本书传主匈牙利数学家埃尔德什是当代罕见的数学奇才。他在60多年的数学生涯中，与合作者们共同发表了1475篇高水平的学术论文。
本书以情趣盎然的笔调，穿插数学史上的种种趣闻轶事，刻画出一幅栩栩如生的埃尔德什“肖像画”，同时也向读者展现了一代又一代数学家不屈不挠地迎战诸如“费马大定理”、“四色问题”这样的难题，直至取得辉煌胜利的动人故事。

In this text, the author constructs the mathematical apparatus of classical mechanics from the beginning, examining all the basic problems in dynamics, including the theory of oscillations, the theory of rigid body motion, and the Hamiltonian formalism. This modern approch, based on the theory of the geometry of manifolds, distinguishes iteself from the traditional approach of standard textbooks. Geometrical considerations are emphasized throughout and include phase spaces and flows, vector fields, and Lie groups. The work includes a detailed discussion of qualitative methods of the theory of dynamical systems and of asymptotic methods like perturbation techniques, averaging, and adiabatic invariance.

《布朗运动和随机计算(第2版)》是Springer《数学研究生丛书》之113卷，是国内外公认的金融数学经典教材，各章有习题详解。

图论起源于著名的哥尼斯堡七桥问题，在计算科学、社会科学和自然科学等各个领域都有广泛应用。本书是本科生或研究生一学期或两学期的图论课程教材。内容全面，证明与应用实例并举，不仅包括对证明技巧的讨论、1200多道习题、400多幅插图以及许多例题，而且对所有定理都给出了详细完整的证明。可以作为高等院校数学系本科生和研究生、计算机专业和其他专业研究生的图论课程教材，也可以作为有关教师和工程技术人员的参考书。
本书全面介绍了图论的基本概念、基本定理和算法，帮助读者理解并掌握图的结构和解决图论问题的技巧。另外，书中包含很多图论的新研究成果，并介绍了一些悬而未决的图论问题，证明与应用并举是本书的一个重要特点，书中对所有定理和命题给出了完整的证明，同时讨论了大量的实例和应用，并提供了120O多道习题。
本书可以作为高等院校数学系本科生和研究生、计算机专业和其他专业研究生的图论课程教材，也可以作为有关教师和工程技术人员的参考书。

《计算机代数系统的数学原理》主要介绍了计算机代数系统的数学理论、经典结果和著名算法。全书包含高精度运算、数论、数学常数、精确线性代数、多项式、方程求解、符号极限、符号求和、符号积分、微分方程符号解等10个部分，涵盖了构建计算机代数系统的最基础也是最重要的内容。书中的许多内容是第一次被系统地整理后出现在中文文献中，并在一些领域体现了本方向的最新进展。

A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.

《有限群的线性表示》是著名法国数学家、菲尔兹奖获得者JeanPierreserre的经典著作。全书分三部分。第一部分讲述有限群的线性表示的最基本的内容，主要是群表示和特征标的对应关系；第二部分对群的常表示做了进一步的阐述，如诱导表示、有理性问题等；第三部分简单讨论了群的模表示理论。《有限群的线性表示》深入浅出，对内容的处理极有特色，是学习有限群的线性表示的经典书籍。
《有限群的线性表示》根据原书第二版的英译本翻译，并根据法文修订第三版作了校订。

This book consists of three parts, rather different in level and purpose. The first part was originally written for quantum chemists. It describes the correspondence, due to Frobenius, between linear representations and characters. The second part is a course given in 1966 to second-year students of l'Ecole Normale. It completes in a certain sense the first part. The third part is an introduction to Brauer Theory.

《代数数论》系统、全面地介绍了该领域的经典理论，并对今后的研究方向作了介绍，书中包含了大量的例子，帮助读者理解。这次科学出版社购买了版权,一次影印了23本施普林格出版社出版的数学书,就是一件好事,也是值得继续做下去的事情。大体上分一下,这28本书中,包括基础数学书5本,应用数学书6本与计算数学书12本,其中有些书也具有交叉性质。这些书都是很新的,2000年以后出版的占绝大部分,共计16本,其余的也是1990年以后出版的。这些书可以使读者较快地了解数学某方面的前沿,例如基础数学中的数论、代数与拓扑三本,都是由该领域大数学家编著的“数学百科全书”的分册。对从事这方面研究的数学家了解该领域的前沿与全貌很有帮助。按照学科的特点,基础数学类的书以“经典”为主,应用和计算数学类的书“前沿”为主。这些书的作者多数是国际知名的大数学家,例如《拓扑学》一书的作者诺维科夫是俄罗斯科学院的院士,曾获“菲尔兹奖”和“沃尔夫数学奖”。这些大数学家的著作无疑将会对我国的科研人员起到非常好的指导作用。
当然,23本书只能涵盖数学的一部分,所以,这项工作还应该继续做下去。更进一步,有些读者面较广的好书还应该翻译成中文出版,使之有更大的读者群。

