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Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
book

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

by Robert Johansson
September 2024
Intermediate to advanced content levelIntermediate to advanced
501 pages
17h 6m
English
Apress
Content preview from Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024
R. JohanssonNumerical Pythonhttps://doi.org/10.1007/979-8-8688-0413-7_17

17. Signal Processing

Robert Johansson1  
(1)
Urayasu-shi, Chiba, Japan
 

This chapter explores signal processing, a subject with applications in diverse branches of science and engineering. A signal in this context can be a quantity that varies in time (temporal signal) or as a function of space coordinates (spatial signal). An audio signal is a typical example of a temporal signal, while an image is a typical example of a spatial signal in two dimensions. In practice, signals are often continuous functions. But it is common in computational applications to work with discretized signals, ...

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