Adaptive cluster sampling is a probabilistic design tailored to populations that exhibit rare or spatially clustered features, such as endangered species, epidemic cases or hidden cultural artefacts.
Sampling protocols have drastically changed with the discovery of compressive sensing (CS) data acquisition and signal recovery 1,2. Prior to the development of CS theory, the Shannon-Nyquist theorem ...
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