Fun and functional Linux, Mac OS X and UNIX shell scripts The UNIX shell is the main scripting environment of every Linux, Mac OS X and UNIX system, whether a rescued laptop or a million-dollar mainframe. This cookbook of useful, customizable, and fun scripts gives you the tools to solve common Linux, Mac OS X and UNIX problems and personalize your computing environment. Among the more than 100 scripts included are an interactive calculator, a spell checker, a disk backup utility, a weather tracker, and a web logfile analysis tool. The book also teaches you how to write your own sophisticated shell scripts by explaining the syntax and techniques used to build each example scripts. Examples are written in Bourne Shell (sh) syntax.

This classic textbook offers a clear exposition of modern probability theory and of the interplay between the properties of metric spaces and probability measures. The first half of the book gives an exposition of real analysis: basic set theory, general topology, measure theory, integration, an introduction to functional analysis in Banach and Hilbert spaces, convex sets and functions and measure on topological spaces. The second half introduces probability based on measure theory, including laws of large numbers, ergodic theorems, the central limit theorem, conditional expectations and martingale's convergence. A chapter on stochastic processes introduces Brownian motion and the Brownian bridge. The edition has been made even more self-contained than before; it now includes a foundation of the real number system and the Stone-Weierstrass theorem on uniform approximation in algebras of functions. Several other sections have been revised and improved, and the comprehensive historical notes have been further amplified. A number of new exercises have been added, together with hints for solution.

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.

This revised and updated fourth edition designed for upper division courses in linear algebra includes the basic results on vector spaces over fields, determinants, the theory of a single linear transformation, and inner product spaces. While it does not presuppose an earlier course, many connections between linear algebra and calculus are worked into the discussion. A special feature is the inclusion of sections devoted to applications of linear algebra, which can either be part of a course, or used for independent study, and new to this edition is a section on analytic methods in matrix theory, with applications to Markov chains in probability theory. Proofs of all the main theorems are included, and are presented on an equal footing with methods for solving numerical problems. Worked examples are integrated into almost every section, to bring out the meaning of the theorems, and illustrate techniques for solving problems. Many numerical exercises make use of all the ideas, and develop computational skills, while exercises of a theoretical nature provide opportunities for students to discover for themselves.

This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The new edition begins with a short chapter on measure theory to orient readers new to the subject.

Advanced Calculus is intended as a text for courses that furnish the backbone of the student's undergraduate education in mathematical analysis. The goal is to rigorously present the fundamental concepts within the context of illuminating examples and stimulating exercises. This book is self-contained and starts with the creation of basic tools using the completeness axiom. The continuity, differentiability, integrability, and power series representation properties of functions of a single variable are established. The next few chapters describe the topological and metric properties of Euclidean space. These are the basis of a rigorous treatment of differential calculus (including the Implicit Function Theorem and Lagrange Multipliers) for mappings between Euclidean spaces and integration for functions of several real variables. Special attention has been paid to the motivation for proofs. Selected topics, such as the Picard Existence Theorem for differential equations, have been included in such a way that selections may be made while preserving a fluid presentation of the essential material. Supplemented with numerous exercises, Advanced Calculus is a perfect book for undergraduate students of analysis.

Between 1900 and the 1970s, twenty million southerners migrated north and west. Weaving together for the first time the histories of these black and white migrants, James Gregory traces their paths and experiences in a comprehensive new study that demonstrates how this regional diaspora reshaped America by "southernizing" communities and transforming important cultural and political institutions. Challenging the image of the migrants as helpless and poor, Gregory shows how both black and white southerners used their new surroundings to become agents of change. Combining personal stories with cultural, political, and demographic analysis, he argues that the migrants helped create both the modern civil rights movement and modern conservatism. They spurred changes in American religion, notably modern evangelical Protestantism, and in popular culture, including the development of blues, jazz, and country music. In a sweeping account that pioneers new understandings of the impact of mass migrations, Gregory recasts the history of twentieth-century America. He demonstrates that the southern diaspora was crucial to transformations in the relationship between American regions, in the politics of race and class, and in the roles of religion, the media, and culture.

Highly useful text studies the logarithmic measures of information and their application to testing statistical hypotheses. Topics include introduction and definition of measures of information, their relationship to Fisher's information measure and sufficiency, fundamental inequalities of information theory, much more. Numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.

Be prepared for your next job interview with this tried-and-true advice In today's tight job market, competition for programming jobs is hotter than ever. This third edition of a popular guide to programming interviews includes new code examples, information on the latest languages, new chapters on sorting and design patterns, tips on using LinkedIn, and a downloadable app to help prepare applicants for the interview. Like its earlier editions, this guide covers what software companies and IT departments want their programmers to know and includes plenty of helpful hints to boost your confidence. Looks at current job search and hiring processes, such as the rise of LinkedIn and other social networks as recruiting resources Addresses the most important languages for a programmer to know and features examples in multiple languages Includes new programming questions designed to sharpen your knowledge Features all-new chapters on design patterns and sorting, including how to deal with memory constraints and mobility issues Walk into your next job interview with confidence, knowing you have thoroughly studied this newest edition of Programming Interviews Exposed .

