Lang, one of the worlds foremost origami artists and scientists, presents the never-before-described mathematical and geometric principles that allow anyone to design original origami, something once restricted to an elite few. From the theoretical underpinnings to detailed step-by-step folding sequences, this book takes a modern look at the centuries-old art of origami.

    Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations.You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tablesStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet starter code and solutions to help you re-implement and extend original experiments in complexityExplore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topicsExamine case studies of complex systems submitted by students and readers

    This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

    This book provides an introduction to the field of solid state physics for undergraduate students in physics, chemistry, engineering, and materials science.

    Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    Hundreds of thousands of pianos are bought and sold each year, yet most people buy a piano with only the vaguest idea of what to look for as they make this major purchase. The Piano Book evaluates and compares every brand and style of piano sold in the United States. There is information on piano moving and storage, inspecting individual new and used pianos, the special market for Steinways, and sales gimmicks to watch out for. An annual supplement, sold separately, lists current prices for more than 2,500 new piano models.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    You'll progress from a complete beginner regarding Arduino programming and electronics knowledge to intermediate skills and the confidence to create your own amazing Arduino projects. Absolutely no experience in programming or electronics required!Rather than requiring you to wade through pages of theory before you start making things, this book has a hands-on approach. You will dive into making projects right from the start, learning how to use various electronic components and how to program the Arduino to control or communicate with those components.Each project is designed to build upon the knowledge learned in earlier projects and to further your knowledge in programming as well as skills with electronics. By the end of the book you will be able create your own projects confidently and with creativity.Please note: the print version of this title is black & white; the eBook is full color. You can download the color diagrams in the book from http: //www.apress.com/9781430232407

    It provides up to date information on structural properties, the processing of materials and their applications.

    All chapters are supplemented by thought-provoking problems. A useful work for graduate-level students with backgrounds in computer science, operations research, and electrical engineering. "Mathematicians wishing a self-contained introduction need look no further." — American Mathematical Monthly.

    The RTL-SDR is a super cheap software defined radio based on DVB-T TV dongles that can be found for under $20. This book is about tips and tutorials that show you how to get the most out of your RTL-SDR dongle. Some projects described in this book are also compatible with other wideband SDRs like the HackRF, Airspy and SDR Play. What's in the book Learn how to set up your RTL-SDR with various free software defined radio programs such as SDR#, HDSDR, SDR-Radio and more. Learn all the little tricks and oddities that the dongle has. A whole chapter dedicated to improving the RTL-SDR's performance. Dozens of tutorials for fun RTL-SDR based projects such as ADS-B aircraft radar, AIS boat radar, ACARS decoding, receiving NOAA and Meteor-M2 weather satellite images, listening to and following trunked radios, decoding digital voice P25/DMR signals, decoding weather balloon telemetry, receiving DAB radio, analysing GSM and listening to TETRA signals, decoding pagers, receiving various HF signals such as ham radio modes, weatherfax and DRM radio, decoding digital D-STAR voice, an introduction to GNU Radio, decoding RDS, decoding APRS, measuring filters and SWR with low cost equipment, and many many more projects! Guide to antennas, cables and adapters. This book is updated every 3-4 months to ensure information is fresh and up to date. Updates are available for free for all customers. Note: To update the book you must manually contact Kindle support and request the update. Last updated to edition 4.1 on 15 June 2015.

    Information is provided on the fundamental concepts of table and graph design, the numbers and knowledge most suitable for display in a graphic form, the best tabular means to communicate certain ideas, and the component-level aspects of design. Analysts, technicians, and managers will appreciate the solid theory behind this outline for ensuring that tables and graphs present quantitative business information in a truthful, attractive format that facilitates better decision making.

    This second edition is appropriate as a supplementary (companion) text for any college-level course covering digital signal processing.

    This introduction is ideal for beginners: it requires no previous programming experience and all concepts are explained from first principles via carefully chosen examples. Each chapter includes exercises that range from the straightforward to extended projects, plus suggestions for further reading on more advanced topics. The author is a leading Haskell researcher and instructor, well-known for his teaching skills. The presentation is clear and simple, and benefits from having been refined and class-tested over several years. The result is a text that can be used with courses, or for self-learning. Features include freely accessible Powerpoint slides for each chapter, solutions to exercises and examination questions (with solutions) available to instructors, and a downloadable code that's fully compliant with the latest Haskell release.