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This popular, world-wide selling textbook teaches engineering mathematics in a step-by-step fashion and uniquely through engineering examples and exercises which apply the techniques right from their introduction. This contextual use of mathematics is highly motivating, as with every topic and each new page students see the importance and relevance of mathematics in engineering. The examples are taken from mechanics, aerodynamics, electronics, engineering, fluid dynamics and other areas. While being general and accessible for all students, they also highlight how mathematics works in any individual's engineering discipline. The material is often praised for its careful pace, and the author pauses to ask questions to keep students reflecting. Proof of mathematical results is kept to a minimum. Instead the book develops learning by investigating results, observing patterns, visualizing graphs and answering questions using technology. This textbook is ideal for first year undergraduates and those on pre-degree courses in Engineering (all disciplines) and Science.
Now in its eighth edition, Engineering Mathematics is an established textbook that has helped thousands of students to succeed in their exams. John Bird's approach is based on worked examples and interactive problems. Mathematical theories are explained in a straightforward manner, being supported by practical engineering examples and applications in order to ensure that readers can relate theory to practice. The extensive and thorough topic coverage makes this an ideal text for a range of Level 2 and 3 engineering courses. This title is supported by a companion website with resources for both students and lecturers, including lists of essential formulae and multiple choice tests.
Discover a simple, direct approach that highlights the basics you need within A FIRST COURSE IN THE FINITE ELEMENT METHOD, 6E. This unique book is written so both undergraduate and graduate students can easily comprehend the content without the usual prerequisites, such as structural analysis. The book is written primarily as a basic learning tool for students, like you, in civil and mechanical engineering who are primarily interested in stress analysis and heat transfer. The text offers ideal preparation for utilizing the finite element method as a tool to solve practical physical problems.
Engineering is mathematics in action. But engineering students do not always see the link between what they learn in mathematics and how this applies to engineering problems.
From relatively simple questions, like determining the maximum weight a beam can support to complex projects like mapping out the most efficient electrical flow for a city’s traffic lights, mathematics is essential.
Essential Mathematics for Chemists is ideally suited for students who have a limited mathematical background and who wish to build their confidence in the use of mathematics that is relevant to their chemistry studies. John Gormally has many years' experience of teaching mathematics to chemistry students and has set out specifically to address common difficulties in understanding the subject. Assuming little knowledge of mathematics, this book first introduces basic skills in handling numbers before covering key topics relevant to chemistry including functions, elementary algebraic manipulation, differential and integral calculus and matrix algebra. The order of the chapters reflects the way in which chemistry courses are often structured and relates to both lecture and laboratory courses. Self-test questions are provided within the text and answers are given at the end of each chapter. Together with the numerous worked examples and sets of graded problems provided, these will help students to acquire relevant skills and gain confidence.
This advanced level engineering mathematics text builds upon the skills that students would have developed in earlier courses. It adheres to the philosophy that students learn by doing, providing a wealth of engineering examples and problems to help students develop their mathematical ability.
This well-known and widely recommended textbook provides an essential basis of mathematical techniques for engineers, physicists, chemists and management scientists at undergraduate level. The material is suitable for the first two years of a typical University or Polytechnic course, and it is developed assuming only an elementary knowledge of pre-University mathematics. The text includes a large number of worked examples, and there is a selection of unworked problems at the end of each chapter.
The tenth edition of this bestselling text includes examples in more detail and more applied exercises; both changes are aimed at making the material more relevant and accessible to readers. Kreyszig introduces engineers and computer scientists to advanced math topics as they relate to practical problems. It goes into the following topics at great depth differential equations, partial differential equations, Fourier analysis, vector analysis, complex analysis, and linear algebra/differential equations.
The brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For more than a century, a diverse array of researchers has been trying to find a language that can be used to capture the essence of what these neurons do and how they communicate - and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it. In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when the abstract world of mathematical modelling collides with the messy details of biology. Each chapter focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain - the individual neuron - through to circuits of interacting neurons, whole brain areas and even the behaviours that brains command. Throughout, Grace examines the history of the field, starting with experiments done on neurons in frog legs at the turn of the twentieth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. She demonstrates the value of describing the machinery of neuroscience using the elegant language of mathematics and reveals in full the remarkable fruits of this endeavour.
