The Nyquist sampling theorem differentiates samplers from digitizers. Undersampling is a term that explains the function of samplers relative to the Nyquist frequency Fs/2. M = the number of test ...

A thought-provoking look at undersampling in data science—exploring when it's harmful, when it's helpful, and why context matters more than hype.

This is the basic mission of 'undersampling'. In order to apply undersampling successfully, a careful frequency plan must be developed. One tried and true technique is the 'fan-fold' paper method.

In undersampling applications, such as wideband receivers, cellular base stations, and communications receivers, the undersampled signal has a relatively low-frequency bandwidth—with the help of the ...