For undergraduate-level courses in Signals and Systems. This comprehensive exploration of signals and systems develops continuous-time and discrete-time concepts/methods in parallel -- highlighting the similarities and differences -- and features introductory treatments of the applications of these basic methods in such areas as filtering, communication, sampling, discrete-time processing of continuous-time signals, and feedback. Relatively self-contained, the text assumes no prior experience with system analysis, convolution, Fourier analysis, or Laplace and z-transforms.

In the century after the Civil War, an economic revolution improved the American standard of living in ways previously unimaginable. Electric lighting, indoor plumbing, home appliances, motor vehicles, air travel, air conditioning, and television transformed households and workplaces. With medical advances, life expectancy between 1870 and 1970 grew from forty-five to seventy-two years. Weaving together a vivid narrative, historical anecdotes, and economic analysis, The Rise and Fall of American Growth provides an in-depth account of this momentous era. But has that era of unprecedented growth come to an end?
Gordon challenges the view that economic growth can or will continue unabated, and he demonstrates that the life-altering scale of innovations between 1870 and 1970 can't be repeated. He contends that the nation's productivity growth, which has already slowed to a crawl, will be further held back by the vexing headwinds of rising inequality, stagnating education, an aging population, and the rising debt of college students and the federal government. Gordon warns that the younger generation may be the first in American history that fails to exceed their parents' standard of living, and that rather than depend on the great advances of the past, we must find new solutions to overcome the challenges facing us.
A critical voice in the debates over economic stagnation, The Rise and Fall of American Growth is at once a tribute to a century of radical change and a harbinger of tougher times to come.

Regular expressions remain a difficult part of the puzzle when learning how to program. Commonly used for sifting through large chunks of text, regexes are incredibly powerful although they may appear daunting to the newcomer. And variations among languages and environments make them even harder to master. Loaded with examples, this introductory guide walks beginners step-by-step through the fundamentals of regular expressions, and helps you decipher complex patterns. * Break down regular expressions into comprehensible parts * Learn common usage patterns through simple, easy-to-follow examples * Discover how finding unique patterns can help you avoid repetitive, hand-editing of text * Use common command-line tools such as grep and sed * Compare how regular expressions are implemented in different languages and environments

Regular expressions are an extremely powerful tool for manipulating text and data. They are now standard features in a wide range of languages and popular tools, including Perl, Python, Ruby, Java, VB.NET and C# (and any language using the .NET Framework), PHP, and MySQL.
If you don't use regular expressions yet, you will discover in this book a whole new world of mastery over your data. If you already use them, you'll appreciate this book's unprecedented detail and breadth of coverage. If you think you know all you need to know about regular expressions, this book is a stunning eye-opener.
As this book shows, a command of regular expressions is an invaluable skill. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Regular expressions can save you time and aggravation. They can be used to craft elegant solutions to a wide range of problems. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them.
Yet despite their wide availability, flexibility, and unparalleled power, regular expressions are frequently underutilized. Yet what is power in the hands of an expert can be fraught with peril for the unwary. Mastering Regular Expressions will help you navigate the minefield to becoming an expert and help you optimize your use of regular expressions.
Mastering Regular Expressions, Third Edition, now includes a full chapter devoted to PHP and its powerful and expressive suite of regular expression functions, in addition to enhanced PHP coverage in the central "core" chapters. Furthermore, this edition has been updated throughout to reflect advances in other languages, including expanded in-depth coverage of Sun's java.util.regex package, which has emerged as the standard Java regex implementation. Topics include:
A comparison of features among different versions of many languages and tools
How the regular expression engine works
Optimization (major savings available here!)
Matching just what you want, but not what you don't want
Sections and chapters on individual languages
Written in the lucid, entertaining tone that makes a complex, dry topic become crystal-clear to programmers, and sprinkled with solutions to complex real-world problems, Mastering Regular Expressions, Third Edition offers a wealth information that you can put to immediate use.
Reviews of this new edition and the second edition:
"There isn't a better (or more useful) book available on regular expressions."
--Zak Greant, Managing Director, eZ Systems
"A real tour-de-force of a book which not only covers the mechanics of regexes in extraordinary detail but also talks about efficiency and the use of regexes in Perl, Java, and .NET...If you use regular expressions as part of your professional work (even if you already have a good book on whatever language you're programming in) I would strongly recommend this book to you."
--Dr. Chris Brown, Linux Format
"The author does an outstanding job leading the reader from regex novice to master. The book is extremely easy to read and chock full of useful and relevant examples...Regular expressions are valuable tools that every developer should have in their toolbox. Mastering Regular Expressions is the definitive guide to the subject, and an outstanding resource that belongs on every programmer's bookshelf. Ten out of Ten Horseshoes."
--Jason Menard, Java Ranch

