The Signal And The Noise

UPDATED FOR 2020 WITH A NEW PREFACE BY NATE SILVER "One of the more momentous books of the decade." —The New York Times Book Review Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future. In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball to global pandemics, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science. Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise. With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.

UPDATED FOR 2020 WITH A NEW PREFACE BY NATE SILVER "One of the more momentous books of the decade." —The New York Times Book Review Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future. In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball to global pandemics, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science. Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise. With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.

Mexico City, 1988. Long before iTunes or MP3s, you said "I love you" with a mixtape. Meche, awkward and fifteen, discovers how to cast spells using music, and with her friends Sebastian and Daniela will piece together their broken families, and even find love... Two decades after abandoning the metropolis, Meche returns for her estranged father's funeral, reviving memories from her childhood she thought she buried a long time ago. What really happened back then? Is there any magic left?

A film director is dying of cancer. His greatest film would have told the story of a European village as the last hour of 999 AD approached—bringing Armageddon. Now that story will never be told. But he’s still working it out in his head, making a film that no one will ever see.

Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding, this text provides a clear introduction to the fundamentals of stochastic processes and their practical applications to random signals and noise. With worked examples, problems, and detailed appendices, Introduction to Random Signals and Noise gives the reader the knowledge to design optimum systems for effectively coping with unwanted signals. Key features: Considers a wide range of signals and noise, including analogue, discrete-time and bandpass signals in both time and frequency domains. Analyses the basics of digital signal detection using matched filtering, signal space representation and correlation receiver. Examines optimal filtering methods and their consequences. Presents a detailed discussion of the topic of Poisson processes and shot noise. An excellent resource for professional engineers developing communication systems, semiconductor devices, and audio and video equipment, this book is also ideal for senior undergraduate and graduate students in Electronic and Electrical Engineering.

Jack Potter puts computer cryptography to work for the highest bidder: sometimes for private corporations, sometimes for the government. Sometimes the work is legal; if not, Jack simply raises his price. But one day, Jack discovers something cloaked in the hiss of background radiation streaming past the Earth from deep space: a message from an alien civilization. One that's eager to do business with humanity -- and its representative. Before he knows it, Jack has entered into a partnership that will open a Pandora's Box of potential profit and loss. The governments, the multinationals, and mysterious players more powerful still, all want a piece of the action -- and they're willing to kill, even wage war, to get it. Now Jack is entangled shifting web of deceit and intrigue in which no one, not even his closest friends, can be trusted. For Earth's cloak-and-dagger business practices are writ large in the heavens...and hostile takeovers are just as common across light years as they are across boardroom tables.

DIVExamines the role of media technologies in shaping urban Africa through an ethnographic study of popular culture in northern Nigeria./div

This textbook introduces methods of geoscientific data acquisition using MATLAB in combination with inexpensive data acquisition hardware such as sensors in smartphones, sensors that come with the LEGO MINDSTORMS set, webcams with stereo microphones, and affordable spectral and thermal cameras. The text includes 35 exercises in data acquisition, such as using a smartphone to acquire stereo images of rock specimens from which to calculate point clouds, using visible and near-infrared spectral cameras to classify the minerals in rocks, using thermal cameras to differentiate between different types of surface such as between soil and vegetation, localizing a sound source using travel time differences between pairs of microphones to localize a sound source, quantifying the total harmonic distortion and signal-to-noise ratio of acoustic and elastic signals, acquiring and streaming meteorological data using application programming interfaces, wireless networks, and internet of things platforms, determining the spatial resolution of ultrasonic and optical sensors, and detecting magnetic anomalies using a smartphone magnetometer mounted on a LEGO MINDSTORMS scanner. The book’s electronic supplementary material (available online through Springer Link) contains recipes that include all the MATLAB commands featured in the book, the example data, the LEGO construction plans, photos and videos of the measurement procedures.

