compressive sensing(CS) 又称 compressived sensing ,compressived sample,大意是在采集信号的时候(模拟到数字),同时完成对信号压缩之意。中文的翻译成“压缩感知”,意思变得至少不太好理解了。 Compressed sensing is a mathematical tool that creates hi-res data sets from lo-res samples. It can be used to...
Tao(2006年菲尔兹奖获得者,2008年被评为世界上最聪明的科学家)等人提出了一种新的信息获取指导理论,即,压缩感知或压缩传感(Compressive Sensing(CS) or Compressed Sensing、Compressed Sampling)。该理论指出:对可压缩的信号可通过远低于Nyquist标准的方式进行采样数据,仍能够精确地恢复出原始信号。该理论一经提出,就...
DCN）学习信号的表示，且类似于贪婪算法或凸松弛算法完成从测量向量到原始信号的逆变换，与传统CS类似的...
压缩感知（Compressive Sensing, CS）是一种理论框架，用于研究如何高效地采集和恢复稀疏或近似稀疏信号。...
理论与实践的边界：狭义的CS主要基于稀疏性，随机采样是常见策略，但非零支持的不确定性增加了分析的复杂性。广义的CS则更包容，包括低秩模型、统计模型等，但理论保证可能因应用范围的不同而有所差异。在图像处理的广阔天地里，压缩感知的应用如繁星点点，其中包括超分辨率图像修复、低剂量CT扫描和欠采样...
Compressive Sensing (CS) refers to a sensing scheme in which perceived signals are compressed at the time of sensing, which allows for reliable sampling at a lower rate than the Nyquist rate [92]. This is only plausible if the sensed signal is sparse and compressible, meaning a signal that...
压缩感知(压缩传感,Compressive Sensing)理论是近年来信号处理领域诞生的一种新的信号处理理论,由D. Donoho(美国科学院院士)、E. Candes(Ridgelet, Curvelet创始人)及华裔科学家T. Tao(2006年菲尔兹奖获得者)等人提出,自诞生之日起便极大地吸引了相关研究人员的关注。网站http://dsp.rice.edu/cs上可以获取大量相关...
Due to the capability of recovering the signal from a small set of samplings and the randomness in the acquisition process, compressive sensing (CS) has a vast prospect in dealing with these problems. In this paper, we propose a secure and packet loss-resistant real-time audio ...
Recently, a new image encryption technique based on compressive sensing (CS) has been proposed. CS allows the signal to be sampled at a much lower rate than the Nyquist- Shannon rate. Furthermore, the signal can be sampled and compressed in a single step using the sparsity of the signal ...