A new block compressive sensingto control the number of measurements

Compressive Sensing (CS) aims to recover a sparse signal from a small number of projections onto random vectors. Because of its great practical possibility, both academia and industries have made efforts to develop the CS´s reconstruction performance, but most of existing works remain at the theoretical study. In this paper, we propose a new Block Compres-sive Sensing (nBCS), which has several benefits compared to the general CS methods. In particular, the nBCS can be dynamically adaptive to varying channel capacity because it conveys the good inheritance of the wavelet transform.