Sparse approximation

Sparse approximation is a mathematical and computational technique used in various fields such as signal processing, machine learning, and statistics. The key idea behind sparse approximation is to represent a signal or data set as a linear combination of a small number of basis elements from a larger set, such that the representation uses significantly fewer non-zero coefficients compared to traditional methods. ### Key Concepts: 1. **Sparsity**: A representation is considered sparse if most of its coefficients are zero or close to zero.