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EN
In this paper, a new lifting wavelet domain audio watermarking algorithm based on the statistical characteristics of sub-band coefficients is proposed. First of all, an original audio signal was segmented and each segment was divided into two sections. Then, the Barker code was used for synchronization, the LWT (lifting wavelet transform) was performed on each section, a synchronization code and a watermark were embedded into the first section and the second section, respectively, by modifying the statistical average value of the sub-band coefficients. The embed strength was determined adaptively according to the auditory masking property. Experiments show that the embedded watermark has better robustness against common signal processing attacks than present algorithms based on LWT and can resist random cropping in particular.
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Content available remote Lifting based compression algorithm for power system signals
EN
The paper concerns the problem of power system signals compression with possible application in system monitoring and control. The proposed compression algorithm for power system signals ensures efficient use of available storage memory or communication channel bandwidth. It is shown that while preserving good quality, compression ratios from 20 in case of highly distorted waveforms to 340 for slightly distorted sinusoidal waves can be achieved. The presented results were evaluated with a specially prepared representative database of field-recorded electric signals. For signal decorrelation lifting implementation of wavelet transform in the compression algorithm was used. The influence of sampling frequency, length of data frame, type of wavelet function, number of wavelet decomposition stages and quantization level on the compression ratio and compression quality was investigated.
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