Hands-on Signal Analysis with Python: An Introduction

This book provides a comprehensive introduction to data analysis in Python, covering filters, the Fourier transform, and machine learning. It includes examples and working Python programs, with tips for efficient programming and the construction of graphical user interfaces.

Format: Paperback / softback
Length: 267 pages
Publication date: 02 June 2022
Publisher: Springer Nature Switzerland AG

This comprehensive book offers a comprehensive guide to analyzing data in Python, covering various types of filters, including FIR, IIR, and morphological filters, along with their applications to one- and two-dimensional data. The mathematics required are kept to a minimum, making it accessible to novice users while providing ample examples and working Python programs for a quick start. The primary objective is to empower users, even those with limited programming experience, to select appropriate methods and successfully accomplish real-world tasks such as differentiation, integration, smoothing of time series, and simple edge detection in images.

To facilitate a smooth learning experience, an introductory section provides helpful tips and guidance on installing and configuring Python on your computer. As the book progresses, more advanced chapters delve into the realm of the Fourier transform, exploring its applications in sound processing and the solution of equations of motion using the Laplace transform. Additionally, a brief excursion into machine learning showcases the powerful tools available with Python.

Furthermore, the book offers valuable tips for efficient programming workflows, including the use of a debugger for identifying errors, code versioning with Git to prevent program loss, and the construction of graphical user interfaces (GUIs) for data visualization. Working, well-documented Python solutions are provided for all exercises, and IPython/Jupyter notebooks offer additional support and insights for the interested reader. By utilizing the comprehensive resources provided in this book, readers will gain the skills and knowledge necessary to effectively analyze data in Python and unlock its full potential for various applications.

Weight: 705g
Dimension: 279 x 210 (mm)
ISBN-13: 9783030579050
Edition number: 1st ed. 2021