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Book Description
Widely respected and admired, Philip Fisher is among the most influential investors of all time. His investment philosophies, introduced almost forty years ago, are not only studied and applied by today's financiers and investors, but are also regarded by many as gospel. This book is invaluable reading and has been since it was first published in 1958. The updated paperback retains the investment wisdom of the original edition and includes the perspectives of the author's son Ken Fisher, an investment guru in his own right in an expanded preface and introduction
"I sought out Phil Fisher after reading his Common Stocks and Uncommon Profits...A thorough understanding of the business, obtained by using Phil's techniques...enables one to make intelligent investment commitments."
Warren Buffet
From AudioFile
This program takes a fundamental view of what it takes to be a top-drawer business worthy of your investment dollar. It's based on traditional company variables like capitalization, market position, and labor relations, and some new variables like organizational adaptability and leadership depth and vision. The broad thinking and nuances are so intuitive and clearly drawn that listeners won't even realize how abstract and intelligent this writing is. The impressive piece of work is nicely abridged, and George Guidall is as connected to the material as anyone could be. Still, this is not for the cognitively challenged, nor for overly aggressive investors nor those with money hang-ups. A great resource for understanding why some companies are great and which ones will be. T.W.
Book Dimension
length: (cm)22.2 　　　 　　　　　 　　　　　 width:(cm)18

Most tasks require a person or an automated system to reason--to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: * Collaborative filtering techniques that enable online retailers to recommend products or media * Methods of clustering to detect groups of similar items in a large dataset * Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm * Optimization algorithms that search millions of possible solutions to a problem and choose the best one * Bayesian filtering, used in spam filters for classifying documents based on word types and other features * Using decision trees not only to make predictions, but to model the way decisions are made * Predicting numerical values rather than classifications to build price models * Support vector machines to match people in online dating sites * Non-negative matrix factorization to find the independent features in a dataset * Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

For introductory courses on computer operating systems. Revised to address the latest version of MINIX (MINIX 3), this streamlined, simplified new edition remains the only operating systems text to first explain relevant principles, then demonstrate their applications using a Unix-like operating system as a detailed example. It has been especially designed for high reliability, for use in embedded systems, and for ease of teaching.

Programming Pearls
- Steve McConnell, author,
When programmers list their favorite books, Jon Bentley's collection of programming pearls is commonly included among the classics. Just as natural pearls grow from grains of sand that irritate oysters, programming pearls have grown from real problems that have irritated real programmers. With origins beyond solid engineering, in the realm of insight and creativity, Bentley's pearls offer unique and clever solutions to those nagging problems. Illustrated by programs designed as much for fun as for instruction, the book is filled with lucid and witty descriptions of practical programming techniques and fundamental design principles. It is not at all surprising that
has been so highly valued by programmers at every level of experience.
In this revision, the first in 14 years, Bentley has substantially updated his essays to reflect current programming methods and environments. In addition, there are three new essays on (1) testing, debugging, and timing; (2) set representations; and (3) string problems. All the original programs have been rewritten, and an equal amount of new code has been generated. Implementations of all the programs, in C or C++, are now available on the Web.
What remains the same in this new edition is Bentley's focus on the hard core of programming problems and his delivery of workable solutions to those problems. Whether you are new to Bentley's classic or are revisiting his work for some fresh insight, this book is sure to make your own list of favorites.

Laboratory experiments with human subjects now provide crucial data in most fields of economics. There has been a tremendous upsurge in interest in this relatively new field of economics. This textbook introduces the world of experimental economics. Contributors including Reinhard Selten and Axel Leijonhufvud add to a book that sketches the history of experimental economics before moving on to describe how to set up an economics experiment and to survey selected applications and the latest methods. This user-friendly book demonstrates how students can use the lessons to conduct original research. With their freeflowing, discursive yet precise style, Friedman and Cassar have created a book that will be essential to students of experimental economics across the world. On account of its authoritative content, Economics Lab will also find its way on to the bookshelves of leading researchers in all fields of economics.

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.