Designing engineering components that make optimal use of materials requires consideration of the nonlinear static and dynamic characteristics associated with both manufacturing and working environments. The modeling of these characteristics can only be done through numerical formulation and simulation, which requires an understanding of both the theoretical background and associated computer solution techniques. By presenting both the nonlinear solid mechanics and the associated finite element techniques together, the authors provide, in the first of two books in this series, a complete, clear, and unified treatment of the static aspects of nonlinear solid mechanics. Alongside a range of worked examples and exercises are user instructions, program descriptions, and examples for the FLagSHyP MATLAB computer implementation, for which the source code is available online. While this book is designed to complement postgraduate courses, it is also relevant to those in industry requiring an appreciation of the way their computer simulation programs work.
Famed mathematical scholar's concise exposition of the mathematical basis of tensor analysis, integrated with well-chosen physical examples of the theory, including those involving elasticity, classical dynamics, relativity and Dirac's matrix calculus. Exercises. Index. Bibliography. Notes.
An introduction to Applied Calculus for Social and Life Sciences, the revised edition, contains all the material in the original version and now contains answers to odd numbered exercises. The book additionally contains selected worked out examples available from the publisher's website. The book is designed primarily for students majoring in Social Sciences and Life Sciences. It prepares students to deal with mathematical problems which arise from real-life problems encountered in other areas of study, such as Agriculture, Forestry, Biochemistry, Biology and the Biomedical Sciences. It is also of value to anyone intending to develop foundational undergraduate calculus for the Physical Sciences.
Intractability is a growing concern across the cognitive sciences: while many models of cognition can describe and predict human behavior in the lab, it remains unclear how these models can scale to situations of real-world complexity. Cognition and Intractability is the first book to provide an accessible introduction to computational complexity analysis and its application to questions of intractability in cognitive science. Covering both classical and parameterized complexity analysis, it introduces the mathematical concepts and proof techniques that can be used to test one's intuition of (in)tractability. It also describes how these tools can be applied to cognitive modeling to deal with intractability, and its ramifications, in a systematic way. Aimed at students and researchers in philosophy, cognitive neuroscience, psychology, artificial intelligence, and linguistics who want to build a firm understanding of intractability and its implications in their modeling work, it is an ideal resource for teaching or self-study.
Why study infinite series? Not all mathematical problems can be solved exactly or have a solution that can be expressed in terms of a known function. In such cases, it is common practice to use an infinite series expansion to approximate or represent a solution. This informal introduction for undergraduate students explores the numerous uses of infinite series and sequences in engineering and the physical sciences. The material has been carefully selected to help the reader develop the techniques needed to confidently utilize infinite series. The book begins with infinite series and sequences before moving onto power series, complex infinite series and finally onto Fourier, Legendre, and Fourier-Bessel series. With a focus on practical applications, the book demonstrates that infinite series are more than an academic exercise and helps students to conceptualize the theory with real world examples and to build their skill set in this area.
Contains a compact disc with nearly 200 microcomputer programs illustrating a wide range of reliability and statistical analyses Mechanical Reliability Improvement provides probability and statistical concepts developed using pseudorandom numbers enumeration-, simulation-, and randomization-based statistical analyses for comparison of the test performance of alternative designs, as well as simulation- and randomization-based tests for examination of the credibility of statistical presumptions and discusses centroid and moment of inertia analogies for mean and variance the organization structure of completely randomized, randomized complete block, and split spot experiment test programs
Discrete Mathematics for Computing presents the essential mathematics needed for the study of computing and information systems. The subject is covered in a gentle and informal style, but without compromising the need for correct methodology. It is perfect for students with a limited background in mathematics. This new edition includes: * An expanded section on encryption * Additional examples of the ways in which theory can be applied to problems in computing * Many more exercises covering a range of levels, from the basic to the more advanced This book is ideal for students taking a one-semester introductory course in discrete mathematics - particularly for first year undergraduates studying Computing and Information Systems. PETER GROSSMAN has worked in both academic and industrial roles as a mathematician and computing professional. As a lecturer in mathematics, he was responsible for coordinating and developing mathematics courses for Computing students. He has also applied his skills in areas as diverse as calculator design, irrigation systems and underground mine layouts. He lives and works in Melbourne, Australia.
Developing an approach to the question of existence, uniqueness and stability of solutions, this work presents a systematic elaboration of the theory of inverse problems for all principal types of partial differential equations. It covers up-to-date methods of linear and nonlinear analysis, the theory of differential equations in Banach spaces, applications of functional analysis, and semigroup theory.
