瑞利信道仿真（多普勒经典谱）

本文档包含的是EPRI-36节点系统算例的摘要说明有关基础数据库中各系统元件的定义和组织方法可参见基础数据库用户手册目录1 系统单线图2 数据方案定义3 潮流计算4 暂态稳定计算5 短路计算

photoshop CC 2018 64位可用dds64位插件，兼容所有PS64位使用

样条插值法实现时间配准，MATLAB仿真

请把本软件放到foxtable目录,如:E:foxtableTrialfoxtable 2012 最新破解版,未修改原文件,理论上支持所有版本,只要把本工具放到foxtable目录即可.长期使用请购买正版软件,所以设定本软件使用30天,(联网验证).破解原理很简单,一不小心就会发现!

这是楼主自己学习过程中整理的机器学习实战全书的全部源代码，书上的代码有很多不能运行的，楼主把全部代码重新进行的书写，所有代码在python3上均通过运行，没有任何bug。全网唯一一个可以在python3下完美运行的代码！有兴趣的可加群907701753一起学习机器学习的知识

有关遗传编程引用的最多的资料，很基础。对遗传编程进行了详细的介绍。

STM32F207的U盘升级程序，USB的通讯模式为USB_HOST主机模式。工作方式：将带有F207_Template.bin升级程序（名称可自行更改）的U盘插在控制板上；复位控制板自动升级并跳转执行APP程序；如若没有插USB或没有可升级文件，一秒后自动跳转，执行APP程序；

