含噪语音压缩感知自适应快速重构算法  

Adaptive Fast Recovery Algorithm for Compressed Sensing of Noisy Speech

作　　者：张殿飞[1,2] 杨震[1,2] 胡海峰[1,2] 

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003 [2]"宽带无线通信与传感网技术"教育部重点实验室,江苏南京210003

出　　处：《信号处理》2016年第9期1065-1071,共7页Journal of Signal Processing

基　　金：国家自然科学基金(61271335)

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 com- pressed 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 algo- rithm is simple and fast and does not require pre-ealculated signal sparsity. Simulation experiment results demonstrate that the proposed algorithm outperforu：s basis pursuit algorithm and fast reconstruction algorithm, and faster than basis pursuit algorithm and fast recovery algorithm,

关 键 词：压缩感知 离散余弦基 行阶梯观测矩阵 自适应快速重构算法 

分 类 号：TN912.3[电子电信—通信与信息系统]