he objective of this book is to implement signal processing algorithms in Python. There are many open-source software packages available to implement signal processing algorithms. The reasons for choosing Python are (1) it is a general-purpose programming language that can be used for various tasks beyond scientiο¬c computing. (2) Python has an active community of developers who create and maintain a wide range of libraries and frameworks. (3) Python has become the language of choice for many Machine Learning and Deep Learning applications with powerful libraries such as TensorFlow, PyTorch, and Keras. The main aim of signal processing is to extract information from the signal. After extracting useful information, further processing, like classiο¬cation of information, has to be done effectively using Machine Learning and Deep Learning libraries in Python.
In this book, Python is used as a tool to implement signal processing algorithms. Teaching Python is not the main aim of this book. Python is used as a vehicle to present concepts related to signal processing. In this book, the signals are generated, manipulated, transformed, and useful information is extracted using libraries available in Python. The Python programs used in this book are purposively made simple and illustrative. The libraries used in this book include (1) Numpy, (2) Scipy, (3) Matplotlib, etc. These libraries provide a wide range of tools and functions for performing operations like ο¬ltering, resampling, prediction, etc.