Understanding the nature of random signals and noise is critically important for detecting signals and for reducing and minimizing the effects of noise in applications such as communications and control systems. Outlining a variety of techniques and explaining when and how to use them, Random Signals and Noise: A Mathematical Introduction focuses on applications and practical problem solving rather than probability theory. A Firm Foundation Before launching into the particulars of random signals and noise, the author outlines the elements of probability that are used throughout the book and includes an appendix on the relevant aspects of linear algebra. He offers a careful treatment of Lagrange multipliers and the Fourier transform, as well as the basics of stochastic processes, estimation, matched filtering, the Wiener-Khinchin theorem and its applications, the Schottky and Nyquist formulas, and physical sources of noise. Practical Tools for Modern Problems Along with these traditional topics, the book includes a chapter devoted to spread spectrum techniques. It also demonstrates the use of MATLAB® for solving complicated problems in a short amount of time while still building a sound knowledge of the underlying principles. A self-contained primer for solving real problems, Random Signals and Noise presents a complete set of tools and offers guidance on their effective application.

A succinct introduction to the physics and function of magnetic resonance imaging with an emphasis on practical information. This thoroughly revised second edition is clearly structured. The underlying physical principles of the MR experiment are described and the basic pulse sequences commonly used in clinical MRI. It progresses to more advanced techniques such as parallel imaging and cardiovascular MR imaging. An extensive glossary offers rapid access to MRI terminology and will help those seeking to understand this interesting fascinating subject.

Signal & Noise is the epic page-turning story of the laying of the trans-Atlantic cable, and the men and women who are caught in its monumental tide. It is also a novel about the collision of worlds seen and unseen: the present and the future; the living and the dead; the real and the imagined. On a wet London morning in 1857, American engineer Chester Ludlow arrives on the muddy banks of the Isle of Dogs to witness the launch of the largest steamship ever built, the Great Eastern. Also amidst the tumultuous throng is Jack Trace, a lonely bachelor and sketch artist hoping to make his name as an illustrator and journalist in the hurly burly of Fleet Street. Other witnesses include a drunken German by the name of Marx; the child who will christen the massive vessel by the wrong name; and Isambard Kingdom Brunel, the ship's apoplectic and dwarfish architect who will soon die in ignominy. As chief engineer for the Atlantic Cable Company, the charismatic Chester enters the orbit of business and showmanship embodied by J. Beaumol Spude, the bombastic Western beef magnate who will mastermind the funding of the project; Joachim Lindt, creator of the Phantasmagorium, an animated tableaux vivant; and his beautiful wife, the musician Katerina Lindt. Drawn by the demands and adventure of creating the first transoceanic telegraph, Chester leaves behind his fragile wife, Franny, at the family estate of Willing Mind in Maine. Abandoned and still mourning the accidental death of their four-year-old daughter, Franny finds solace in the company of Chester's troubled brother, Otis, who introduces her to the mysteries of the world of spiritualism just as séancing is becoming all the rage in the jittery times leading up to the Civil War. As Chester achieves renown as the glamorous engineer of the trans-Atlantic project, Franny, desperate to contact her dead child, becomes the preeminent spirit conjuror of a war-torn America.

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

A guide to the most relevant issues in contemporary American politics provides nonpartisan coverage of a range of topics from the war in Iraq and climate change to the economy and renewable energy sources.

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.

Isaiah Berlin's classic essay on Tolstoy - an exciting new edition with new criticism and a foreword. 'The fox knows many things, but the hedgehog knows one big thing.' This fragment of Archilochus, which gives this book its title, describes the central thesis of Isaiah Berlin's masterly essay on Tolstoy. There have been various interpretations of Archilochus' fragment; Isaiah Berlin has simply used it, without implying anything about the true meaning of the words, to outline a fundamental distinction that exists in mankind, between those who are fascinated by the infinite variety of things (foxes) and those who relate everything to a central all-embracing system (hedgehogs). When applied to Tolstoy, the image illuminates a paradox of his philosophy of history, and shows why he was frequently misunderstood by his contemporaries and critics. Tolstoy was by nature a fox, but he believed in being a hedgehog.