本书的诞生还是半个世纪之前的事情，但是，深贯其中的严谨的学术风范以及针对不同时代所做出的切实改进使得它愈久弥新，成为复分析领域历经考验的一本经典教材。本书作者在数学分析领域声乐卓著，多次荣获国际大次，这也是本书始终保持旺盛的生命力的原因之一。本书适合用做数学专业本科高年级学生及研究生教材。

《高等代数:定理•问题•方法》简介：高等代数与数学分析并称为最重要的数学基础课程，多年来为教育界所公认。学生从高等代数课程中所获得的知识与方法训练，在其后的数学学习与研究中有不可替代的作用。《高等代数:定理•问题•方法》通过800道例题分析，透彻地阐释并系统运用了读者在学习过程中所感觉到的优美的思想与方法，务求读者能真正透彻地弄清一些问题。《高等代数:定理•问题•方法》共分四章，分别为多项式、矩阵与向量、特征值与标准形、内积空间与二次型，每小节以概念与定理、问题与方法的模式进行阐述。

Gilbert Strang's textbooks have changed the entire approach to learning linear algebra -- away from abstract vector spaces to specific examples of the four fundamental subspaces: the column space and nullspace of A and A'.
Introduction to Linear Algebra, Fourth Edition includes challenge problems to complement the review problems that have been highly praised in previous editions. The basic course is followed by seven applications: differential equations, engineering, graph theory, statistics, fourier methods and the FFT, linear programming, and computer graphics.
Thousands of teachers in colleges and universities and now high schools are using this book, which truly explains this crucial subject.
Chapter 1: Introduction to Vectors; Chapter 2: Solving Linear Equations; Chapter 3: Vector Spaces and Subspaces; Chapter 4: Orthogonality; Chapter 5: Determinants; Chapter 6: Eigenvalues and Eigenvectors; Chapter 7: Linear Transformations; Chapter 8: Applications; Chapter 9: Numerical Linear Algebra; Chapter 10: Complex Vectors and Matrices; Solutions to Selected Exercises; Final Exam. Matrix Factorizations. Conceptual Questions for Review. Glossary: A Dictionary for Linear Algebra Index Teaching Codes Linear Algebra in a Nutshell.

Proofs without words are generally pictures or diagrams that help the reader see why a particular mathematical statement may be true, and how one could begin to go about proving it. While in some proofs without words an equation or two may appear to help guide that process, the emphasis is clearly on providing visual clues to stimulate mathematical thought. The proofs in this collection are arranged by topic into five chapters: Geometry and algebra; Trigonometry, calculus and analytic geometry; Inequalities; Integer sums; and Sequences and series. Teachers will find that many of the proofs in this collection are well suited for classroom discussion and for helping students to think visually in mathematics.

银行存款利息、向日葵种子的分布以及圣路易斯大拱门的外形，因为神秘的数字e而有了千丝万缕的联系。e的背后隐藏着无数鲜为人知的传奇，牛顿与莱布尼茨到底谁才是微积分的¬¬发明者？二人的宿怨在科学界引起了怎样的轩然大波？伯努利家族缘何在科学领域称霸了一百多年？数学家约翰伯努利与音乐家巴赫这两位貌似毫无交集的人物会面时是什么情景？听Maor讲述e的故事，一一解开你心中的谜团。
这里包罗万象，既描绘了数学、物理、生物、音乐、金融等众多领域中与e密切相关的现象，也展示了关于e的著名公式、定理和法则。这些趣味横生的历史故事和缜密严谨的数学论断交织在一起，让你从全新的角度去审视这一熟悉又陌生的常数，更让人于走马观花之间了解几千年来数学发展的一个侧影。

Beginning graduate students in mathematics and other quantitative subjects are expected to have a daunting breadth of mathematical knowledge. But few have such a background. This 2002 book will help students to see the broad outline of mathematics and to fill in the gaps in their knowledge. The author explains the basic points and a few key results of all the most important undergraduate topics in mathematics, emphasizing the intuitions behind the subject. The topics include linear algebra, vector calculus, differential geometry, real analysis, point-set topology, probability, complex analysis, abstract algebra, and more. An annotated bibliography then offers a guide to further reading and to more rigorous foundations. This book will be an essential resource for advanced undergraduate and beginning graduate students in mathematics, the physical sciences, engineering, computer science, statistics, and economics who need to quickly learn some serious mathematics.

This well-accepted introduction to computational geometry is a textbook for high-level undergraduate and low-level graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In this third edition, besides revisions to the second edition, new sections discussing Voronoi diagrams of line segments, farthest-point Voronoi diagrams, and realistic input models have been added.

The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary.