Information entropy analysis for signal quantization and discrete Fourier transforms
The conventional description method does not meet the requirements of peoples work to obtain the information carried by the signal,and in view of the problem of information loss in the process of signal quantification and acquisition spectrum,it is proposed to analyze the change of quantification and discrete Fourier transform information from the perspective of in-formation domain,and measure the effect of processing by the amount of information.Based on the entropy representation of the discrete Fourier transform derived from the information entro-py,it can be seen from the application example results that when the number of sampling points reaches a certain value,the output entropy of the signal tends to a constant value,and combined with the spectrogram,it is found that the spectrogram obtained by increasing the number of sampling points has almost no change,and the information loss is negligible.The experimental data results are generally universal,providing theoretical support for the original empirical work,and the effect prediction before processing can reduce the experimental cost and save time,and provide an objective analysis method for signal processing.
Information entropyMutual in formationdiscrete Fourier transformQuantizationSignal processing
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