Sub-Nyquist sampling and Finite Rate of Innovation (FRI) signal processing represent a paradigm shift in the acquisition and reconstruction of signals. Traditional sampling theories require adherence ...

In part 1, we started to make some intuitive connections between near-Nyquist sampling, the addition of close-frequency sines, and how those signals would interact with perfect LP filters. Let's put ...

Bravo to Harry Nyquist and Claude Shannon! In the 1920s, these gentlemen created the now-well-known Nyquist theorem, which states that when sampling a signal at discrete intervals, the sampling must ...

A look at the Nyquist sampling theorem. How to deal with aliasing by attenuating signals using low-pass filters (i.e., an antialiasing filter, or AAF). AAF requirements for different ADCs. A deep dive ...

A research team at POSTECH, led by Professor Junsuk Rho, along with M.S./Ph.D. students Seokwoo Kim, Joohoon Kim, Kyungtae ...

A research team has developed a novel multidimensional sampling theory to overcome the limitations of flat optics. The study not only identifies the constraints of conventional sampling theories in ...

If you haven’t come across compressive sensing, you will do soon. It’s a way of sampling and reconstructing an analogue signal at a rate far lower than standard information theory would deem possible.

Sampling a signal causes the original signal spectrum (blue) to create sum (purple) and difference (red) frequencies around the sampling frequency, fS. When the difference signals fall into the ...

A research team at POSTECH has developed a novel multidimensional sampling theory to overcome the limitations of flat optics.