Computational science is fundamentally changing how technological questions are addressed. The design of aircraft, automobiles, and even racing sailboats is now done by computational simulation. The mathematical foundation of this new approach is numerical analysis, which studies algorithms for computing expressions defined with real numbers. Emphasizing the theory behind the computation, this book provides a rigorous and self-contained introduction to numerical analysis and presents the advanced mathematics that underpin industrial software, including complete details that are missing from most textbooks. Using an inquiry-based learning approach, "Numerical Analysis" is written in a narrative style, provides historical background, and includes many of the proofs and technical details in exercises. Students will be able to go beyond an elementary understanding of numerical simulation and develop deep insights into the foundations of the subject. They will no longer have to accept the mathematical gaps that exist in current textbooks. For example, both necessary and sufficient conditions for convergence of basic iterative methods are covered, and proofs are given in full generality, not just based on special cases. The book is accessible to undergraduate mathematics majors as well as computational scientists wanting to learn the foundations of the subject. It presents the mathematical foundations of numerical analysis. It explains the mathematical details behind simulation software. It introduces many advanced concepts in modern analysis. It is self-contained and mathematically rigorous. It contains problems and solutions in each chapter. This is an excellent follow-up course to "Principles of Mathematical Analysis" by Rudin.

This accessible and quick how-to book covers all the basic and practical aspects of EEG interpretation. Arranged in an easy-to-use format, the text covers the value of EEG, practical tips on interpretation, specific areas where EEG is most useful, pitfalls to avoid, how to report on findings, and explanations of the most prominent EEG phenomena. The reader will easily obtain knowledge of EEGs with the clinical pearls provided by experts.

《翻译美学》荣获上海交通大学2004年度学术著作出版基金资助。全书分为主体篇、问美篇、朦胧篇、实践篇四部分，从美学的角度深入探讨翻译实践与方法，理论性强，例句丰富，有代表性，具有较强的翻译实践指导意义；对国内翻译界具有参考借鉴的学术价值。《翻译美学》可用作高等院校英语专业硕士研究生选修课教材。

One of the major challenges in science is to study and understand the human brain. Numerous methods examining different aspects of brain functions have been developed and employed. To study systemic interactions brain networks in vivo, non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been used with great success. However, each of these methods can map only certain, quite selective aspects of brain function while missing others; and the inferences on neuronal processes and information flow are often rather indirect. To overcome these shortcomings of single methods, researchers have attempted to combine methods in order to make optimal use of their advantages while compensating their disadvantages. Hence, it is not surprising that soon after the introduction of fMRI as a neuroimaging method the possibilities of combinations with EEG have been explored. This book is intended to aid researchers who plan to set up a simultaneous EEG-fMRI laboratory and those who are interested in integrating electrophysiological and hemodynamic data. As will be obvious from the different chapters, this is a dynamically developing field in which several approaches are being tested, validated and compared. Currently, there is no one best solution for all problems available, but many promising techniques are emerging. This book shall give a comprehensive overview of these techniques. In addition, it points to open questions and directions for future research.

This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.

The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.

The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Some acclaim for previous editions: "Buy it, study it, enjoy it. It's as timeless as a book can be in our age of volubility." — The New York Times "No book in shorter space, with fewer words, will help any writer more than this persistent little volume." — The Boston Globe "White is one of the best stylists and most lucid minds in this country. What he says and his way of saying it are equally rewarding." — The Wall Street Journal "The book remains a nonpareil: direct, correct, and delightful." — The New Yorker ". . . Should be the daily companion of anyone who writes for a living, and for that matter, anyone who writes at all." — Greensboro (N.C.) Daily News "This excellent book, which should go off to college with every freshman, is recognized as the best book of its kind we have." — St. Paul Dispatch – Pioneer Press "It's hard to imagine an engineer or a manager who doesn't need to express himself in English prose as part of his job. It's also hard to imagine a writer who will not be improved by a liberal application of The Elements of Style." — Telephone Engineer & Management --This text refers to the Paperback edition.

With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process. * Create vectors, handle variables, and perform other basic functions * Input and output data * Tackle data structures such as matrices, lists, factors, and data frames * Work with probability, probability distributions, and random variables * Calculate statistics and confidence intervals, and perform statistical tests * Create a variety of graphic displays * Build statistical models with linear regressions and analysis of variance (ANOVA) * Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language-one practical example at a time." -Jeffrey Ryan, software consultant and R package author

Today, interpreting data is a critical decision-making factor for businesses and organizations. If your job requires you to manage and analyze all kinds of data, turn to "Head First Data Analysis", where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in "Head First Data Analysis" is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to: determine which data sources to use for collecting information; assess data quality and distinguish signal from noise; build basic data models to illuminate patterns, and assimilate new information into the models; cope with ambiguous information; design experiments to test hypotheses and draw conclusions; use segmentation to organize your data within discrete market groups; visualize data distributions to reveal new relationships and persuade others; predict the future with sampling and probability models; clean your data to make it useful; and, communicate the results of your analysis to your audience. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, "Head First Data Analysis" uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

