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A compression algorithm based on wavelet networks for historical data in process control system is developed in this paper. The implementation and computation process of the algorithm are described in detail. The simulation results show that the algorithm has the advantage of high convergence rate and compression ratio once applied to the compression and decompression process of pressure signals from...
Signal decomposition is usually used as a preprocessing step in signal processing. After decomposing an original signal, we can process each decomposed bases individually. Different decomposition methods result in different bases. Less number of bases could reduce the complexity of further processing. This paper shows a new method, which decomposes a signal into a mixture of continuous and discontinuous...
In terms of the fractional Fourier transform and the generalized Hilbert transform, in this note, we prove the kernel function K-p (u,t) of the inverse fractional Fourier transform is a generalized analytic signal. Since there is a close relation between analytic signals and Bedrosian theorem, the generalized Bedrosian theorem is provided in the fractional Fourier domain
The minimum mean-square error (MMSE) is an important optimization criterion, which is widely applied to many fields in signal processing and others, such as waveforms estimation, signal detection and system identification. In many practical scenarios, the optimal solutions are usually expected to locate in some especial subspace. So, it is significant to study the MMSE detector or estimator with various...
How to choose a wavelet basis for a given signal is always important and difficult in wavelet applications. In this paper, based on the fact that the Morlet has been conventionally selected to make wavelet analysis of LFM signals, some further research on the wavelet basis selection are done. Morlet is in fact not the best choice under all application conditions related to LFM signals processing,...
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