A sparse signal is a signal that contains a significant amount of zeros or negligible values, with only a few non-zero or significant components. In various contexts, such as in signal processing or machine learning, sparsity implies that the signal can be effectively represented with fewer parameters or features than its dimension suggests. This property allows for more efficient storage, transmission, and processing of the signal. Sparsity is often leveraged in techniques like compressed sensing and feature selection.
In signal and image processing, "sparse" refers to a representation where most of the signal or image data is zero or near-zero, with only a few significant non-zero values. This sparsity can facilitate more efficient storage, transmission, and processing, as only the essential components need to be retained. Sparse representations are often leveraged in techniques like compressed sensing, where the goal is to recover signals from fewer samples than traditionally required. Such representations are particularly useful in applications like image compression and denoising.
i made a sparse contribution for a charity
Sparse was created in 2003.
Sparse grass
The antonym for sparse is dense.
Another sparse matrix.
Sparse grow in plain land
The comparative form of sparse is sparser
Slim Pickins had sparse facial hair. Some parts of the desert have sparse growth.
A sparse matrix is a matrix in which most of the elements are zero.
The sparse caterpillars are poisonous to cats and dogs, but not humans. Sparse caterpillars do however sting as a way to protect themselves.
Example sentence - The grass in the pasture looked sparse.