In parallel basis selection algorithms of sparse signal representation, there will be serious bias in amplitude estimation when frequency is not in grid.
在稀疏信号表示的并行选取字典算法中，当频率不在栅格点上时，对应的幅度估计可能会有很大的偏差。
The recognition problem is taken as one of classifying among multiple linear regression models, and sparse signal representation is used to solve this problem.
将识别问题看作是多个线性回归模型中的分类问题，并用稀疏表示理论解决这些问题。
Signal sparse representation or the optimal N-term approximation is one of the important problems, which is applied to many areas such as the data compression, denoising.
信号的稀疏表示或最佳n -项逼近是数据压缩、噪声抑制等众多应用中的一个重要问题。
Wavelet thresholding technology is using the sparse property of wavelet representation and diagonal filter for signal denoising . This method is nearly optimal in many signal spaces.
小波阈值降噪技术利用小波变换表示信号的稀疏性质，使用对角形式的阈值滤波器达到信号降噪的目的，这个方法在很多信号空间上是近似最优的。
As a novel signal processing method, adaptive sparse representation has a merit of representing signal flexibly and can de-noise effectively when maintaining features of targets.
自适应稀疏表示，作为一种新的信号处理方法，具有表达信号灵活的特点，能够在保持目标特征的同时有效地去除噪声。
As a novel signal processing method, adaptive sparse representation has a merit of representing signal flexibly and can de-noise effectively when maintaining features of targets.
自适应稀疏表示，作为一种新的信号处理方法，具有表达信号灵活的特点，能够在保持目标特征的同时有效地去除噪声。
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