sparse signal representation

基本解釋

It first de-noises by employing sparse signal representation, and then restores images by using L-R algorithm.
首先采用稀疏信號(hào)表示的方法進(jìn)行去噪，然后使用L-R算法進(jìn)行圖像恢復(fù)。
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As sparse signal representation has greater flexibility in matching structure in the signal, it can be used in ISAR imaging.
稀疏信號(hào)表示在與信號(hào)結(jié)構(gòu)匹配方面具有很大的靈活性，可以用于逆合成孔徑雷達(dá)（ISAR）成像。
The recognition problem is taken as one of classifying among multiple linear regression models, and sparse signal representation is used to solve this problem.
將識(shí)別問題看作是多個(gè)線性回歸模型中的分類問題，并用稀疏表示理論解決這些問題。