Compressed sensing is a signal processing technique that allows for the reconstruction of a signal from a small number of measurements, based on the principle that many signals are sparse or compressible in some basis. This method enables efficient data acquisition and recovery, which is particularly beneficial in applications like imaging and communications, where traditional sampling techniques can be inadequate or inefficient. It leverages the concept of sparsity, meaning that only a few components are needed to accurately describe a signal, making it closely related to various approximation strategies.
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