Parameterized Lifting for Sparse Signal Representations Using the Gini Index
نویسندگان
چکیده
Sparsity is good. We like sparsity. We can make signals more sparse by transforming them. This paper proposes a novel, two-parameter method for designing a stable wavelet basis. Our goal is to determine a basis that represents a given signal as sparsely as possible. We choose the Gini index as a measure of sparsity and sparsify a signal by iteratively lifting the wavelet basis and at each step choosing the lift that maximizes the Gini index of the representation.
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