PRINCETON LECTURES IN ANALYSIS II COMPLEX ANALYSIS (1版)

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【原文書】 書名：Complex Analysis (Princeton Lectures in Analysis, No. 2) 作者：STEIN 出版社：PRINCETON 出版日期：2003/04/07 ISBN：9780691113852

PRINCETON LECTURES IN ANALYSIS I FOURIER ANALYSIS AN INTRODUCTION (1版)

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Fourier Analysis—An Introduction 系列名：Princeton Lectures in Analysis, Volume 1 ISBN13：9780691113845 替代書名：Fourier Analysis 出版社：Princeton Univ Pr 作者：Elias M. Stein; Rami Shakarchi 裝訂：精裝 規格：24.1cm*16.5cm*1.9cm (高/寬/厚) 出版日：2003/03/17 內容簡介 This first volume, a three-part introduction to the subject, is intended for students with a beginning knowledge of mathematical analysis who are motivated to discover the ideas that shape Fourier analysis. It begins with the simple conviction that Fourier arrived at in the early nineteenth century when studying problems in the physical sciences--that an arbitrary function can be written as an infinite sum of the most basic trigonometric functions. The first part implements this idea in terms of notions of convergence and summability of Fourier series, while highlighting applications such as the isoperimetric inequality and equidistribution. The second part deals with the Fourier transform and its applications to classical partial differential equations and the Radon transform; a clear introduction to the subject serves to avoid technical difficulties. The book closes with Fourier theory for finite abelian groups, which is applied to prime numbers in arithmetic progression. In organizing their exposition, the authors have carefully balanced an emphasis on key conceptual insights against the need to provide the technical underpinnings of rigorous analysis. Students of mathematics, physics, engineering and other sciences will find the theory and applications covered in this volume to be of real interest. The Princeton Lectures in Analysis represents a sustained effort to introduce the core areas of mathematical analysis while also illustrating the organic unity between them. Numerous examples and applications throughout its four planned volumes, of which Fourier Analysis is the first, highlight the far-reaching consequences of certain ideas in analysis to other fields of mathematics and a variety of sciences. Stein and Shakarchi move from an introduction addressing Fourier series and integrals to in-depth considerations of complex analysis; measure and integration theory, and Hilbert spaces; and, finally, further topics such as functional analysis, distributions and elements of probability theory.

Princeton Lectures in Analysis III Real Analysis Measure Theory,Integration ,& Hilbert Spaces (1版)

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書名：Real Analysis: Measure Theory, Integration, And Hilbert Spaces 作者：STEIN 出版社：PRINCETON 出版日期：2005/03/14 ISBN：9780691113869

Applied Combinatorics (6版)

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+作者：Tucker +年份：2012 年6 版 +ISBN：9780470458389 +書號：MA0462H +規格：精裝/單色 +頁數：498 +出版商：John Wiley 內容簡介 The new 6th edition of Applied Combinatorics builds on the previous editions with more in depth analysis of computer systems in order to help develop proficiency in basic discrete math problem solving. As one of the most widely used book in combinatorial problems, this edition explains how to reason and model combinatorically while stressing the systematic analysis of different possibilities, exploration of the logical structure of a problem, and ingenuity. Although important uses of combinatorics in computer science, operations research, and finite probability are mentioned, these applications are often used solely for motivation. Numerical examples involving the same concepts use more interesting settings such as poker probabilities or logical games. This book is designed for use by students with a wide range of ability and maturity (sophomores through beginning graduate students). The stronger the students, the harder the exercises that can be assigned. The book can be used for one-quarter, two-quarter, or one-semester course depending on how much material is used. 目錄 Part One: Graph Theory. Chapter 1: Elements of Graph Theory. Chapter 2: Covering Circuits and Graph coloring. Chapter 3: Trees and Searching. Chapter 4: Network Algorithms. Part Two: Enumeration. Chapter 5: General Counting Methods for Arrangements and Selections. Chapter 6: Generating Functions. Chapter 7: Recurrence Relations. Chapter 8: Inclusion-Exclusion. Part Three: Additional Topics. Chapter 9: Polya's Enumeration Formula. Chapter 10: Games with Grapes. POSTLUDE APPENDIX A.1 Set Theory A.2 Mathematical Induction A.3 A Little Probability A.4 The Pigeonhole Principle A.5 Computational Complexity and NP-Completeness GLOSSARY OF COUNTING AND GRAPH THEORY TERMS BIBLIOGRAPHY SOLUTIONS TO ODD-NUMBERED PROBLEMS

STATISTICAL INFERENCE 2/e (2版)

