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Python for Signal Processing

Python for Signal Processing PDF Author: José Unpingco
Publisher: Springer Science & Business Media
ISBN: 3319013424
Category : Technology & Engineering
Languages : en
Pages : 128

Book Description
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.

Python for Signal Processing

Python for Signal Processing PDF Author: José Unpingco
Publisher: Springer Science & Business Media
ISBN: 3319013424
Category : Technology & Engineering
Languages : en
Pages : 128

Book Description
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.

Think DSP

Think DSP PDF Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 149193851X
Category : Technology & Engineering
Languages : en
Pages : 168

Book Description
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.

Digital Signal Processing (DSP) with Python Programming

Digital Signal Processing (DSP) with Python Programming PDF Author: Maurice Charbit
Publisher: John Wiley & Sons
ISBN: 1119373034
Category : Technology & Engineering
Languages : en
Pages : 290

Book Description
The parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.

Hands-on Signal Analysis with Python

Hands-on Signal Analysis with Python PDF Author: Thomas Haslwanter
Publisher: Springer Nature
ISBN: 3030579034
Category : Technology & Engineering
Languages : en
Pages : 276

Book Description
This book provides the tools for analyzing data in Python: different types of filters are introduced and explained, such as FIR-, IIR- and morphological filters, as well as their application to one- and two-dimensional data. The required mathematics are kept to a minimum, and numerous examples and working Python programs are included for a quick start. The goal of the book is to enable also novice users to choose appropriate methods and to complete real-world tasks such as differentiation, integration, and smoothing of time series, or simple edge detection in images. An introductory section provides help and tips for getting Python installed and configured on your computer. More advanced chapters provide a practical introduction to the Fourier transform and its applications such as sound processing, as well as to the solution of equations of motion with the Laplace transform. A brief excursion into machine learning shows the powerful tools that are available with Python. This book also provides tips for an efficient programming work flow: from the use of a debugger for finding mistakes, code-versioning with git to avoid the loss of working programs, to the construction of graphical user interfaces (GUIs) for the visualization of data. Working, well-documented Python solutions are included for all exercises, and IPython/Jupyter notebooks provide additional help to get people started and outlooks for the interested reader.

Linear Algebra, Signal Processing, and Wavelets - A Unified Approach

Linear Algebra, Signal Processing, and Wavelets - A Unified Approach PDF Author: Øyvind Ryan
Publisher: Springer
ISBN: 3030018121
Category : Mathematics
Languages : en
Pages : 360

Book Description
This book offers a user friendly, hands-on, and systematic introduction to applied and computational harmonic analysis: to Fourier analysis, signal processing and wavelets; and to their interplay and applications. The approach is novel, and the book can be used in undergraduate courses, for example, following a first course in linear algebra, but is also suitable for use in graduate level courses. The book will benefit anyone with a basic background in linear algebra. It defines fundamental concepts in signal processing and wavelet theory, assuming only a familiarity with elementary linear algebra. No background in signal processing is needed. Additionally, the book demonstrates in detail why linear algebra is often the best way to go. Those with only a signal processing background are also introduced to the world of linear algebra, although a full course is recommended. The book comes in two versions: one based on MATLAB, and one on Python, demonstrating the feasibility and applications of both approaches. Most of the MATLAB code is available interactively. The applications mainly involve sound and images. The book also includes a rich set of exercises, many of which are of a computational nature.

Practical Signal Processing

Practical Signal Processing PDF Author: Mark Owen
Publisher: Cambridge University Press
ISBN: 0521854784
Category : Technology & Engineering
Languages : en
Pages : 347

Book Description
This book introduces the basic theory of digital signal processing, with emphasis on real-world applications.

Digital Filter Design using Python for Power Engineering Applications

Digital Filter Design using Python for Power Engineering Applications PDF Author: Shivkumar Venkatraman Iyer
Publisher: Springer Nature
ISBN: 3030618609
Category : Technology & Engineering
Languages : en
Pages : 201

Book Description
This book is an in-depth description on how to design digital filters. The presentation is geared for practicing engineers, using open source computational tools, while incorporating fundamental signal processing theory. The author includes theory as-needed, with an emphasis on translating to practical application. The book describes tools in detail that can be used for filter design, along with the steps needed to automate the entire process. Breaks down signal processing theory into simple, understandable language for practicing engineers; Provides readers with a highly-practical introduction to digital filter design; Uses open source computational tools, while incorporating fundamental signal processing theory; Describes examples of digital systems in engineering and a description of how they are implemented in practice; Includes case studies where filter design is described in depth from inception to final implementation.

Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK

Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK PDF Author: Rulph Chassaing
Publisher: John Wiley & Sons
ISBN: 1118210344
Category : Science
Languages : en
Pages : 612

Book Description
Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK Now in a new edition—the most comprehensive, hands-on introduction to digital signal processing The first edition of Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK is widely accepted as the most extensive text available on the hands-on teaching of Digital Signal Processing (DSP). Now, it has been fully updated in this valuable Second Edition to be compatible with the latest version (3.1) of Texas Instruments Code Composer Studio (CCS) development environment. Maintaining the original’s comprehensive, hands-on approach that has made it an instructor’s favorite, this new edition also features: Added program examples that illustrate DSP concepts in real-time and in the laboratory Expanded coverage of analog input and output New material on frame-based processing A revised chapter on IIR, which includes a number of floating-point example programs that explore IIR filters more comprehensively More extensive coverage of DSP/BIOS All programs listed in the text—plus additional applications—which are available on a companion website No other book provides such an extensive or comprehensive set of program examples to aid instructors in teaching DSP in a laboratory using audio frequency signals—making this an ideal text for DSP courses at the senior undergraduate and postgraduate levels. It also serves as a valuable resource for researchers, DSP developers, business managers, and technology solution providers who are looking for an overview and examples of DSP algorithms implemented using the TMS320C6713 and TMS320C6416 DSK.

Machine Learning for Signal Processing

Machine Learning for Signal Processing PDF Author: Max A. Little
Publisher: Oxford University Press, USA
ISBN: 0198714939
Category : Computers
Languages : en
Pages : 378

Book Description
Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Digital Signal Processing and Spectral Analysis for Scientists

Digital Signal Processing and Spectral Analysis for Scientists PDF Author: Silvia Maria Alessio
Publisher: Springer
ISBN: 3319254685
Category : Technology & Engineering
Languages : en
Pages : 900

Book Description
This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.