Python for Signal Processing: Featuring IPython Notebooks

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future.  For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

 

1116974737
Python for Signal Processing: Featuring IPython Notebooks

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future.  For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

 

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Python for Signal Processing: Featuring IPython Notebooks

Python for Signal Processing: Featuring IPython Notebooks

by Josï Unpingco
Python for Signal Processing: Featuring IPython Notebooks

Python for Signal Processing: Featuring IPython Notebooks

by Josï Unpingco

eBook2014 (2014)

$99.00 

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Overview

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future.  For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

 


Product Details

ISBN-13: 9783319013428
Publisher: Springer-Verlag New York, LLC
Publication date: 10/04/2013
Sold by: Barnes & Noble
Format: eBook
Pages: 128
File size: 2 MB

About the Author

Dr. José Unpingco is an onsite technical director for large-scale signal and image processing for the (USA) Department of Defense (DoD). He is also the lead scientific Python instructor for DoD labs nationwide.  He has worked in industry as an engineer, analyst, consultant, and instructor for his entire career, with deep experience in a wide array of signal and data processing technologies. 

Table of Contents

Introduction.- Sampling Theorem.- Discrete-Time Fourier Transform.- Introducing Spectral Analysis.- Finite Impulse Response Filters.

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