Compressive sensing is a signal processing technique that enables the reconstruction of sparse or compressible signals from a small number of linear measurements. It allows for the efficient acquisition and representation of signals using fewer samples than traditional methods, making it particularly useful in applications where data acquisition is costly or time-consuming. Compressive sensing has found applications in various fields including medical imaging, remote sensing, and audio signal processing. The key idea behind compressive sensing is that by exploiting the sparsity or compressibility of the signal, one can recover the original signal accurately from a reduced set of measurements. This technique has enabled significant advancements in signal processing and data acquisition, leading to more efficient and cost-effective systems.