Sparsity refers to the condition of having a significant number of zero or near-zero elements in a dataset or signal, which allows for more efficient data representation and processing. It plays a crucial role in various fields by enabling algorithms to focus on the most important components while ignoring redundant information, making it easier to recover or estimate signals with minimal error. In many applications, including estimation and recovery, sparsity is leveraged to improve computational efficiency and accuracy.
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