NATIONAL BESTSELLER ONE OF THE NEW YORK TIMES 10 BEST BOOKS OF THE YEAR Who are the immensely wealthy right-wing ideologues shaping the fate of America today? From the bestselling author of The Dark Side, an electrifying work of investigative journalism that uncovers the agenda of this powerful group. In her new preface, Jane Mayer discusses the results of the most recent election and Donald Trump's victory, and how, despite much discussion to the contrary, this was a huge victory for the billionaires who have been pouring money in the American political system. Why is America living in an age of profound and widening economic inequality? Why have even modest attempts to address climate change been defeated again and again? Why do hedge-fund billionaires pay a far lower tax rate than middle-class workers? In a riveting and indelible feat of reporting, Jane Mayer illuminates the history of an elite cadre of plutocrats—headed by the Kochs, the Scaifes, the Olins, and the Bradleys—who have bankrolled a systematic plan to fundamentally alter the American political system. Mayer traces a byzantine trail of billions of dollars spent by the network, revealing a staggering conglomeration of think tanks, academic institutions, media groups, courthouses, and government allies that have fallen under their sphere of influence. Drawing from hundreds of exclusive interviews, as well as extensive scrutiny of public records, private papers, and court proceedings, Mayer provides vivid portraits of the secretive figures behind the new American oligarchy and a searing look at the carefully concealed agendas steering the nation. Dark Money is an essential book for anyone who cares about the future of American democracy. National Book Critics Circle Award Finalist LA Times Book Prize Finalist PEN/Jean Stein Book Award Finalist Shortlisted for the Lukas Prize

Noise and Vibration Analysis is a complete and practical guide that combines both signal processing and modal analysis theory with their practical application in noise and vibration analysis. It provides an invaluable, integrated guide for practicing engineers as well as a suitable introduction for students new to the topic of noise and vibration. Taking a practical learning approach, Brandt includes exercises that allow the content to be developed in an academic course framework or as supplementary material for private and further study. Addresses the theory and application of signal analysis procedures as they are applied in modern instruments and software for noise and vibration analysis Features numerous line diagrams and illustrations Accompanied by a web site at www.wiley.com/go/brandt with numerous MATLAB tools and examples. Noise and Vibration Analysis provides an excellent resource for researchers and engineers from automotive, aerospace, mechanical, or electronics industries who work with experimental or analytical vibration analysis and/or acoustics. It will also appeal to graduate students enrolled in vibration analysis, experimental structural dynamics, or applied signal analysis courses.

This book presents the first in-depth introduction to parallel imaging techniques and, in particular, to the application of parallel imaging in clinical MRI. It will provide readers with a broader understanding of the fundamental principles of parallel imaging and of the advantages and disadvantages of specific MR protocols in clinical applications in all parts of the body at 1.5 and 3 Tesla.

This revised and expanded second edition brings you to the cutting edge with new chapters on LPI radar design, including over-the-horizon radar, random noise radar, and netted LPI radar. You also discover critical LPI detection techniques, parameter extraction signal processing techniques, and anti-radiation missile design strategies to counter LPI radar.

Teaches the analytical skills necessary to glean value from the warehouses of accumulating data In this age of so-called Big Data, organizations are scrambling to implement new software and hardware to increase the amount of data they collect and store. However, in doing so they are unwittingly making it harder to find the needles of useful information in the rapidly growing mounds of hay. If you don't know how to differentiate signals from noise, adding more noise only makes things worse. When we rely on data for making decisions, how do we tell what qualifies as a signal and what is merely noise? In and of itself, data is neither. Assuming that data is accurate, it is merely a collection of facts. When a fact is true and useful, only then is it a signal. When it's not, it's noise. It's that simple. In "Signal," Stephen Few provides the straightforward, practical instruction in everyday signal detection that has been lacking until now. Using data visualization methods, he teaches how to apply statistics to gain a comprehensive understanding of one's data and adapts the techniques of Statistical Process Control in new ways to detect not just changes in the metrics but also changes in the patterns that characterize data.