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	On greedy randomized coordinate descent methods for solving large linear least-squares problems 期刊论文 OAI收割 NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, 2019, 卷号: 26, 期号: 4, 页码: 15 作者: Bai, Zhong-Zhi; Wu, Wen-Ting \| 收藏 \| 浏览/下载：65/0 \| 提交时间：2020/01/10 convergence property coordinate descent method linear least-squares problem randomized iteration
	Gray level correction algorithm of LED display panel based on least squares approximation (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China 作者: Sun Z.-Y. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 Aiming at the problem that the linear characteristic of LED display panel is not compatible with the non-linear characteristic of image data this leads to appear the large deviation during grayscale rendition the gray level correction algorithm based on least squares approximation is provided. First the necessity of gray level correction is analyzed. Then the gray level correction algorithm model is constructed according to the principle of latest squares approximation. Next realization steps are described in accordance with this constructed algorithm model. Finally this algorithm is implemented in a LED display panel whose resolution is 128128. Experimental results show that this algorithm is able to reduce the deviation obviously during grayscale rendition and the problem of gray level deformation can be resolved perfectly because the linear relation between image data after correcting and gray level is good which satisfies the linear characteristic of LED display panel. 2010 IEEE.
	The study on the near infrared spectrum technology of sauce component analysis (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li S.; Wang C.; Chen X.; Chen X.; Chen X. 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/03/25 The author Shangyu Li engages in supervising and inspecting the quality of products. In soy sauce manufacturing quality control of intermediate and final products by many components such as total nitrogen saltless soluble solids nitrogen of amino acids and total acid is demanded. Wet chemistry analytical methods need much labor and time for these analyses. In order to compensate for this problem we used near infrared spectroscopy technology to measure the chemical-composition of soy sauce. In the course of the work a certain amount of soy sauce was collected and was analyzed by wet chemistry analytical methods. The soy sauce was scanned by two kinds of the spectrometer the Fourier Transform near infrared spectrometer (FT-NIR spectrometer) and the filter near infrared spectroscopy analyzer. The near infrared spectroscopy of soy sauce was calibrated with the components of wet chemistry methods by partial least squares regression and stepwise multiple linear regression. The contents of saltless soluble solids total nitrogen total acid and nitrogen of amino acids were predicted by cross validation. The results are compared with the wet chemistry analytical methods. The correlation coefficient and root-mean-square error of prediction (RMSEP) in the better prediction run were found to be 0.961 and 0.206 for total nitrogen 0.913 and 1.215 for saltless soluble solids 0.855 and 0.199 nitrogen of amino acids 0.966 and 0.231 for total acid respectively. The results presented here demonstrate that the NIR spectroscopy technology is promising for fast and reliable determination of major components of soy sauce.