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【原文書】 書名：Statistical Inference 2/E 作者：George Casella 出版社：CENGAGE ISBN：9780534243128 Table of contents 1. Probability Theory. Set Theory. Probability Theory. Conditional Probability and Independence. Random Variables. Distribution Functions. Density and Mass Functions. Exercises. Miscellanea. 2. Transformations and Expectations. Distribution of Functions of a Random Variable. Expected Values. Moments and Moment Generating Functions. Differentiating Under an Integral Sign. Exercises. Miscellanea. 3. Common Families of Distributions. Introductions. Discrete Distributions. Continuous Distributions. Exponential Families. Locations and Scale Families. Inequalities and Identities. Exercises. Miscellanea. 4. Multiple Random Variables. Joint and Marginal Distributions. Conditional Distributions and Independence. Bivariate Transformations. Hierarchical Models and Mixture Distributions. Covariance and Correlation. Multivariate Distributions. Inequalities. Exercises. Miscellanea. 5. Properties of a Random Sample. Basic Concepts of Random Samples. Sums of Random Variables from a Random Sample. Sampling for the Normal Distribution. Order Statistics. Convergence Concepts. Generating a Random Sample. Exercises. Miscellanea. 6. Principles of Data Reduction. Introduction. The Sufficiency Principle. The Likelihood Principle. The Equivariance Principle. Exercises. Miscellanea. 7. Point Estimation. Introduction. Methods of Finding Estimators. Methods of Evaluating Estimators. Exercises. Miscellanea. 8. Hypothesis Testing. Introduction. Methods of Finding Tests. Methods of Evaluating Test. Exercises. Miscellanea. 9. Interval Estimation. Introduction. Methods of Finding Interval Estimators. Methods of Evaluating Interval Estimators. Exercises. Miscellanea. 10. Asymptotic Evaluations. Point Estimation. Robustness. Hypothesis Testing. Interval Estimation. Exercises. Miscellanea. 11. Analysis of Variance and Regression. Introduction. One-way Analysis of Variance. Simple Linear Regression. Exercises. Miscellanea. 12. Regression Models. Introduction. Regression with Errors in Variables. Logistic Regression. Robust Regression. Exercises. Miscellanea. Appendix. Computer Algebra. References.

Geometric Function Theory: Explorations in Complex Analysis 2006 <SV> 0-8176-4339-7

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(特價699)Geometric Function Theory: Explorations in Complex Analysis 2006 <SV> 0-8176-4339-7 KRANTZ 9780817643393

RELATIVITY : THE SPECIAL & THE GENERAL THEORY

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書名：Relativity: The Special & The General Theory 作者：EINSTEIN 出版社：PRINCETON 出版日期：2019/03/12 ISBN：9780691191812

年份較久，上下側及側面及內頁都泛黃，書皮有摺痕，未使用過 Quantum Electrodynamics 2/e Course of Theoretical Physics Vol:4 1982 (BH) 0-7506-3371-9 (2版)

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書名：Quantum Electrodynamics 2/e Course of Theoretical Physics Vol:4 作者：BERESTETSKII 出版社：HB ISBN：9780750633710

Physical Kinetics Course of Theoretical Physics Vol:10 (1版)

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書名：Physical Kinetics Course of Theoretical Physics Vol:10 作者：LIFSHITZ 出版社：HB ISBN：9780750626354

ABSTRACT ALGEBRA (3版)

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【原文書】 書名：ABSTRACT ALGEBRA 3/E 作者：DUMMIT 出版社：JOHN WILEY 出版日期：2003/07/01 ISBN：9780471433347

ELEMENTS OF DISCRETE MATHEMATICS (2版)

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書名：Elements of Discrete Mathematics 2/e 作者：LIU 出版社：McGraw-Hill 出版日期：1985/00/00 ISBN：9780071005449 內容簡介 This book presents a selection of topics from set theory, combinatorics, graph theory, and algebra which were been considered as basic and useful to students in Applied Mathematics, Computer Seience, and Engineering. It's intended to be a textbook for a course in Discrete Mathematics at the sophomore-junior level, although it can also be used in a freshman-level course since the presentation does not assume any background beyond high-school mathematics. 目錄 1. Sets and Propositions 2. Computability and Formal Languages 3. Permutations, Combinations, and Discrete Probability 4. Relations and Functions 5. Graphs and Planar Graphs 6. Trees and Cut-Sets 7. Finite State Machines 8. Analysis of Algorithms 9. Discrete Numberic Functions and Generating Functions 10. Recurrence Relations and Recursive Algorithms 11. Groups and Rings 12. Boolean Algebras