在特征波长选取方面有一些创新，可以作为参考。在特征波长选取方面有一些创新，可以作为参考。（基于高光谱成像的蓝莓内部品质检测特征波长选择方法研究古文君1 ，田有文 1* ，张芳1 ，赖兴涛 1 ，何宽1 ，姚萍1 ，刘博林 2）586-482016620010~15mm0.8~2.3g。fone3:(InSpector V10E, Spectral InFinland)1392pix×1040pixCCDL CCD2(IGV-B141OM, IMPERX Incorporated, USA), 150W1. CCD Camera; 2.Spectrometer; 3.Shot; 4. Light source; 5. Samples(3900 Illuminatior, Illumination Tech6.Translationplatform7.Lightsourcecontroller;8.computernologies inc.,USA)、(IRCP0076-19. Translation platform controllerCOM,)、(120cm×50cmx(DELL VoStro 5560D-1528Figure 1 Schematic diagram of hyperspectral imagingcmsystem400~1000nm,4722.8nmRRGY-4(10mm)(DBR45(successive projections algorithm, SPA(stepwise multiple linear regression, SMLR)(SPA)(SMLR)SPASPASMLRSPA-SPA、SMLR_SMLR、SPA- SMLRSMLR-SPA21994-2018ChinaAcadcmicJournalElcctronicPublishingHousc.Allrightsrcscrved.http://www.cnki.nct5871.6BP(error back propagation)BP17(correlation coeffiient of calibration, Re)(root mean square error of calibration set, RMSEC)correlation coeffiient of pre-diction, Rp)(root mean square error of prediction set, RMSEP)ENVI 4.8(Research System Inc, ), MATLAB 2014a(The Math Works Inc)、TheUnscrambler9.7、 Excel2010(Ⅵ icrosoftdgle banddWcvef.BP models for soluble solidsThe selected characteristic wavelengthCurve of relative reflectanceExtract the region of interescontent and firmness prediction2figure 2 Flow chart of data processing280mm,68ms,28mm·s-。99%202.2600nm600nm2b2c)21994-2018ChinaAcadcmicJournalElcctronicPublishingHousc.Allrightsrcscrved.http://www.cnki.nct5884823(2f)BPSavitzky-Golasavitzky -golayTable 1 The effect of different spectra preprocessingCalibration setPredictioSpectrum typeRMSECRMSEPOriginal spcctrum0.933/0.9230.3510.4040.9200.9100.508/0.319MSCThe spectrum after MSC processing0.940/0.9450.56lO.3120.9190.9320.516/0.282SNThe spectrum after SNV processin0.93709340.60210.24309220.9010.6320.462Savitzky-golayThe spectrum after Savitzky-Golay processing 0.955/0.9550.3240.2410.951/0.9490.400/0.2782.5SPA-SPA SMLRSMLR SPA-SMLR SMLR-SPASPA-SPASPASavitzky-GolaySPATable 2 The results of multi-stage characteristic wavelength selection methodnmCharacteristie wavelength selection methodSPA-SPA452,455,470,482,490,785,893,912,921,942,950455,470,482,785,893.912SMLR-SMLR457,508,516,534,543,51,556,568,712,720.774,778508,534,543,712,720,774SPA-SMLR452,455,470,482,490,785,893,912,921,942,950452,470,482,490,893,912SMLR-SPA457,508,516,534,543,551,556,568,712,720,774,78534,7202.6Savilzky-gola(FS)392SPA-SPASMLR-SMLRSMLR-SMLRSMLR-SPABPBP0.001500021994-2018ChinaAcadcmicJournalElcctronicPublishingHousc.Allrightsrcscrved.http://www.cnki.nct589BPBPSPA-SPARp RMseP0.9520.391°Brix,RpRMSEP0.9530.234BrixTable 3 Detection results of soluble solid content and firmness of blueberry based on different multi-stagecharacteristic wavelength selection methodsCalibration setPrediction setCharacteristic selection method Wavelength numberRMSECRMSEP3929550.9550.324/0.2410.9510.9490.400/0.278SPA-SPA0.9590.9560.3180.1530.9520.9530.391/0.234SMLR-SMLR0.9560.9340.414/0.243912109020.559/0.349SPA SMLR0.828/0.8581.3670.58582208091.440/0.719SMLR- SPA20.958/0.9360.402/0.3359320.9280.435/0,4041387nm1229nm91.5%BPRRMSEP0.904215.163lBP3Rv0.84V0.94Rv0.83,SEV0.63。400-1000nmSavitzky-GolayBPSPA-SPASPA-SPA21994-2018ChinaAcadcmicJournalElcctronicPublishingHousc.Allrightsrcscrved.http://www.cnki.nct59048[1 KADER F,ROVEL. B Fractionation and identification of the phenolic compounds of highbush blueberries(Vaccinium corymbosumLUJ].Food Chemistry, 1996,55(1): 35-40「J,2012,33(1):340-342,2017,38(2):301-305.[4 MENDOZA F, LU R, ARIANA D,et al. Integrated spectral and image analysis of hyperspectral scattering data for prediction ofple [ruil firmness and soluble solids conlenl[J] Poslharvesl Biology and Technology, 2011, 62(2: 149-160[5 SUN M J, ZHANG D, LIU L,et al. How to predict the sugariness and hardness of melons a near-infrared [J]. Food Chemistry,2017,218(3:413-42116 SIEDLISKA A, BARANOWSKI P, MAZUREK W, ct al. Classification models of bruise and cultivar detection on the basis of hy-perspectral imaging data[J]. Computers and Electronics in Agriculture, 2014, 106: 66-74[7 LIU D, SUN D W, ZENG X N, el al. Recenl aDvances in wavelength seleclion lechniques for hyperspectral image processing inthe food industry[J]. Food Bioprocess Technol, 2014, 7: 307-323[8 ZHANG C, GUO C T, LIU F,et al. Hyperspectral imaging analysis for ripeness evaluation of strawberry with support vector ma-chine[j] Journal of Food Engincering, 2016, 179: 11-18[9J,2016,47(5:634-6402009,29(:1611-1615201536(12)171-17612]J,2012,32(11:3093309[13] LI B C, HOU B L, ZHANG D W,et al. Pears characteristics (soluble solids content and firmness prediction, varieties) testingInethods based on visible-near infrared hyperspecTral imaging[J]. OpLik, 2016, 127: 2624-2630[14] FAN S X, ZHANG B H,LI J B, et al. Prediction of soluble solids content of apple using the combination of spectra and textural features of hyperspectral reflectance imaging data[J. Postharvest Biology and Technology, 2016, 121: 51-61[15 RAJKUMAR P, WANG N,EIMASRY G, et al.Studies on banana fruit quality and maturity stages using hyperspectral imaging[ JIJournal of Food Engineering 2012, 108: 194-200,2015,36(16):10172015,35(8:2297-2302[18]WANG N,2007,23(2:151-155.「192008,39(5):91-9320」201536(10:70-74.[21] WU D, SUN D WAdvanced applications of hyperspectral imaging technology for food quality and safety analysis and assess-ment a review part T[J]. Innovative Food Science and Emerging Technologies, 2013, 19(4): 1-14J2014,35(8:57-61BP,2012.124」13,44(2):142-146.25],201523(6:1530-1537M011:41-48.[27,2013,24(10:1972-19762010,30(10):2729-2733?1994-2018ChinaAcadcmicJournaleLcctronicPublishingHousc.Allrightsreservedhttp://www.cnki.nct

讲述关于网络安全相关书籍，对于向我这样想了解黑客到底如何利用网站漏洞对站点进行攻击，有很多丰富的实例。很适合互联网的开发者，按照不同的漏洞类型进行了分类。 针对每个漏洞类型，阐述了基本概念、业界的惨痛教训、如何防范的基本技巧，不局限于某种语言，某种浏览器。同时对于互联网公司进行安全方面的维护和运营也阐述了相关的可以使用的经验。

用python学习数字信号处理 digital signal processing