Abstract
An adaptive compression algorithm based on sparse dictionary is proposed to solve the pressure on the transmission system caused by long-time high sampling rate sampling of transient signals. Due to the obvious difference between transient and non-transient information features of transient signals. According to the sparse dictionary construction characteristic that the more matching atoms and signal features are, the better sparse performance is, the transient signal feature information is extracted and compressed separately. After data compression, the principle of compressed sensing is applied to restore the transient signal, so as to reduce the amount of data transmitted in the transmission system. In summary, the adaptive sparse dictionary compression algorithm effectively compresses the transient signal data, and the compressed data can accurately recover the transient signal.
Export citation and abstract BibTeX RIS
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.