Calculus And Linear Algebra In Recipes
Download Calculus And Linear Algebra In Recipes full books in PDF, epub, and Kindle. Read online free Calculus And Linear Algebra In Recipes ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Christian Karpfinger |
| Publisher | : Springer Nature |
| Total Pages | : 1015 |
| Release | : 2022-11-08 |
| Genre | : Mathematics |
| ISBN | : 366265458X |
This book provides a clear and easy-to-understand introduction to higher mathematics with numerous examples. The author shows how to solve typical problems in a recipe-like manner and divides the material into short, easily digestible learning units. Have you ever cooked a 3-course meal based on a recipe? That generally works quite well, even if you are not a great cook. What does this have to do with mathematics? Well, you can solve a lot of math problems recipe-wise: Need to solve a Riccati's differential equation or the singular value decomposition of a matrix? Look it up in this book, you'll find a recipe for it here. Recipes are available for problems from the · Calculus in one and more variables, · linear algebra, · Vector Analysis, · Theory on differential equations, ordinary and partial, · Theory of integral transformations, · Function theory. Other features of this book include: · The division of Higher Mathematics into approximately 100 chapters of roughly equal length. Each chapter covers approximately the material of a 90-minute lecture. · Many tasks, the solutions to which can be found in the accompanying workbook. · Many problems in higher mathematics can be solved with computers. We always indicate how it works with MATLAB®. For the present 3rd edition, the book has been completely revised and supplemented by a section on the solution of boundary value problems for ordinary differential equations, by the topic of residue estimates for Taylor expansions and by the characteristic method for partial differential equations of the 1st order, as well as by several additional problems.
| Author | : Stanley I. Grossman |
| Publisher | : Academic Press |
| Total Pages | : 993 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483218031 |
Multivariable Calculus, Linear Algebra, and Differential Equations, Second Edition contains a comprehensive coverage of the study of advanced calculus, linear algebra, and differential equations for sophomore college students. The text includes a large number of examples, exercises, cases, and applications for students to learn calculus well. Also included is the history and development of calculus. The book is divided into five parts. The first part includes multivariable calculus material. The second part is an introduction to linear algebra. The third part of the book combines techniques from calculus and linear algebra and contains discussions of some of the most elegant results in calculus including Taylor's theorem in "n" variables, the multivariable mean value theorem, and the implicit function theorem. The fourth section contains detailed discussions of first-order and linear second-order equations. Also included are optional discussions of electric circuits and vibratory motion. The final section discusses Taylor's theorem, sequences, and series. The book is intended for sophomore college students of advanced calculus.
| Author | : William H. Press |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2002 |
| Genre | : Computers |
| ISBN | : 9788175960961 |
Now the acclaimed Second Edition of Numerical Recipes is available in the C++ object-oriented programming language. Including and updating the full mathematical and explanatory contents of Numerical Recipes in C, this new version incorporates completely new C++ versions of the more than 300 Numerical Recipes routines that are widely recognized as the most accessible and practical basis for scientific computing. The product of a unique collaboration among four leading scientists in academic research and industry, Numerical Recipes is a complete text and reference book on scientific computing. In a self-contained manner it proceeds from mathematical and theoretical considerations to actual practical computer routines. Highlights include linear algebra, interpolation, special functions, random numbers, nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations and inverse theory. The authors approach to C++ preserves the efficient execution that C users expect, while simultaneously employing a clear, object-oriented interface to the routines. Tricks and tips for scientific computing in C++ are liberally included. The routines, in ANSI/ISO C++ source code, can thus be used with almost any existing C++ vector/matrix class library, according to user preference. A simple class library for stand-alone use is also included in the book. Both scientific programmers new to C++, and experienced C++ programmers who need access to the Numerical Recipes routines, can benefit from this important new version of an invaluable, classic text.
| Author | : Marco Aiello |
| Publisher | : Springer Nature |
| Total Pages | : 180 |
| Release | : |
| Genre | : |
| ISBN | : 3031725786 |
| Author | : Richard H. Enns |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 436 |
| Release | : 2007-02-26 |
| Genre | : Mathematics |
| ISBN | : 0387312625 |
* Contains computer algebra worksheets or "recipes" designed using MAPLE (System 10); no prior knowledge of MAPLE is assumed * Effective computational science text for first- and second-year undergraduates in mathematics, physics, engineering, chemistry, economics, biology, and pre-medicine * Examples and problems provide basis for both self-study and on-line course
| Author | : Richard H. Enns |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 273 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 146120013X |
This is a standalone, but the recipes are correlated with topics found in standard texts, and make use of MAPLE (Release 7). As a reference text, or self-study guide this book is useful for science professionals and engineers.; Good for the classroom correlates with topics found in standard classical mechanics texts.; This book makes use of the powerful computer algebra system MAPLE (Release 7) but no prior knowledge of MAPLE is presumed.; The relevant command structures are explained on a need-to-know basis as the recipes are developed, thus making this a standalone text.
