Lecture

Signal processing and vector spaces

Description

This lecture covers the importance of using vector spaces in signal processing, providing a unified framework for different classes of signals, continuous-time signals, Fourier Transform, sampling, interpolation, approximation, compression, and communication system design. It explains the general properties of vector spaces and how once these properties are satisfied, all tools for the space can be utilized. Analogies with object-oriented programming and LEGO are used to illustrate the concepts.

In MOOCs (4)

Instructors (3)

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Official source

https://mediaspace.epfl.ch/media/0_i3bie872

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Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Information engineering

Signal processing: Data compression, Fourier analysis

Statistics

Data collection: Statistical sampling

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