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针对红外光谱常常遭受到谱带重叠和随机噪声的问题,本文提出了一种基于自适应Tikhonov正则化约束的红外光谱信号重构方法。该方法能有效的抑制平坦区域的噪声和保存谱带的结构信息,不同光谱区域的结构信息可以通过自适应项来区分。本文所建立的数学模型能有效通过交替最小值最优方法求解。对比实验结果表明,该方法能有效的分裂重叠的谱带并抑制Poisson噪声。重构的红外光谱易于提取光谱特征并解释未知的药品成分。
Aiming at the problem that the infrared spectrum often suffers from band overlap and random noise, a new method of signal reconstruction based on the adaptive Tikhonov regularization is proposed in this paper. This method can effectively suppress the noise in the flat area and preserve the structural information of the bands. The structural information of different spectral regions can be distinguished by the adaptive term. The mathematical model established in this paper can be effectively solved by the alternative minimum optimal method. The experimental results show that this method can effectively split the overlapping bands and suppress Poisson noise. Reconstructed infrared spectroscopy facilitates the extraction of spectral features and interpretation of unknown pharmaceutical ingredients.