This Topic considers the concept of aliasing, which is signal distortion
due to the spectral overlap of the spectral images that result from the
sampling process. This Topic discusses the condition under which
aliasing occurs, and investigates what happens when the spectral images
are summed together, and the resulting signal after the reconstruction
filter. The Topic then considers strategies for how to avoid aliasing in
practice, including the notion of anti-aliasing filters, and
oversampling. The video also considers the limitations of practical data
systems, such as imperfect low-pass filters in the anti-aliasing and
reconstruction filters, as well as imperfect sample-and-hold and DACs.
Finally, the video considers the exemplar case of high-resolution audio.
ELEE08021 Sensor Networks and Data Analysis 2 Lectures -- School of Engineering, University of Edinburgh. Copyright James R. Hopgood and University of Edinburgh, Scotland, United Kingdom (UK). 2020.
Institute for Digital Communications, Alexander Graham Bell Building, The King's Buildings, Thomas Bayes Road, Edinburgh, EH9 3JL. UK.