含噪语音压缩感知自适应快速重构算法
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摘要
本文针对含噪语音压缩感知在低信噪比时重构语音性能差的问题,提出了一种自适应快速重构算法。该算法将行阶梯观测矩阵与一种新型的快速重构算法结合,并根据含噪语音信号的信噪比自适应选择最佳重构参数,使得在重构语音的同时提高了重构信噪比。算法实现简单快速,且不需要预先计算信号的稀疏度。实验结果表明:在低信噪比时,自适应快速重构算法的重构性能优于基追踪算法和快速重构算法,且重构速度快于快速重构算法和基追踪算法。
An adaptive fast recovery algorithm is proposed to solve the problem of poor reconstruction performance for compressed sensing of noisy speech with low signal-to-noise ratio. This method combines row echelon measurement matrix and a new fast recovery algorithm,adaptively selects the optimal reconstruction parameters according to the signal-to-noise ratio of noisy speech signal,and enhances the signal-to-noise ratio while reconstructing the speech. The adaptive fast recovery algorithm is simple and fast and does not require pre-calculated signal sparsity. Simulation experiment results demonstrate that the proposed algorithm outperforms basis pursuit algorithm and fast reconstruction algorithm,and faster than basis pursuit algorithm and fast recovery algorithm.
An adaptive fast recovery algorithm is proposed to solve the problem of poor reconstruction performance for compressed sensing of noisy speech with low signal-to-noise ratio. This method combines row echelon measurement matrix and a new fast recovery algorithm,adaptively selects the optimal reconstruction parameters according to the signal-to-noise ratio of noisy speech signal,and enhances the signal-to-noise ratio while reconstructing the speech. The adaptive fast recovery algorithm is simple and fast and does not require pre-calculated signal sparsity. Simulation experiment results demonstrate that the proposed algorithm outperforms basis pursuit algorithm and fast reconstruction algorithm,and faster than basis pursuit algorithm and fast recovery algorithm.
引文
[1]Donoho D L.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
[2]Candes E J,Romberg J,Tao T.Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theory,2006,52(2):489-509.
[3]杨真真,杨震.语音压缩感知硬阈值梯度追踪重构算法[J].信号处理,2014,30(4):391-398.Yang Z Z,Yang Z.Hard Threshold Gradient Pursuit Reconstruction Algorithm for Speech Compressed Sensing[J].Journal of Signal Processing,2014,30(4):391-398.(in Chinese)
[4]Mingrui Yang,Frank de Hoog.Orthogonal Matching Pursuit with Thresholding and Its Application in Compressive Sensing[J].IEEE Transactions on Signal Processing,2015,63(20):5479-5486.
[5]孙林慧,杨震.语音压缩感知研究进展与展望[J].数据采集与处理,2015,30(2):275-288.Sun L H,Yang Z.Compressed Speech Sensing for Research Process and Prospect[J].Journal of Data Acquisitions and Processing,2015,30(2):275-288.(in Chinese)
[6]孙林慧,杨震.基于自适应基追踪去噪的含噪语音压缩感知[J].南京邮电大学学报,2011,31(5):1-6.Sun L H,Yang Z.Compressed sensing of noisy speech signal based on adaptive basis pursuit de-noising[J].Journal of Nanjing University of Posts and Telecommunications:Natural Science,2011,31(5):1-6.(in Chinese)
[7]杨真真,杨震.含噪语音压缩与重构的自适应共轭梯度投影算法[J].仪器仪表学报,2012,33(10):2200-2207.Yang Z Z,Yang Z.Adaptive conjugate gradient projection algorithm for noisy speech compression and reconstruction[J].Chinese Journal of Science Instrument,2012,33(10):2200-2207.(in Chinese)
[8]季云云,杨震.脉冲噪声环境下高斯稀疏信源贝叶斯压缩感知重构[J].电子学报,2013,41(2):363-370.Ji Y Y,Yang Z.Bayesian Compressed sensing for Gaussian Sparse Signals in the Presence of Impulsive Noise[J].Acta Electronica Sinica,2013,41(2):363-370.(in Chinese)
[9]叶蕾,杨震,王天荆,等.行阶梯观测矩阵,对偶仿射尺度内点重构算法下的语音压缩感知[J].电子学报,2012,40(3):429-434.Ye L,Yang Z,Wang T J,et al.Compressed sensing of speech signal based on row echelon measurement matrix and dual affine scaling interior point reconstruction method[J].Acta Electronica Sinica,2012,40(3):429-434.(in Chinese)
[10]Andrianiaina Ravelomanantsoa,Hassan Rabah,Amar Rouane.Compressed sensing:A Simple Deterministic Measurement Matrix and a Fast Recovery Algorithm[J].IEEE Transactions on Instrumentation and Measurement,2015,64(12):3405-3413.
