登录
首页 » matlab » Microlithography

Microlithography

于 2020-12-01 发布 文件大小:272KB
0 213
下载积分: 1 下载次数: 4

代码说明:

  用于duv光刻掩膜优化算法的模型,包含部分相干光照明,光刻胶分层模型,具体考虑了瞳孔放大系数,以及电磁波的畸变等因素。(The model for DUV photolithography optimization algorithm, including partially coherent light illumination and photoresist stratification model, takes into account the factor of pupil magnification and electromagnetic wave distortion.)

文件列表:

Microlithography\@Litho\computeImage.m, 7246 , 2015-01-19
Microlithography\@Litho\computePixelMaskSpectrum.m, 183 , 2017-09-07
Microlithography\@Litho\computeSource.m, 1749 , 2017-09-14
Microlithography\@Litho\computeSystem.m, 1000 , 2017-10-27
Microlithography\@Litho\Litho.m, 3174 , 2017-10-27
Microlithography\addPathToKernel.m, 84 , 2016-10-13
Microlithography\ComputeEPE.m, 656 , 2017-05-25
Microlithography\computeHp.m, 1938 , 2017-01-04
Microlithography\computeHpSD.m, 1690 , 2017-08-27
Microlithography\computeHpSD_1.m, 1768 , 2017-06-15
Microlithography\computeJCC.m, 2420 , 2017-06-26
Microlithography\computeVectorM.m, 1598 , 2017-06-15
Microlithography\computeVectorM_1.m, 1663 , 2017-06-15
Microlithography\computeVectorT.m, 681 , 2017-06-15
Microlithography\computeVectorT_1.m, 744 , 2017-09-13
Microlithography\conv2mtx_same.m, 1534 , 2013-08-20
Microlithography\ConvInFreq.m, 474 , 2017-03-31
Microlithography\CSTIC2017PrepImage.m, 460 , 2016-12-14
Microlithography\evolve_normal_ENO2_modified.m, 1582 , 2017-06-14
Microlithography\FindSmallestTwoExpo.m, 103 , 2016-10-21
Microlithography\GetZernikeXYPoly.m, 3260 , 2017-10-27
Microlithography\gssLitho.m, 1675 , 2017-05-19
Microlithography\gssMO.m, 2008 , 2017-06-13
Microlithography\imageEPS.m, 493 , 2017-08-24
Microlithography\images\img11.bmp, 5690 , 2017-11-04
Microlithography\images\img12.bmp, 5690 , 2017-11-04
Microlithography\images\img13.bmp, 5690 , 2017-11-04
Microlithography\images\img14.bmp, 5690 , 2017-11-04
Microlithography\images\img15.bmp, 5690 , 2017-11-04
Microlithography\images\img9.bmp, 5690 , 2017-09-08
Microlithography\images\img9c.bmp, 1678 , 2017-09-08
Microlithography\images\resm11.bmp, 67898 , 2017-11-08
Microlithography\images\resm12.bmp, 67898 , 2017-11-08
Microlithography\images\resm13.bmp, 67898 , 2017-11-08
Microlithography\images\resm14.bmp, 67898 , 2017-11-08
Microlithography\images\resm15.bmp, 67898 , 2017-11-08
Microlithography\images\ress11.bmp, 2006 , 2017-11-08
Microlithography\images\ress12.bmp, 2006 , 2017-11-08
Microlithography\images\ress13.bmp, 2006 , 2017-11-08
Microlithography\images\ress14.bmp, 2006 , 2017-11-08
Microlithography\images\ress15.bmp, 2006 , 2017-11-08
Microlithography\images\resultphoto.m, 1393 , 2017-11-08
Microlithography\ImageVelocity.m, 4468 , 2017-06-02
Microlithography\LithoFconju.m, 4514 , 2017-06-18
Microlithography\main_CalcVectorAerial.m, 2919 , 2016-10-15
Microlithography\maskContour.m, 282 , 2017-05-25
