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)
Digital Signal Processing I
Basic signal processing concepts, Fourier analysis and filters. This module can
be used as a starting point or a basic refresher in elementary DSP
Digital Signal Processing II
Adaptive signal processing, A/D and D/A. This module provides the basic
tools for adaptive filtering and a solid mathematical framework for sampling and
quantization
Digital Signal Processing III
Advanced topics: this module covers real-time audio processing (with
examples on a hardware board), image processing and communication system design.
Digital Signal Processing IV
Advanced topics: this module covers real-time audio processing (with
examples on a hardware board), image processing and communication system design.
Instructors (3)
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