| Author | : Sam Morley |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 353 |
| Release | : 2020-07-31 |
| Genre | : Computers |
| ISBN | : 1838986561 |
Discover easy-to-follow solutions and techniques to help you to implement applied mathematical concepts such as probability, calculus, and equations using Python's numeric and scientific libraries Key FeaturesCompute complex mathematical problems using programming logic with the help of step-by-step recipesLearn how to utilize Python's libraries for computation, mathematical modeling, and statisticsDiscover simple yet effective techniques for solving mathematical equations and apply them in real-world statisticsBook Description Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain. The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science. What you will learnGet familiar with basic packages, tools, and libraries in Python for solving mathematical problemsExplore various techniques that will help you to solve computational mathematical problemsUnderstand the core concepts of applied mathematics and how you can apply them in computer scienceDiscover how to choose the most suitable package, tool, or technique to solve a certain problemImplement basic mathematical plotting, change plot styles, and add labels to the plots using MatplotlibGet to grips with probability theory with the Bayesian inference and Markov Chain Monte Carlo (MCMC) methodsWho this book is for This book is for professional programmers and students looking to solve mathematical problems computationally using Python. Advanced mathematics knowledge is not a requirement, but a basic knowledge of mathematics will help you to get the most out of this book. The book assumes familiarity with Python concepts of data structures.
| Author | : A.N. Pressley |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 336 |
| Release | : 2013-11-11 |
| Genre | : Mathematics |
| ISBN | : 1447136969 |
Pressley assumes the reader knows the main results of multivariate calculus and concentrates on the theory of the study of surfaces. Used for courses on surface geometry, it includes intersting and in-depth examples and goes into the subject in great detail and vigour. The book will cover three-dimensional Euclidean space only, and takes the whole book to cover the material and treat it as a subject in its own right.
| Author | : John Stillwell |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 230 |
| Release | : 2008-12-15 |
| Genre | : Mathematics |
| ISBN | : 038778215X |
In this new textbook, acclaimed author John Stillwell presents a lucid introduction to Lie theory suitable for junior and senior level undergraduates. In order to achieve this, he focuses on the so-called "classical groups'' that capture the symmetries of real, complex, and quaternion spaces. These symmetry groups may be represented by matrices, which allows them to be studied by elementary methods from calculus and linear algebra. This naive approach to Lie theory is originally due to von Neumann, and it is now possible to streamline it by using standard results of undergraduate mathematics. To compensate for the limitations of the naive approach, end of chapter discussions introduce important results beyond those proved in the book, as part of an informal sketch of Lie theory and its history. John Stillwell is Professor of Mathematics at the University of San Francisco. He is the author of several highly regarded books published by Springer, including The Four Pillars of Geometry (2005), Elements of Number Theory (2003), Mathematics and Its History (Second Edition, 2002), Numbers and Geometry (1998) and Elements of Algebra (1994).
| Author | : Yves Nievergelt |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 297 |
| Release | : 2013-11-27 |
| Genre | : Mathematics |
| ISBN | : 1461205735 |
This book explains the nature and computation of mathematical wavelets, which provide a framework and methods for the analysis and the synthesis of signals, images, and other arrays of data. The material presented here addresses the au dience of engineers, financiers, scientists, and students looking for explanations of wavelets at the undergraduate level. It requires only a working knowledge or memories of a first course in linear algebra and calculus. The first part of the book answers the following two questions: What are wavelets? Wavelets extend Fourier analysis. How are wavelets computed? Fast transforms compute them. To show the practical significance of wavelets, the book also provides transitions into several applications: analysis (detection of crashes, edges, or other events), compression (reduction of storage), smoothing (attenuation of noise), and syn thesis (reconstruction after compression or other modification). Such applications include one-dimensional signals (sounds or other time-series), two-dimensional arrays (pictures or maps), and three-dimensional data (spatial diffusion). The ap plications demonstrated here do not constitute recipes for real implementations, but aim only at clarifying and strengthening the understanding of the mathematics of wavelets.