If you've asked someone the secret to writing efficient, well-written software, the answer that you've probably gotten is "learn assembly language programming." By learning assembly language programming, you learn how the machine really operates and that knowledge will help you write better high-level language code. A dirty little secret assembly language programmers rarely admit to, however, is that what you really need to learn is machine organization, not assembly language programming. Write Great Code Vol I, the first in a series from assembly language expert Randall Hyde, dives right into machine organization without the extra overhead of learning assembly language programming at the same time. And since Write Great Code Vol I concentrates on the machine organization, not assembly language, the reader will learn in greater depth those subjects that are language-independent and of concern to a high level language programmer. Write Great Code Vol I will help programmers make wiser choices with respect to programming statements and data types when writing software, no matter which language they use.

The second volume in the Write Great Code series supplies the critical information that today's computer science students don't often get from college and university courses: How to carefully choose their high-level language statements to produce efficient code. Write Great Code, Volume 2: Thinking Low-Level, Writing High-Level, teaches software engineers how compilers translate high-level language statements and data structures into machine code. Armed with this knowledge, a software engineer can make an informed choice concerning the use of those high-level structures to help the compiler produce far better machine code--all without having to give up the productivity and portability benefits of using a high-level language.

The computing world today is in the middle of a revolution: mobile clients and cloud computing have emerged as the dominant paradigms driving programming and hardware innovation today. The Fifth Edition of Computer Architecture focuses on this dramatic shift, exploring the ways in which software and technology in the cloud are accessed by cell phones, tablets, laptops, and other mobile computing devices. Each chapter includes two real-world examples, one mobile and one datacenter, to illustrate this revolutionary change. Updated to cover the mobile computing revolution Emphasizes the two most important topics in architecture today: memory hierarchy and parallelism in all its forms. Develops common themes throughout each chapter: power, performance, cost, dependability, protection, programming models, and emerging trends ("What's Next") Includes three review appendices in the printed text. Additional reference appendices are available online. Includes updated Case Studies and completely new exercises.

Graph algorithms are critical for a wide range of applications, including network connectivity, circuit design, scheduling, transaction processing, and resource allocation. The latest in Robert Sedgewick's classic series on algorithms, this is the field's definitive guide to graph algorithms for C++. Far more than a "revision," this is a thorough rewriting, five times as long as the previous edition, with a new text design, innovative new figures, more detailed descriptions, and many new exercises -- all designed to dramatically enhance the book's value to developers, students, and researchers alike. The book contains six chapters covering graph properties and types, graph search, directed graphs, minimal spanning trees, shortest paths, and networks -- each with diagrams, sample code, and detailed descriptions intended to help readers understand the basic properties of as broad a range of fundamental graph algorithms as possible. The basic properties of these algorithms are developed from first principles; discussion of advanced mathematical concepts is brief, general, and descriptive, but proofs are rigorous and many open problems are discussed. Sedgewick focuses on practical applications, giving readers all the information and real (not pseudo-) code they need to confidently implement, debug, and use the algorithms he covers. (Also available: Algorithms in C++: Parts 1-4, Third Edition, ISBN: 0-201-35088-2).

The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.

You've learned the basics of Python, but how do you take your skills to the next stage? Even if you know enough to be productive, there are a number of features that can take you to the next level in Python. Pro Python explores concepts and features normally left to experimentation, allowing you to be even more productive and creative. In addition to pure code concerns, Pro Python will develop your programming techniques and approaches, which will help make you a better Python programmer. Not only will this book help your code, it will also help you understand and interact with the many established Python communities, or even start your own. * Take your Python knowledge and coding skills to the next level. * Write clean, innovative code that will be respected among your peers. * Make your code do more with introspection and metaprogramming. * Design complete frameworks and libraries (two are included in the book!). What you'll learn * Write strong Python code that will be respected in the Python community. * Understand the reasons behind big design decisions in Python. * Write programs that can reconfigure themselves in Python. * Disguise your code as different types of objects in Python. * Inspect just about any object in Python. * Prepare your code for international audiences. * Ensure code quality with rigorous testing. Who this book is for This book is for intermediate to advanced Python programmers who are looking to understand how and why Python works the way it does and how they can take their code to the next level. Table of Contents * Principles and Philosophy * Advanced Basics * Functions * Classes * Common Protocols * Object Management * Strings * Documentation * Testing * Distribution * Sheets: A CSV Framework