根据Ozaktas1996年的文章《DigitalComputationoftheFractionalFourierTransform》编写的分数阶傅里叶变换程序。

TheJupyterNotebookallowsyoutocreateandsharedocumentsthatcontainlivecode,equations,visualizations,andexplanatorytext.TheJupyterNotebooksystemisextensivelyusedindomainssuchasdatacleaningandtransformation,numericalsimulation,statisticalmodeling,andmachinelearning.LearningJupyter5willhelpyougettogripswithinteractivecomputingusingreal-worldexamples.ThebookstartswithadetailedoverviewoftheJupyterNotebooksystemanditsinstallationindifferentenvironments.Next,youwilllearntointegratetheJupytersystemwithdifferentprogramminglanguagessuchasR,Python,Java,JavaScript,andJulia,andexplorevariousversionsandpackagesthatarecompatiblewiththeNotebooksystem.Movingahead,youwillmasterinteractivewidgetsandnamespacesandworkwithJupyterinamulti-usermode.Bytheendofthisbook,youwillhaveusedJupyterwithabigdatasetandbeabletoapplyallthefunctionalitiesyou’veexploredthroughoutthebook.YouwillalsohavelearnedallabouttheJupyterNotebookandbeabletostartperformingdatatransformation,numericalsimulation,anddatavisualization.

定义基于左手坐标系的三维数据类型，包括：点（Vector4）、变换矩阵（TranformMatrix）定义三维模型数据表示：顶点（Vertex）、Camera和三角形（Triangle）；
实现三维数据操作方法，包括：矢量的加（+）、减（-）、点积（DotProduct）和叉积（CrossProduct）；
矢量和矩阵的乘积（点和向量的坐标变换），实现完整坐标变换算法，能将三维空间中的点经过WorldTransform、ViewTransform、ProjectTransform、ViewPortTransform后显示于屏幕上；
实现三角形的线框显示，采用DDA算法；
实现Phong光照算法和Gouraud着色，支持环境光（AmbientLight）和一个直射光（DirectionalLight），实现纹理印射的透视矫正，显示多个三角形组成的物体；
实现裁剪算法，实现一个灵活的Camera。

MicrosoftExcel2019PivotTableDataCrunching(BusinessSkills)By作者:BillJelen–MichaelAlexanderISBN-10书号:1509307249ISBN-13书号:9781509307241Edition版本:1出版日期:2019-01-18pages页数:(512)RenownedExcelexpertsBillJelen(MrExcel)andMichaelAlexanderhelpyoucrunchdatafromanysourcewithExcel2019pivottables.UseExcel2019pivottablesandpivotchartstoproducepowerful,dynamicreportsinminutesinsteadofhours,totakecontrolofyourdataandyourbusiness.Evenifyou’venevercreatedapivottablebefore,thisbookwillhelpyouleveragealltheirremarkableflexibilityandanalyticalpower–includingvaluableimprovementsinExcel2019andExcelinOffice365.Drawingonmorethan45combinedyearsofExcelexperience,BillJelenandMichaelAlexanderofferpractical“recipes”forsolvingrealbusinessproblems,helpyouavoidcommonmistakes,andpresenttipsandtricksyou’llfindnowhereelse.Byreadingthisbook,youwill:Mastereasy,powerfulwaystocreate,customize,change,andcontrolpivottablesControlallfuturepivottablesusingnewpivottabledefaultsTransformhugedatasetsintoclearsummaryreportsInstantlyhighlightyourmostprofitablecustomers,products,orregionsUsePowerQuerytoquicklyimport,clean,shape,andanalyzedisparatedatasourcesBuildgeographicalpivottableswith3DMapConstructandsharestate-of-the-artdynamicdashboardsRevampanalysesontheflybydragginganddroppingfieldsBuilddynamicself-servicereportingsystemsShareyourpivottableswithcolleaguesCreatedatamashupsusingthefullPowerPivotcapabilitiesofExcel2019andExcelinOffice365AutomatepivottableswithmacrosandVBASavetimebyadaptingreportswithGetPivotDataDiscovertoday’smostusefulpivottabletipsandshortcuts

