稀疏表示技术与应用综述

Survey on Sparse Representation Techniques and Applications

近年来稀疏表示技术在信号处理、图像处理、目标识别、盲源分离等领域都有着突出的贡献.为了全面的了解和分析现有稀疏表示优化算法,首先回顾了稀疏表示技术的历史进程,简单描述了稀疏表示技术的原理,然后将稀疏表示优化算法分为贪心算法和约束算法以及其他算法三大类,具体分析了前两种类别算法的原理和特征,介绍了两类算法的代表算法,总结了算法的发展进程,并对贪心算法中的五种代表算法进行了简单对比,最后总结了稀疏表示技术在各个领域的应用情况,并针对存在的问题对未来的发展方向进行了分析,以期为研究者们提供有益参考.

Recently,sparse representation has made outstanding contributions to signal and image processing,target recognition and blind source separation.Firstly,the history and rationale of sparse representation are reviewed to summarize the existing sparse representation optimization algorithms.Secondly,those algorithms are divided into the greedy algorithm,the constraint algorithm and other algorithms.The basic principles and characteristics of the first two categories are elaborated respectively,and their representative algorithms and state-of-the-art applications are summarized as well.In addition,the five representative algorithms of the greedy algorithm are simply compared.Finally,the applications of sparse representation in various fields and its general outlook regarding existing problems are offered.