10. A system for hierarchical sparse dictionary learning (“HiSDL”) to construct a learned dictionary regularized by an a priori over-complete dictionary, the system comprising: an a priori over-complete dictionary generator configured to provide at least one a priori over-complete dictionary for regularization; a sparse coder configured to perform sparse coding of the at least one a priori over-complete dictionary to provide a sparse coded dictionary; using a processor, a dictionary updater configured to update the sparse coded dictionary with regularization using at least one auxiliary variable to provide a learned dictionary; a convergence determination device configured to determine convergence of the learned dictionary to an input data set; and an output device configured to output the learned dictionary regularized by the at least one a priori over-complete dictionary when the learned dictionary converges to the input data set.
12. The system of claim 10 , wherein the input data set includes at least one of high-dimensional heterogeneous time series data and a data matrix.