Abstract
A new data compression method is shown, implementation of the algorithm is based on the classical theory of numerical analysis. The values of the k th.order finite differences of the samples are calculated and their greatest value determines the length of the time interval, which will be compressed by means of k data stored in memory. In this time domain analysis method (TDAM), it is possible to fix initially the desired peak error. Logically the length of the compressed interval is also a function of this peak error. A polynomial interpolation passing through the stored data perforins the reconstruction of the compressed samples. To improve the method, a process of sample preselection is used allowing high compression of smooth signals. Moreover, the number of stored data is not subordinated to the number of samples taken from a given waveform. This procedure allows for good efficiency in the observation and compression of almost unknown signals, as the experimental results show.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
