摘要
Abstract
When multiple source signals coexist in the same frequency band or time domain,they may interfere with each other,resulting in signal aliasing.In this case,using dual channel audio sensors for capture cannot accurately capture the information of all source signals,resulting in uncertainty in the separation process.A dual channel audio signal noise adaptive separation method based on underdetermined blind source separation is proposed.An underdetermined blind source separation model is constructed,which can decompose and reconstruct the signal based on wavelet packet transform to obtain signal components.The decomposed components are selected based on the number of interrelationships between the signal and the components,and redundant components are removed to generate new observation signals.Based on the Bayesian information criterion,the singular value decomposition method is used to estimate the quantity of the source signal and convert it into the positive definite white signal.The fast independent component analysis method is used to classify the signal,so as to realize adaptive noise separation of dual channel audio signals.The testing results show that this method can complete signal transformation processing while ensuring signal quality,the signal-to-noise ratio results are all above 15 dB,and the correlation coefficients of each component retained after screening are all above 0.65,which can effectively separate signal and noise.关键词
欠定盲源分离/双路音频/信号噪声/自适应分离/小波包变换分解/贝叶斯信息准则Key words
blind source separation/dual channel audio/signal noise/adaptive separation/wavelet packet transform decomposition/Bayesian information criterion分类
信息技术与安全科学