Microlithography\Partially\ImageVelocity.m, 1858 , 2017-09-14
Microlithography\Partially\LithoMOconjuP.m, 4025 , 2017-09-08
Microlithography\Partially\main_Litho.m, 1559 , 2017-09-08
Microlithography\PPPPPpengfei_test1.m, 71 , 2017-09-08
Microlithography\PrepSystem.m, 1808 , 2017-06-24
Microlithography\PrepSystemMO.m, 1615 , 2017-08-27
Microlithography\PrepSystemMOconju.m, 1632 , 2017-06-15
Microlithography\rotate90Hp.m, 788 , 2016-10-23
Microlithography\sigmoid_syj.m, 622 , 2009-03-11
Microlithography\SOcomputeT.m, 918 , 2017-06-26
Microlithography\SOconju.m, 4712 , 2017-06-26
Microlithography\source_ADDA.m, 3236 , 2017-09-15
Microlithography\source_ADG.m, 3625 , 2017-09-17
Microlithography\source_RMS.m, 3061 , 2017-09-14
Microlithography\SOVelocity.m, 662 , 2017-05-18
Microlithography\SOVelocityNW.m, 954 , 2017-05-21
Microlithography\Stratifeid\@Layer\computeM.m, 361 , 2017-09-06
Microlithography\Stratifeid\@Layer\Layer.m, 776 , 2017-09-12
Microlithography\Stratifeid\@stack\computemsp.m, 603 , 2017-09-06
Microlithography\Stratifeid\@stack\computeRT.m, 815 , 2017-09-06
Microlithography\Stratifeid\@stack\multiple.asv, 503 , 2017-09-06
Microlithography\Stratifeid\@stack\stack.m, 684 , 2017-09-06
Microlithography\Stratifeid\computeHp.m, 8470 , 2017-09-14
Microlithography\Stratifeid\ED.asv, 1597 , 2017-10-27
Microlithography\Stratifeid\ED.m, 1613 , 2018-02-14
Microlithography\Stratifeid\ImageVelocity.m, 5055 , 2017-09-14
Microlithography\Stratifeid\iteration_get.m, 1989 , 2017-09-19
Microlithography\Stratifeid\Mask_inverse.m, 4141 , 2017-09-19
Microlithography\Stratifeid\multiple.m, 440 , 2017-09-06
Microlithography\Stratifeid\PrepSystem.m, 1993 , 2018-01-05
Microlithography\test.m, 3429 , 2016-10-17
Microlithography\testConv.m, 463 , 2017-04-25
Microlithography\testLitho.m, 3473 , 2017-08-26
Microlithography\testLithoF.m, 3919 , 2017-08-21
Microlithography\testLithoFconju.m, 3847 , 2017-05-31
Microlithography\testSO.m, 3197 , 2017-05-25
Microlithography\testSOconju.m, 3263 , 2017-06-19
Microlithography\testSOnarrow.m, 3180 , 2017-05-19
Microlithography\testSOnarrowConju.m, 3299 , 2017-06-19
Microlithography\test_ILT.m, 3255 , 2016-10-20
Microlithography\ttest.m, 654 , 2017-04-01
Microlithography\VectorModelGk.m, 1825 , 2017-05-12
Microlithography\VectorModelImage.m, 2935 , 2017-01-04
Microlithography\VectorModelImageSD.m, 1612 , 2016-10-27
Microlithography\VectorModelImageSO.m, 793 , 2017-06-16
Microlithography\VectorModelImageTest.m, 2265 , 2017-03-31
Microlithography\VectorModelVelocity.m, 3277 , 2017-01-04
Microlithography\VectorModelVelocitySD.m, 1553 , 2017-05-25
Microlithography\VectorModelVelocityTest.m, 3430 , 2017-05-24
Microlithography\VnIntermediate.m, 742 , 2016-10-23
Microlithography\Stratifeid\@Layer, 0 , 2018-04-14
Microlithography\Stratifeid\@stack, 0 , 2018-04-14
Microlithography\Stratifeid\data, 0 , 2018-04-14
Microlithography\@Litho, 0 , 2018-04-14

