# 1 SAMPLING AND RECONSTRUCTION

With the advent of digital computers, processing information has become faster, more reliable, easy to debug and most importantly allowed for performing complex non-linear tasks. However, since most phenomenon of interest are continuous functions of time, methods of analogue to digital conversion become important.

In this module, we shall see sampling and perfect reconstruction using the famous Shannon sampling theorem that accounts for bandlimited signals. We also delve into other interpolation methods with linear interpolation and motivate the idea of shift-invariant spaces.

### Additional Reading

1. [Shannon's 1949 paper on "*Communication in the presence of noise*"](https://scholar.google.co.in/citations?view_op=view_citation\&hl=en\&user=2M6S-aAAAAAJ\&citation_for_view=2M6S-aAAAAAJ:d1gkVwhDpl0C)
2. [Michael Unser's magazine article on sampling theory](https://scholar.google.co.in/citations?view_op=view_citation\&hl=en\&user=nKVDcQoAAAAJ\&citation_for_view=nKVDcQoAAAAJ:2osOgNQ5qMEC)
