Optimized measurements for kernel compressive sensing

Certain classes of signals can be well approximated using a few principal components in the feature space, that is obtained by a non-linear transformation of the input signal space. Compressive sensing of such signals with random measurements can be performed using the kernel trick. In this paper, we propose a procedure to compute optimized measurement… CONTINUE READING