Название: Signal Processing with Python: A Practical ApproachАвтор: Irshad Ahmad Ansari, Varun Bajaj
Издательство: IOP Publishing
Год: 2024
Страниц: 297
Язык: английский
Формат: pdf (true)
Размер: 59.5 MB
This book explores the domain of signal processing using Python, with the help of working examples and accompanying code. The book introduces the concepts of Python programming via signal processing with numerous hands-on examples and code snippets. The book will enable readers to appreciate the power of Python in this field and write their code to implement complex signal processing algorithms such as signal compression, cleaning, segmentation, decomposition, and feature extraction and be able to incorporate machine learning models using relevant Python libraries. This book aims to bring together professionals from academia and industry to ignite new developments and techniques in the domain of signal processing with Python.
Python, being an open source and popular language, has attracted a lot of application development. Signal processing has also seen tremendous growth in the recent past. The majority of signal processing work revolves around simulation and testing before the final hardware implementation. Many times, code-based implementation itself is sufficient. These implementations make use of a cloud processing unit for a faster and more efficient user experience. Python has been developed as a tool for simulation, visualization, understanding, and manipulation of signals. The same has attracted a lot of new development in the field of signal processing. Python and signal processing both go hand in hand for many applications developments. The present book is an attempt to explore the domain of signal processing with the help of working examples of the Python language.
There are many signal processing applications such as acquisition, sensing, representation, understanding, feature extraction, classification, compression etc. There are standard ways to implement different signal processing methods. Signal processing has become a backbone of modern technical systems. It is almost impossible to develop any systems without using signal processing concepts. Python has helped developers to club together different concepts of signals to make use of them for practical systems. The proposed book is an attempt to introduce the concepts of Python via signal processing with hands-on examples for the readers. The book is planned to include code-led examples that will help readers to get an in-depth understanding of the subject. We will use Python libraries MNE, NumPy, Matplotlib, and Pandas to preprocess and make data usable for further Machine Learning algorithms and models.
Furthermore, the book first focuses on the basics of Python and signal processing, then moves forward to more advanced applications like Machine Learning (ML) and research avenues in the domain. This field of academia and new system development is rapidly changing. Python is a multifaceted area of development including the concepts of signal processing, ML etc. Therefore, the aim of this book is to bring forward professionals from academia and industry, presenting their recent work with Python support.
Key features:
• Hands-on Python examples and code for each chapter
• Covers basic to advanced topics
• Focuses on practical applications
• Includes machine learning-based applications
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