It is the definitive reference guide, now in a second edition. Although the first edition was written in 1978, it continues to be a worldwide best-seller. This second edition brings the classic original up to date to include the ANSI standard. From the Preface: We have tried to retain the brevity of the first edition. C is not a big language, and it is not well served by a big book. We have improved the exposition of critical features, such as pointers, that are central to C programming. We have refined the original examples, and have added new examples in several chapters. For instance, the treatment of complicated declarations is augmented by programs that convert declarations into words and vice versa. As before, all examples have been tested directly from the text, which is in machine-readable form. As we said in the first preface to the first edition, C "wears well as one's experience with it grows." With a decade more experience, we still feel that way. We hope that this book will help you to learn C and use it well.

    It uses examples and exercise sets, with clear explanations of problem-solving techniqes and material on the further theory of functions.

    One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

    In each new edition, the authors have refined their primary goal of helping you develop the skills and confidence you need to master the art of solving fluid mechanics problems. This new Fifth Edition includes many new problems, revised and updated examples, new Fluids in the News case study examples, new introductory material about computational fluid dynamics (CFD), and the availability of FlowLab for solving simple CFD problems. Access special resources online New copies of this text include access to resources on the book's website, including: * 80 short Fluids Mechanics Phenomena videos, which illustrate various aspects of real-world fluid mechanics.* Review Problems for additional practice, with answers so you can check your work.* 30 extended laboratory problems that involve actual experimental data for simple experiments. The data for these problems is provided in Excel format.* Computational Fluid Dynamics problems to be solved with FlowLab software. Student Solution Manual and Study Guide A Student Solution Manual and Study Guide is available for purchase, including essential points of the text, "Cautions" to alert you to common mistakes, 109 additional example problems with solutions, and complete solutions for the Review Problems.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    The main objective of this book is to present circuit analysis in a clear, easy-to-understand manner, with many practical applications to interest the student. Each chapter opens with either historical sketches or career information on a subdiscipline of electrical engineering. This is followed by an introduction that includes chapter objectives. Each chapter closes with a summary of the key points and formulas. The authors present principles in an appealing and lucid step-by-step manner, carefully explaining each step. Important formulas are highlighted to help students sort out what is essential and what is not. Many pedagogical aids reinforce the concepts learned in the text so that students get comfortable with the various methods of analysis presented in the text.

    Extensively illustrated and user-friendly, the text offers examples pf how knowledge of biochemistry is essential for understanding the molecular basis of health and disease. The 26th edition also features expanded content on results of the Human Genome Project. Perfect as both text and USMLE review.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks.The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

     This top-selling, theorem-proof text presents a careful treatment of the principal topics of linear algebra, and illustrates the power of the subject through a variety of applications. It emphasizes the symbiotic relationship between linear transformations and matrices, but states theorems in the more general infinite-dimensional case where appropriate.

    The most up-to-date and beautifully illustrated text on the market, it has a strong molecular and cellular approach, firmly relating the molecular and cellular biological underpinnings of physiology to the study of human physiology and disease. Contributions from leading physiologists ensure authoritative, cutting-edge information, and thorough and consistent editing have produced a readable and student-friendly text.The smart way to study!Elsevier titles with STUDENT CONSULT will help you master difficult concepts and study more efficiently in print and online! Perform rapid searches. Integrate bonus content from other disciplines. Download text to your handheld device. And a lot more. Each STUDENT CONSULT title comes with full text online, a unique image library, case studies, USMLE style questions, and online note-taking to enhance your learning experience.

    Linear Equations; Vector Spaces; Linear Transformations; Polynomials; Determinants; Elementary canonical Forms; Rational and Jordan Forms; Inner Product Spaces; Operators on Inner Product Spaces; Bilinear Forms For all readers interested in linear algebra.

    The text is written in straightforward language and is complemented by extensive clear, full-colour illustrations. Each chapter provides an explanation of the normal structure and functions of the human body and what occurs when disease or illness disrupts the normal processes.Carefully refined, clear and unambiguous textExcellent layout ensures the text and relevant illustrations are close togetherHighly illustrated with clear line diagrams, mostly in colourText uses regular sequences of headings, lists, and bullet points to help with learning and revisionOmits the unnecessary detail which can confuse the student new to the subjectA glossary of common prefixes, suffixes and roots commonly used in anatomy and physiologyAn Appendix containing useful biological values for easy referenceLearning outcomes related to the sections within each chapterAccompanying Colouring and workbook that facilitates structured learning and revision of the material in this bookAccess to an Evolve companion website offering animations, MCQs, a full image bank, an audio pronunciation guide as well as useful web links.- text revised and updated, including one chapter integrating the musculoskeletal system and a new chapter on genetics to reflect the increasing importance of this topic - new and revised artwork/illustrations - enhanced features on the Evolve website for students: -High quality animations -Multiple-choice questions -Web links to supplementary websites -An audio pronunciation guideand for Lecturers: -Image bank: the complete collection of images from the book.

    The exposition is simple and leads to the most complete direct means of solving problems in mechanics. The final sections on adiabatic invariants have been revised and augmented. In addition a short biography of L D Landau has been inserted.