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。
For the advantage of wavelet transform in denoising and data compression, we choose wavelet transform to denoise and compress the data of Near-infrared spectra.
并根据小波变换在噪声滤除及数据压缩方面的优势，选取小波变换对光谱数据进行滤噪和初步压缩。
Aim The data adaptive scalar decomposition transform (SDT) and its application in data compression and denoising are studied.
目的研究常数分解变换法(SDT)及其在数据压缩和消噪上的应用。
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