Optimum Rate-Distortion Dictionary Selection for Compression of Atomic Decompositions of Electric Disturbance Signals

In this letter, we address rate-distortion-optimum compression of signals from electric power system disturbances, using atomic decompositions. Usually, such optimization is obtained assuming a single dictionary and consists of finding the best compromise between the quantization of the coefficients in the atomic decomposition and its number of terms. Here, several parameterized dictionaries are used instead. This allows the selection of the dictionary leading to the best rate-distortion (R-D) compromise. Distinct dictionaries correspond to different quantizers for the parameters of the atoms. Side information must be transmitted in order to indicate the dictionary employed. The R-D performance in this case depends on a complex interplay between the quantizers of the parameters of the atoms and the coefficient quantizers. Using a training stage, we select a reduced set of parameter and coefficient quantizers that give near-optimum R-D performance. Simulation results show that the proposed scheme indeed achieves near-optimum R-D performance with low computational complexity in the coding stage