Linear Algebra offers a unified treatment of both matrix-oriented and theoretical approaches to the course, which will be useful for classes with a mix of mathematics, physics, engineering, and computer science students. Major topics include singular value decomposition, the spectral theorem, linear systems of equations, vector spaces, linear maps, matrices, eigenvalues and eigenvectors, linear independence, bases, coordinates, dimension, matrix factorizations, inner products, norms, and determinants.
This concise, plain-language guide for senior undergraduates and graduate students aims to develop intuition, practical skills and an understanding of the framework of numerical methods for the physical sciences and engineering. It provides accessible self-contained explanations of mathematical principles, avoiding intimidating formal proofs. Worked examples and targeted exercises enable the student to master the realities of using numerical techniques for common needs such as solution of ordinary and partial differential equations, fitting experimental data, and simulation using particle and Monte Carlo methods. Topics are carefully selected and structured to build understanding, and illustrate key principles such as: accuracy, stability, order of convergence, iterative refinement, and computational effort estimation. Enrichment sections and in-depth footnotes form a springboard to more advanced material and provide additional background. Whether used for self-study, or as the basis of an accelerated introductory class, this compact textbook provides a thorough grounding in computational physics and engineering.
This well-balanced text touches on theoretical and applied aspects of protecting digital data. The reader is provided with the basic theory and is then shown deeper fascinating detail, including the current state of the art. Readers will soon become familiar with methods of protecting digital data while it is transmitted, as well as while the data is being stored. Both basic and advanced error-correcting codes are introduced together with numerous results on their parameters and properties. The authors explain how to apply these codes to symmetric and public key cryptosystems and secret sharing. Interesting approaches based on polynomial systems solving are applied to cryptography and decoding codes. Computer algebra systems are also used to provide an understanding of how objects introduced in the book are constructed, and how their properties can be examined. This book is designed for Masters-level students studying mathematics, computer science, electrical engineering or physics.
The third edition of this highly acclaimed undergraduate textbook is suitable for teaching all the mathematics for an undergraduate course in any of the physical sciences. As well as lucid descriptions of all the topics and many worked examples, it contains over 800 exercises. New stand-alone chapters give a systematic account of the 'special functions' of physical science, cover an extended range of practical applications of complex variables, and give an introduction to quantum operators. Further tabulations, of relevance in statistics and numerical integration, have been added. In this edition, half of the exercises are provided with hints and answers and, in a separate manual available to both students and their teachers, complete worked solutions. The remaining exercises have no hints, answers or worked solutions and can be used for unaided homework; full solutions are available to instructors on a password-protected web site, www.cambridge.org/9780521679718.
Covers multivariable calculus, starting from the basics and leading up to the three theorems of Green, Gauss, and Stokes, but always with an eye on practical applications. Written for a wide spectrum of undergraduate students by an experienced author, this book provides a very practical approach to advanced calculus--starting from the basics and leading up to the theorems of Green, Gauss, and Stokes. It explains, clearly and concisely, partial differentiation, multiple integration, vectors and vector calculus, and provides end-of-chapter exercises along with their solutions to aid the readers' understanding. Written in an approachable style and filled with numerous illustrative examples throughout, Two and Three Dimensional Calculus: with Applications in Science and Engineering assumes no prior knowledge of partial differentiation or vectors and explains difficult concepts with easy to follow examples. Rather than concentrating on mathematical structures, the book describes the development of techniques through their use in science and engineering so that students acquire skills that enable them to be used in a wide variety of practical situations. It also has enough rigor to enable those who wish to investigate the more mathematical generalizations found in most mathematics degrees to do so. Assumes no prior knowledge of partial differentiation, multiple integration or vectors Includes easy-to-follow examples throughout to help explain difficult concepts Features end-of-chapter exercises with solutions to exercises in the book. Two and Three Dimensional Calculus: with Applications in Science and Engineering is an ideal textbook for undergraduate students of engineering and applied sciences as well as those needing to use these methods for real problems in industry and commerce.
For an introductory, one or two semester, or sophomore-junior level course in Probability and Statistics or Applied Statistics for engineering, physical science, and mathematics students. An Applications-Focused Introduction to Probability and Statistics Miller & Freund's Probability and Statistics for Engineers is rich in exercises and examples, and explores both elementary probability and basic statistics, with an emphasis on engineering and science applications. Much of the data has been collected from the author's own consulting experience and from discussions with scientists and engineers about the use of statistics in their fields. In later chapters, the text emphasizes designed experiments, especially two-level factorial design. The Ninth Edition includes several new datasets and examples showing application of statistics in scientific investigations, familiarizing students with the latest methods, and readying them to become real-world engineers and scientists.
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