Denoising audio sampling algorithm based on signal frequency probability density function distribution

Abstract

The invention relates to a denoising audio resampling algorithm based on signal frequency probability density function distribution and belongs to the technical field of audio signal processing. According to the algorithm, a collected audio signal is processed through utilizing the excellent denoising capability and the forward prediction function of a Kalman filter to obtain a denoising audio with the short-term prediction function, Fourier transform is performed for a processed audio signal to obtain a spectral function of the audio signal, and the audio signal is resampled under the controlof a probability density function p(f). Redundant sampling points are reduced, the collected audio signal is subjected to Kalman filtering processing to obtain resampling data, the processing resultis smoother compared with other algorithms, the recovered audio signal is of higher quality, real-time performance of audio signal processing is improved, the algorithm is simple in theory, programming is further easy to implement, and practical engineering applications further have strong stability and robustness.

Description

technical field [0001] The invention relates to a denoising frequency sampling algorithm based on signal frequency probability density function distribution, and belongs to the technical field of audio characteristic signal processing. Background technique [0002] At present, uniform sampling is mostly used for audio signal sampling, and the set sampling frequency is too low, and the recovered signal after information transmission has a large degree of distortion. If the set sampling frequency is high to meet the accuracy requirements, but a large amount of data processing It also poses a great challenge to the information processing system. It is difficult to choose an appropriate sampling frequency to satisfy distortion-free sampling and eliminate redundant redundant information. The resampling algorithm that the present invention proposes first utilizes the Kalman filter to carry out denoising processing to the signal to obtain the denoising signal with a certain short-t...

AI Technical Summary

Problems solved by technology

[0002] At present, uniform sampling is mostly used for audio signal sampling, and the set sampling frequency is too low, and the recovered signal after information transmission has a large degree of distortion. If the set sampling frequency is high to meet the accuracy requirements, but a large amount of data processing It also poses a great challenge to the information processing system. It is difficult to choose an appropriate sampling frequency to satisfy distortion-free sampling and eliminate redundant redundant information.

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