基于改进匹配追踪算法的化爆地震波信号时频特征提取

通过化爆地震波信号的时频分析可以获取丰富的地下岩层信息,为进一步的化爆地震波特性研究提供支撑。本文中利用爆炸地震波信号的非平稳随机特性,提出一种改进的匹配追踪算法(matching pursuits),该方法能更有效地获取化爆地震波信号的时频信息。该算法首先对地震波信号进行Hibert变换,将其转换成复数信号,获得爆炸地震波信号瞬时频率相位参数,再进行子波分解,从而显著提高了匹配追踪算法的运算速率;用分解后的信号计算其魏格纳威利分布(Wigner Ville distribution),有效地消除了交叉干扰项的影响。将该方法用于实测地震波信号的时频分析,获得了分辨率较高的时频分布图,且运算速率大大提高。

     

Non-Iterative Regularized reconstruction Algorithm for Non-CartesiAn MRI: NIRVANA

We introduce a novel noniterative algorithm for the fast and accurate reconstruction of nonuniformly sampled MRI data. The proposed scheme derives the reconstructed image as the nonuniform inverse Fourier transform of a compensated dataset. We derive each sample in the compensated dataset as a weighted linear combination of a few measured k-space samples. The specific k-space samples and the weights involved in the linear combination are derived such that the reconstruction error is minimized. The computational complexity of the proposed scheme is comparable to that of gridding. At the same time, it provides significantly improved accuracy and is considerably more robust to noise and undersampling. The advantages of the proposed scheme makes it ideally suited for the fast reconstruction of large multidimensional datasets, which routinely arise in applications such as f-MRI and MR spectroscopy. The comparisons with state-of-the-art algorithms on numerical phantoms and MRI data clearly demonstrate the performance improvement.     

基于匹配追踪算法的激波信号特征提取

针对时域重叠、噪声混合等情况下从多弹头激波信号中提取时延特征参数问题,利用匹配追踪(Matching pursuits,MP)算法的自适应分解特性对激波混合信号进行特征提取,并针对运行时间长和内存占用大等问题提出"粗提取—精提取"两步改进算法,通过"粗提取"获得各个激波信号的长度,触发位置等先验知识,利用"分库"、"总库"思想重构过完备原子库进行精提取。仿真结果表明,该改进算法不仅能以较高精度提取时延特征参数,而且能有效提高提取速度和减小内存占用。     

基于粒子群优化的核匹配追踪目标识别

提出了一种基于粒子群优化的用于目标识别的核匹配追踪算法.该算法用粒子群优化算法在基函数字典中选择最优的基函数,大大降低了基匹配追踪算法的计算复杂度.通过与标准核匹配追踪算法及基于遗传算法的核匹配追踪算法对UCI数据集及纹理图像的识别试验表明,核匹配追踪算法优良的分类性能以及粒子群优化算法高效的全局搜索能力使新算法能有效识别目标数据.