数据采集与处理2017，Vol.32Issue(2)：232-245,14.DOI:10.16337/j.1004-9037.2017.02.003
语音信号处理中鲁棒性压缩感知关键技术
Key Issues of Robust Compressed Sensing in Speech Signal Processing
摘要
Abstract
Compressed sensing (CS) is widely used in different areas.The key technologies of compressed sensing include the selection of sparse matrix,the construction of the measurement matrix,and the design of the reconstruction algorithm.Speech signal usually has special structural characteristics in the measurement matrix and reconstruction algorithm.In actual applications,noises may inevitably exist.In compressed sensing theory,the reconstruction system is nonlinear and sensitive to noise.Therefore,we need to study the robust compressed sensing technology.This technique would have utilizable perspective,if the robustness problem gets solved.The paper begins with the concept of compressed sensing,then analyses the effects brought by various noises.When it comes to the solutions to the noises in the speech signal,this paper focuses on the introduction of robust projection operator and robust recovery algorithms.Finally,the possible future research directions are prospected.关键词
压缩感知/鲁棒性/重构算法/语音信号/投影算子Key words
compressed sensing/robustness/reconstruction algorithm/speech signal/projection operator分类
信息技术与安全科学引用本文复制引用
杨震,徐珑婷..语音信号处理中鲁棒性压缩感知关键技术[J].数据采集与处理,2017,32(2):232-245,14.基金项目
国家自然科学基金(61671252,61271335)资助项目 （61671252,61271335）
南京邮电大学校科研基金(NY214191)资助项目. （NY214191）
