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阐述了铜杆生产过程中信息采集系统的主要研究内容;概括了硬件的结构和选用的主要设备;阐述了上位机软件的主要模块及实现方法;系统采用面向对象的编程方法,界面友好,操作简单,功能完善;实际运行效果良好,具有较好的应用前景。 相似文献
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A weighting algorithm to determine the coordinates of the center of a Gaussian laser beam projected onto a matrix photodetector is considered. The influence of the internal noise of the photodetector, the maximum brightness of the signal at the beam maximum, and the beam radius on the precision of the algorithm is investigated. Recommendations on image processing are presented. 相似文献
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Hugh S. Fairman 《Color research and application》1995,20(1):44-49
In 1993, the American Society for Testing and Materials carried out a field test of newly calculated tristimulus weighting factors. These weighting factors had been calculated by a method proposed by Venable. the test also included a method of correction for bandpass dependence put forth by Stearns. the purpose of the trial was to assess the possible reduction in bandpass dependence introduced by each of these sets of weights. A large number of sets of spectral data were gathered from the cooperators in the field test. Results of integration by the various sets of tristimulus weighting factors were calculated. A total of 15 120 color differences were calculated and statistics were derived to test the probable error resulting from each method of correction. Errors attributable to bandpass dependence were on the order of a few tenths to as much as one CIELAB unit when uncorrected weight sets were used. These errors could be reduced to a few hundreths of a CIELAB unit, and in some cases to a few thousandths of a unit, by employing one correcting strategy or the other. an overall mix of strategies was ultimately chosen to minimize the bandpass dependence over the entire range of weight sets. Utilizing this mixed strategy, the median error introduced into 10-nm integration by bandpass dependence was only 0.004 CIELAB units. © 1995 John Wiley & Sons, Inc. 相似文献
5.
Centroid-based categorization is one of the most popular algorithms in text classification. In this approach, normalization is an important factor to improve performance of a centroid-based classifier when documents in text collection have quite different sizes and/or the numbers of documents in classes are unbalanced. In the past, most researchers applied document normalization, e.g., document-length normalization, while some consider a simple kind of class normalization, so-called class-length normalization, to solve the unbalancedness problem. However, there is no intensive work that clarifies how these normalizations affect classification performance and whether there are any other useful normalizations. The purpose of this paper is three folds; (1) to investigate the effectiveness of document- and class-length normalizations on several data sets, (2) to evaluate a number of commonly used normalization functions and (3) to introduce a new type of class normalization, called term-length normalization, which exploits term distribution among documents in the class. The experimental results show that a classifier with weight-merge-normalize approach (class-length normalization) performs better than one with weight-normalize-merge approach (document-length normalization) for the data sets with unbalanced numbers of documents in classes, and is quite competitive for those with balanced numbers of documents. For normalization functions, the normalization based on term weighting performs better than the others on average. For term-length normalization, it is useful for improving classification accuracy. The combination of term- and class-length normalizations outperforms pure class-length normalization and pure term-length normalization as well as unnormalization with the gaps of 4.29%, 11.50%, 30.09%, respectively. 相似文献
6.
文本索引词项相对权重计算方法与应用 总被引:4,自引:0,他引:4
文本索引词权重计算方法决定了文本分类的准确率。该文提出一种文本索引词项相对权重计算方法,即文本索引词项权重根据索引词项在该文本中的出现频率与在整个文本空间出现的平均频率之间的相对值进行计算。该方法能有效地提高索引词对文本内容识别的准确性。 相似文献
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《中国科学:信息科学(英文版)》2012,(8):1852-1859
To counter the problem of acquiring and processing huge amounts of data for synthetic aperture radar(SAR)using traditional sampling techniques,a method for sparse SAR imaging with an optimized azimuthal aperture is presented.The equivalence of an azimuthal match filter and synthetic array beamforming is shown so that optimization of the azimuthal sparse aperture can be converted to optimization of synthetic array beamforming.The azimuthal sparse aperture,which is composed of a middle aperture and symmetrical bilateral apertures,can be obtained by optimization algorithms(density weighting and simulated annealing algorithms,respectively).Furthermore,sparse imaging of spectrum analysis SAR based on the optimized sparse aperture is achieved by padding zeros at null samplings and using a non-uniform Taylor window.Compared with traditional sampling,this method has the advantages of reducing the amount of sampling and alleviating the computational burden with acceptable image quality.Unlike periodic sparse sampling,the proposed method exhibits no image ghosts.The results obtained from airborne measurements demonstrate the effectiveness and superiority of the proposed method. 相似文献
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针对三维模糊控制器规则多,结构复杂,难以实现的问题,提出了一种简化的三维模糊控制器。该方法是把三个输入量分别为偏差、偏差变化、偏差的偏差变化的一维模糊控制器加权融合实现简化的三维模糊控制器。并提出了根据不同类型的被控对象设置三个加权系数。加权系数具有粗调、细调和微调的作用,类似于传统PID调节器的比例、积分和微分,实现对系统静差的消除。 相似文献