You're not alone. At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on... something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design paddle pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect - a visually-rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

Do you use Excel for simple lists, but get lost when it comes to actually doing something useful with all that data, like functions? Revolutionize the way your use the information in your life! "Head First Excel" helps you move from a spreadsheet dabbler into a savvy user in just a short time. Whether you're completely new to Excel, or an experienced user looking to make the program work better for you, this book will help you incorporate Excel into every aspect of your workflow, from a scratch pad for data-based brainstorming, to exploratory analysis with PivotTables, optimizing outcomes with Goal Seek, and presenting your conclusions with sophisticated data visualizations. Organize and present information clearly in a spreadsheet. Make calculations across a number of worksheets. Change your point of view with sorting, zooming, and filtering. Manipulate numerical and data to extract and use the data you need. Leverage Excel as a grid-based layout program. Get the most out of writing the right formulas for the right functionality. Nest formulas for more complex operations. Create sophisticated data visualizations with charts and graphs. Use Goal Seek to optimize possible outcomes based on different assumptions. Create summaries from large data sets for exploratory data analysis with PivotTables. We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, "Head First Excel" uses a visually rich format designed for the way your brain works, rather than a text-heavy approach that will put you to sleep.

執行工作、擬訂企畫、會議簡報、培育人才、收集資訊、知識開發的最佳利器！ 風行130國，微軟、3M、福特汽車、花旗、可口可樂、HSBC等一流企業採用 由腦力開發權威東尼‧博贊（Tony Buzan）所發明的心智圖，被譽為「思考的瑞士刀」，目前已有超過兩億五千萬人、兩千家知名企業採用，是可激發創意、幫助記憶、提升效率、傳承知識的多元技術。本書鎖定心智圖於職場的應用，以實例詳盡解說繪製步驟，讓你迅速掌握這項可加強績效與競爭力的有效工具。有了心智圖，你的思路將更清晰敏銳，工作也會更得心應手。從今天起，指派工作或承接任務、訂定待辦事務處理程序、撰寫企劃案、規劃會議議題與流程、整理與分享會議紀錄、製作簡報、企業內訓、收集與統整參考資料、彙整人脈資料、知識管理……等重要作業，請使用心智圖！ 何謂心智圖？ 心智圖是以關鍵字繪出放射狀圖樣的工具，有著「協助思考並同時進行圖解」的功能，任何人均能輕鬆上手，而且製作與檢視都能迅速完成。 心智圖的特點 改善思考僵化，激發創意 讓使用者能綜觀全貌，不遺漏任何重點 以圖像呈現，比文字更容易理解 讓經驗（非形式知識）輕易轉化為形式知識 透過顏色、圖像等表現，能強化閱圖者直覺理解的效果 可作為輔助理解事物的圖解技術 能讓閱圖者更容易理解自己的想法 實際在職場中運用心智圖時，必須將重點置於「繪製出能使他人輕易理解的心智圖」。若在心智圖中使用只有自己才看得懂的關鍵字或圖示，便無法使對方充分理。 心智圖的繪製方法 準備一張白紙，並將其橫放於桌上。 在白紙正中央寫上作為主題的字串，並在其周圍畫上與該字串相關的圖像（或圖案）。 由正中央開始向周圍延伸分支，並於各分支線上端，寫上與中央字串或圖像相關的標題。分支線的長應與字串的長度相當。越接近中央的分支線越粗，而越接近末端的分支線則應越細。另外，標題的數目若過多將會導致閱讀上的困難，因此應控制在七項以內。 接著在各標題下方寫上相關的副標題。只須將當下所想到的、足以表現該標題內容的關鍵字寫出即可。 在繪製各標題的分支時，要盡量繪出平順優美的線條。 使用的單字應具備次序性（依照性質排列順序）或邏輯性為佳。 在分支線及單字上塗上顏色。 在分支字串的前後加入記號或圖案（圖像文字）。 想要強調分支線上的字串時，可使用圈選或著色等方式。 想要強調某一區塊的分支線時，可圈選整塊區塊或加上色塊。 ○11檢視整體架構，並於其中加入誇張、幽默等表現方式，藉以創造出豐富多變的特色。 心智圖於工作現場的運用 承接工作 當上司交付工作給自己時，必須正確地理解工作的內容與程序。事實上，這是相當深奧的步驟，菜鳥與經驗豐富的業務員對同一份工作的理解必會有所差異，而部屬的定位也會因上司的認知不同而改變，因此，如何與上司建立良好的溝通與互動管道，通常是許多業務員的煩惱。此時若能善加運用心智圖，便能將腦中紊亂的想法整理成條理分明的內容。 擬定企劃案 企劃負責人運用心智圖工具來進行作業的實例比比皆是。無論是激發創意、構思或撰寫企劃案等階段，心智圖均能派上極大的用場。但實際上，光憑藉心智圖本身所具備的功能，並無法刺激出源源不絕的創意與令人耳目一新的企劃案。這是因為創意並不會憑空出現，而必須藉由腦中長久以來累積的大量資訊與智慧催化方能誕生。本書將告訴大家如何運用心智圖來完成獨一無二的企劃案。 製作會議紀錄 在職場上，最常使用心智圖的場合就是會議，運用心智圖來製作會議紀錄就占有相當大的比例。並非是以手繪方式製作心智圖，而是使用電腦軟體來製作，理由如下： ˙將書面企劃案透過電腦呈現，將可使所有與會者均能看見企劃心智圖的全貌。 ˙與會者的意見將可即時反映於企劃心智圖中。由於參與討論企劃的與會者均能同步看見心智圖的變化，因此將更容易理解該企劃案與所討論的內容。 ˙由於會同步製作會議紀錄，因此在會議結束時紀錄將已接近完成，只須稍作修訂，就可將以心智圖格式呈現的會議紀錄分發給與會者。若與會者不習慣閱讀心智圖，則可利用心智圖軟體將其轉換為Word等文字檔案後再行分發。 ˙會後所分發的心智圖會議紀錄較條列式會議紀錄容易理解，與會者也比較容易回想起會議中所作出的各項決策。 企劃簡報 簡報技術（presentation）是業務員的必備能力。在簡報時，為使與會者均能充分理解，簡報內容必須明確而條理分明，簡潔易懂。說明企劃案之前也要先闡明企劃背景，以吸引聽眾注意，還必須具備足夠的簡報技巧，能善加利用表情、姿勢與聲音與簡報軟體來提升效果。而透過心智圖進行簡報，將可充分達成以上要求。心智圖可使用在擬定企劃案階段與實際執行企劃案階段。 人才培育 過去的職場根深柢固地認為「用眼睛學習！」是不可動搖的準則，使得上個世代的主管不僅鮮少有傳經授道的經驗，部屬也多具有出眾的獨立學習精神。然而，今日的二十與三十世代的年輕職員卻得時常接受內部訓練，也間接使得上司的責任與日俱增。而運用心智圖，能讓人才培育工作更事半功倍。 資料收集 許多人必須長時間地使用電子郵件處理各項事務，想將複雜而不易閱讀的郵件轉成易於理解的內容，以及將郵件內容與其他已化為心智圖的資訊作超連結時，都可以使用心智圖。另外，一般人通常會將所需要的網頁存入「我的最愛」中，但當「我的最愛」中保存的網頁數量太多時，整理起來就會相當費時，網頁也無法與其他網頁相互連結，使用上常會造成不便。而心智圖軟體能在各分支上插入超連結，只要直接將各網頁的網址貼上，即可完成心智圖與各網頁的連結。有些心智圖軟體還具備點選瀏覽器上的選項，即可自動完成URL連結的功能。

