Materials Functional Oxides Porous Materials Energy Materials All volumes are sold individually or as comprehensive 5 Volume Set.

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.