sparse signal representation 稀疏信号表示
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。
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。
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。
应用推荐