| 迭代预测正交匹配追踪算法 |
| |
| 引用本文： | 刘学文,肖嵩,王玲,薛晓.迭代预测正交匹配追踪算法[J].信号处理,2017,33(2):178-184. |
| |
| 作者姓名： | 刘学文 肖嵩 王玲 薛晓 |
| |
| 作者单位： | 西安电子科技大学ISN国家重点实验室 |
| |
| 基金项目： | 国家自然科学基金项目（61372069）；高等学校学科创新引智计划（111计划）资助项目（B08038）；河南省高等学校重点科研项目计划项目（15A510002）
|
| |
| 摘 要： | 正交匹配追踪系列算法中，每次迭代在原子库中选择和残差匹配的多个原子是主流的改进方向，但对多原子的选择标准却鲜有深入研究，一般是选择原子库中与残差相关系数中最大的K个原子，或者选择所有大于某一阈值的原子。本文以正交匹配追踪算法为原型，运用统计学方法，研究了相邻两次迭代中与残差相关系数最大的原子之间的关系，得出了其相关系数具有区间性的结论，这对一次迭代选择多个原子具有指导意义。该结论可以支撑对下一步迭代中的原子进行高概率预测。基于此，本文提出了迭代预测正交匹配追踪算法，实验结果表明，相对于其他匹配追踪算法，其在保证重构精度未降低的情况下，耗时有较大幅度降低。
|
| 关 键 词： | 匹配追踪 稀疏重构 测量矩阵 压缩感知 |
| 收稿时间： | 2016-05-18 |
Iteration forecast orthogonal matching pursuit algorithm |
| |
| Affiliation: | ISN National Lab,Xidian University |
| |
| Abstract: | To improve orthogonal matching pursuit algorithm, the mainstream direction is to select several atoms which is matching the residual in each iteration.However, there is few in-depth research about selection criteria of atoms.Generally, it is to select K atoms in atom library which have largest correlation coefficients with residual, or select all atoms whose correlation coefficients with residual are greater than a certain threshold. Based on orthogonal matching pursuit algorithm,by statistical method, this paper researches the relationship between the two atoms of two adjacent iterations, and concludes that their correlation coefficients with the earlier residual have interval feature, which has a guiding significance on choosing more atoms in one iteration. And it can support the prediction of the atom in the next iteration with high probability. Based on this, this paper presents the iteration forecast orthogonal matching pursuit algorithm. Experimental results show that, compared with other matching pursuit algorithm, its time-consuming is greatly reduced while the reconstruction accuracy has not significantly reduced. |
| |
| Keywords: | |
|
| 点击此处可从《信号处理》浏览原始摘要信息 |
|
点击此处可从《信号处理》下载全文 |
|