职场上，成功的人总是把失败的经验写在笔记本上，然后重新出发；追求成果的人总在积极改变工作习惯，善用笔记本“捕获”升级加薪的机会；注重自我投资的人不会让时间和金钱白白溜走，学以致用只为成就梦想。 本书告诉我们，职场达人和普通人的最大差别在于做工作笔记的方法！奥运会选手有以往成绩可循，才能一再破纪录；金牌销售员妙用笔记本管理客户关系，业绩才能屡创新高；策划经理靠笔记本记录灵感，品牌影响力才能经久不衰…… 作者独创“金三角笔记法”——记事笔记本＋航母笔记本＋行程笔记本。他认为，工作笔记不同于学生时代的课堂笔记，课堂笔记是为了“记忆”，而工作笔记是为了“遗忘”，“烂笔头”式面面俱到的笔记法不再适用，技巧与效率兼备的超级笔记法才是职场达人的必杀技。 你上谷歌搜索，只能找到别人的经验，唯有自己的笔记本，才是专属于你的资历累积。千万不要小看工作笔记，不论成功或失败，全部记下来，你会有意想不到的人生礼物！

你是否常覺得自己生活紊亂、工作毫無頭緒，更別說要對人生有規劃了？ 如果你已經厭倦這樣的自己，請跟著筆記女王的腳步一起來寫手帳吧！ 只是，為什麼要寫手帳呢？ 因為手帳可以幫你自我管理、整頓生活，更重要的是它可以讓你圓夢！ ◆筆記女王的超效率時間管理攻略: 搭配《筆記女王的超效率時間管理攻略》，筆記女王Ada將分享她的時間管理祕訣，公開手帳與圓夢的祕密，給你手帳、更給你使用方法。跟著Ada這樣做，三步驟就能讓夢想實現。 完全披露！筆記女王的生活管理大絕招 ◆十字時間規劃法 ◆便利貼工作管理術 ◆三色筆工作?人生平衡法…