Compressive Sampling for Energy Spectrum Estimation of Turbulent Flows

Recent results from compressive sampling (CS) have demonstrated that accurate reconstruction of sparse signals often requires far fewer samples than suggested by the classical Nyquist--Shannon sampling theorem. Typically, signal reconstruction errors are measured in the $\ell^2$ norm and the signal is assumed to be sparse or compressible. Our spectrum estimation by sparse optimization (SpESO) method uses a priori information about isotropic …