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搜索结果: 1-10 共查到Matching Pursuit相关记录10条 . 查询时间(0.031 秒)
Finding the sparsest solution to underdetermined systems of linear equations y = Φx is NP-hard in general. We show here that for systems with ‘typical’/‘random’ Φ, a good approximation to the sparse...
Hyperspectral images contain rich and fine spectral information, an improvement of land use/cover classification accuracy is expected from the use of such images. However, the classification methods...
In this paper, we present coherence-based performance guarantees of Orthogonal Matching Pursuit (OMP) for both support recovery and signal reconstruction of sparse signals when the measurements are co...
Many models for sparse regression typically assume that the covariates are known completely, and without noise. Particularly in high-dimensional applications, this is often not the case. This paper de...
本文研究了心电信号在身份识别中的应用,提出了基于快速傅里叶变换的匹配追踪心电特征提取算法。在预处理阶段,对心电信号进行消噪、标准化和质量检测等预处理,有效去除了心电信号中的噪声和心率变异所带来的干扰。特征提取阶段,对心电模板进行基于快速傅里叶变换的匹配追踪稀疏分解,原子的时频参数和投影值作为特征参数,然后构建支持向量机分类器,实现了身份识别。最后利用MIT-BIH的ST Change、PTB、QT...
In this paper, we consider the problem of compressed sensing where the goal is to recover almost all the sparse vectors using a small number of fixed linear measurements. For this problem, we propose ...
The success of ultrasonic nondestructive testing technology depends not only on the generation and measurement of the desired waveform, but also on the signal processing of the measured waves.
The success of ultrasonic nondestructive testing technology depends not only on the generation and measurement of the desired waveform, but also on the signal processing of the measured waves.
Orthogonal Matching Pursuit (OMP) has long been considered a powerful heuristic for attacking compressive sensing problems; however, its theoretical development is, unfortunately, somewhat lacking. Th...
Compressed sensing is a recently developing area which is interested in reconstruction of sparse signals acquired in reduced dimensions. Acquiring the data with a small number of samples makes the rec...

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