Signal compression using the discrete linear chirp transform (DLCT)

Signal compression aims to decrease transmission rate (increase storage capacity) by reducing the amount of data necessary to be transmitted. The discrete linear chirp transform (DLCT) is a joint frequency instantaneous-frequency transform that decomposes the signal in terms of linear chirps. The DLCT can be used to transform signals that are not sparse in either time or frequency, such as linear chirps, into sparse signals. In this paper, we propose a new algorithm for signal compression based on the direct and the dual DLCT, depending on the sparsity of the signal in either time or in frequency. Furthermore, we develop a data structure for the extracted coefficients of compressed signals. In the data structure, the extracted parameters are arranged in certain way that are predetermined for the compress and decompress processes. The ability of the proposed method in signal compression are demonstrated using test as well as actual signals. The results are compared with those obtained with compressive sensing (CS) method.