[11]Golub G H,Loan C F V.Matrix Computations[M].Third Edition.London,UK:The Johns Hopkins University Press,1996.
[12]Hoda Dehghan,Richard M,Dansereau,Adrian D C.Restricted Isometry Property on Banded Block Toeplitz Matrices with Application to Multi-Channel Convolutive Source Separation[J].IEEE Transactions on Signal Processing,2015,63(21):5665-5676.
[2]Candes E J,Romberg J,Tao T.Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theory,2006,52(2):489-509.
[3]杨真真,杨震.语音压缩感知硬阈值梯度追踪重构算法[J].信号处理,2014,30(4):391-398.Yang Z Z,Yang Z.Hard Threshold Gradient Pursuit Reconstruction Algorithm for Speech Compressed Sensing[J].Journal of Signal Processing,2014,30(4):391-398.(in Chinese)
[4]Mingrui Yang,Frank de Hoog.Orthogonal Matching Pursuit with Thresholding and Its Application in Compressive Sensing[J].IEEE Transactions on Signal Processing,2015,63(20):5479-5486.
[5]孙林慧,杨震.语音压缩感知研究进展与展望[J].数据采集与处理,2015,30(2):275-288.Sun L H,Yang Z.Compressed Speech Sensing for Research Process and Prospect[J].Journal of Data Acquisitions and Processing,2015,30(2):275-288.(in Chinese)
[6]孙林慧,杨震.基于自适应基追踪去噪的含噪语音压缩感知[J].南京邮电大学学报,2011,31(5):1-6.Sun L H,Yang Z.Compressed sensing of noisy speech signal based on adaptive basis pursuit de-noising[J].Journal of Nanjing University of Posts and Telecommunications:Natural Science,2011,31(5):1-6.(in Chinese)
[7]杨真真,杨震.含噪语音压缩与重构的自适应共轭梯度投影算法[J].仪器仪表学报,2012,33(10):2200-2207.Yang Z Z,Yang Z.Adaptive conjugate gradient projection algorithm for noisy speech compression and reconstruction[J].Chinese Journal of Science Instrument,2012,33(10):2200-2207.(in Chinese)
[8]季云云,杨震.脉冲噪声环境下高斯稀疏信源贝叶斯压缩感知重构[J].电子学报,2013,41(2):363-370.Ji Y Y,Yang Z.Bayesian Compressed sensing for Gaussian Sparse Signals in the Presence of Impulsive Noise[J].Acta Electronica Sinica,2013,41(2):363-370.(in Chinese)
[9]叶蕾,杨震,王天荆,等.行阶梯观测矩阵,对偶仿射尺度内点重构算法下的语音压缩感知[J].电子学报,2012,40(3):429-434.Ye L,Yang Z,Wang T J,et al.Compressed sensing of speech signal based on row echelon measurement matrix and dual affine scaling interior point reconstruction method[J].Acta Electronica Sinica,2012,40(3):429-434.(in Chinese)
[10]Andrianiaina Ravelomanantsoa,Hassan Rabah,Amar Rouane.Compressed sensing:A Simple Deterministic Measurement Matrix and a Fast Recovery Algorithm[J].IEEE Transactions on Instrumentation and Measurement,2015,64(12):3405-3413.
[11]Golub G H,Loan C F V.Matrix Computations[M].Third Edition.London,UK:The Johns Hopkins University Press,1996.
[12]Hoda Dehghan,Richard M,Dansereau,Adrian D C.Restricted Isometry Property on Banded Block Toeplitz Matrices with Application to Multi-Channel Convolutive Source Separation[J].IEEE Transactions on Signal Processing,2015,63(21):5665-5676.