Think DSP

Digital Signal Processing in Python

Author: Allen B. Downey

Publisher: "O'Reilly Media, Inc."

ISBN: 1491938528

Category: Computers

Page: 168

View: 2575

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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.
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Game Audio Programming 2

Principles and Practices

Author: Guy Somberg

Publisher: CRC Press

ISBN: 1351653946

Category: Computers

Page: 362

View: 5471

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Welcome to the second volume of Game Audio Programming: Principles and Practices – the first series of its kind dedicated to the art of game audio programming! This volume features more than 20 chapters containing advanced techniques from some of the top game audio programmers and sound designers in the industry. This book continues the tradition of collecting more knowledge and wisdom about game audio programming than any other volume in history. Both audio programming beginners and seasoned veterans will find content in this book that is valuable, with topics ranging from extreme low-level mixing to high-level game integration. Each chapter contains techniques that were used in games that have shipped, and there is a plethora of code samples and diagrams. There are chapters on threading, DSP implementation, advanced middleware techniques in FMOD Studio and Audiokinetic Wwise, ambiences, mixing, music, and more. This book has something for everyone who is programming audio for a game: programmers new to the art of audio programming, experienced audio programmers, and those souls who just got assigned the audio code. This book is for you!
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Precision Medicine and the Reinvention of Human Disease

Author: Jules J. Berman

Publisher: Academic Press

ISBN: 0128143940

Category: Business & Economics

Page: 398

View: 313

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Despite what you may have read in the popular press and in social media, Precision Medicine is not devoted to finding unique treatments for individuals, based on analyzing their DNA. To the contrary, the goal of Precision Medicine is to find general treatments that are highly effective for large numbers of individuals who fall into precisely diagnosed groups. We now know that every disease develops over time, through a sequence of defined biological steps, and that these steps may differ among individuals, based on genetic and environmental conditions. We are currently developing rational therapies and preventive measures, based on our precise understanding of the steps leading to the clinical expression of diseases. Precision Medicine and the Reinvention of Human Disease explains the scientific breakthroughs that have changed the way that we understand diseases, and reveals how medical scientists are using this new knowledge to launch a medical revolution. Clarifies the foundational concepts of Precision Medicine, distinguishing this field from its predecessors such as genomics, pharmacogenetics, and personalized medicine. Gathers the chief conceptual advances in the fields of genetics, pathology, and bioinformatics, and synthesizes a coherent narrative for the field of Precision Medicine. Delivers its message in plain language, and in a relaxed, conversational writing style, making it easy to understand the complex subject matter. Guides the reader through a coherent and logical narrative, gradually providing expertise and skills along the way. Covers the importance of data sharing in Precision Medicine, and the many data-related challenges that confront this fragile new field.
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Data Simplification

Taming Information With Open Source Tools

Author: Jules J. Berman

Publisher: Morgan Kaufmann

ISBN: 0128038543

Category: Computers

Page: 398

View: 2845

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Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data. Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user. Discusses data simplification principles, methods, and tools that must be studied and mastered Provides open source tools, free utilities, and snippets of code that can be reused and repurposed to simplify data Explains how to best utilize indexes to search, retrieve, and analyze textual data Shows the data scientist how to apply ontologies, classifications, classes, properties, and instances to data using tried and true methods
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