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • VB6.0开机启动管理程序
    VB6.0开机启动管理程序,Windows随系统一起运行的启动项管理程序,初次运行本程序,为做首次运行准备,比如备份Windows注册表,在操作失误时可恢复。本程序对加入到开机启动项中的项目进行管理和查看,可删除这些启动项,并显示启动项所属的程序名称。
    2022-03-23 17:47:00下载
    积分:1
  • Rossler
    混沌吸引子的产生程序,演示了混沌吸引子的奇妙变化,适合初学者。(Chaotic attractor of the generation process, to demonstrate chaotic attractor of the wonderful changes, suitable for beginners.)
    2007-10-09 16:35:01下载
    积分:1
  • 关于AD9833开发的论文,原理应用写的都很好,还指出实际调试中容易出现的问题,很不错,大家参考参考!...
    关于AD9833开发的论文,原理应用写的都很好,还指出实际调试中容易出现的问题,很不错,大家参考参考!-AD9833 developed on paper, the principle of application is well written, but also pointed out that the actual commissioning of easier problems, it is true that your information!
    2023-04-15 17:25:03下载
    积分:1
  • 售楼管理系统 比较好的售楼管理系统源码毕业的同学
    售楼管理系统 比较好的售楼管理系统源码毕业的同学-Sales management system for better sales management system for school-leavers source
    2022-03-23 15:38:16下载
    积分:1
  • ceemdan1
    CEEMDAN是对EEMD的改进算法,EEMD算法通过加入噪声来减小EMD的模态效应,CEEMDAN算法通过加入自适应的噪声来进一步减小模态效应,而且具有更好的收敛性。(CEEMDAN is an improved algorithm of EEMD, the EEMD algorithm by adding noise to reduce modal effects of EMD, CEEMDAN algorithm by adding noise adaptive mode to further reduce the effect, but also has better convergence.)
    2017-09-19 10:17:51下载
    积分:1
  • test1.part02
    说明:  这是一个基于pocketsphinx的例子程序,已经在andtoid studio编译成功,并能识别简单的词汇。这是第二部分(This is an example program based on pocketsphinx, which has been successfully compiled in andtoid studio and can recognize simple words.this is the 2nd part)
    2020-06-21 19:40:01下载
    积分:1
  • 高程注记自动移位
    这是用来调压盖的,喜欢的可以拿去用用,后面是多余的话(This is for the surge tank cover, like can take to use, followed by superfluous words)
    2018-06-08 09:51:53下载
    积分:1
  • 滤波法
    说明:  A、名称:限幅滤波法(又称程序判断滤波法) B、方法: 根据经验判断,确定两次采样允许的最大偏差值(设为A), 每次检测到新值时判断: 如果本次值与上次值之差A,则本次值无效,放弃本次值,用上次值代替本次值。 C、优点: 能有效克服因偶然因素引起的脉冲干扰。 D、缺点: 无法抑制那种周期性的干扰。 平滑度差。(A. Name: Limited filter method (also known as program judgement filter method) B. Method: Based on experience, the maximum allowable deviation (set to A) of two sampling times is determined. Judge each time a new value is detected: If the difference between the current value and the previous value is
    2020-06-24 18:20:01下载
    积分:1
  • Microsoft MS-DOS 6.22 [Virtual PC VHD]
    dos os for virtual m
    2018-01-28 07:17:18下载
    积分:1
  • tvpvar_m
    说明:  TVP-VAR模型matlab代码,新手小白可参考,自学入门必备,代码来源Nakajima文章。(TVP-VAR model matlab code, novice little white can refer to, self learning entry necessary, code source Nakajima article.)
    2021-04-10 16:18:59下载
    积分:1
  • 696518资源总数
  • 106215会员总数
  • 5今日下载