function[PSNR,y_est]=BM3D(y,z,sigma,profile,print_to_screen,N2,N2_wiener,Ns,Ns_wiener,tau_match)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%BM3DisanalgorithmforattenuationofadditivewhiteGaussiannoisefrom%grayscaleimages.Thisalgorithmreproducestheresultsfromthearticle:%%[1]K.Dabov,A.Foi,V.Katkovnik,andK.Egiazarian,"ImageDenoising%bySparse3DTransform-DomainCollaborativeFiltering,"%IEEETransactionsonImageProcessing,vol.16,no.8,August,2007.%preprintathttp://www.cs.tut.fi/~foi/GCF-BM3D.%%%FUNCTIONINTERFACE:%%[PSNR,y_est]=BM3D(y,z,sigma,profile,print_to_screen)%%!Thefunctioncanworkwithoutanyoftheinputarguments,%inwhichcase,theinternaldefaultonesareused!%%BASICUSAGEEXAMPLES:%%Case1)Usingthedefaultparameters(i.e.,imagename,sigma,etc.)%%[PSNR,y_est]=BM3D;%%Case2)Usinganexternalnoisyimage:

ArthurErdelyi-Tablesofintegraltransforms.Vol.1.-McGraw-HillInc.,US(1954)

Thisneweditiontotheclassicbookbyggplot2creatorHadleyWickhamhighlightscompatibilitywithknitrandRStudio.ggplot2isadatavisualizationpackageforRthathelpsuserscreatedatagraphics,includingthosethataremulti-layered,withease.Withggplot2,it'seasyto:producehandsome,publication-qualityplotswithautomaticlegendscreatedfromtheplotspecificationsuperimposemultiplelayers(points,lines,maps,tiles,boxplots)fromdifferentdatasourceswithautomaticallyadjustedcommonscalesaddcustomizablesmoothersthatusepowerfulmodelingcapabilitiesofR,suchasloess,linearmodels,generalizedadditivemodels,androbustregressionsaveanyggplot2plot(orpartthereof)forlatermodificationorreusecreatecustomthemesthatcapturein-houseorjournalstylerequirementsandthatcaneasilybeappliedtomultipleplotsapproachagraphfromavisualperspective,thinkingabouthoweachcomponentofthedataisrepresentedonthefinalplotThisbookwillbeusefultoeveryonewhohasstruggledwithdisplayingdatainaninformativeandattractiveway.SomebasicknowledgeofRisnecessary(e.g.,importingdataintoR).ggplot2isamini-languagespecificallytailoredforproducinggraphics,andyou'lllearneverythingyouneedinthebook.Afterreadingthisbookyou'llbeabletoproducegraphicscustomizedpreciselyforyourproblems,andyou'llfinditeasytogetgraphicsoutofyourheadandontothescreenorpage.TableofContentsPartIGettingStartedChapter1IntroductionChapter2GettingStartedwithggplot2Chapter3ToolboxPartIITheGrammarChapter4MasteringtheGrammarChapter5BuildaPlotLayerbyLayerChapter6Scales,AxesandLegendsChapter7PositioningChapter8ThemesPartIIIDataAnalysisChapter9DataAnalysisChapter10DataTransformationChapter11ModellingforVisualisationChapter12Programmingwithggplot2

第七版Indroduction_to_Mathematica_Statistics.Hogg,McKean,Craigseventhedition.pdfUIUC的STAT401统计课程教材ContentsPrefaceix1ProbabilityandDistributions11.1Introduction................................11.2SetTheory................................31.3TheProbabilitySetFunction......................101.4ConditionalProbabilityandIndependence...............211.5RandomVariables............................321.6DiscreteRandomVariables.......................401.6.1Transformations.........................421.7ContinuousRandomVariables......................441.7.1Transformations.........................461.8ExpectationofaRandomVariable...................521.9SomeSpecialExpectations.......................571.10ImportantInequalities..........................682MultivariateDistributions732.1DistributionsofTwoRandomVariables................732.1.1Expectation............................792.2Transformations:BivariateRandomVariables.............842.3ConditionalDistributionsandExpectations..............942.4TheCorrelationCoefficient.......................1022.5IndependentRandomVariables.....................1102.6ExtensiontoSeveralRandomVariables................1172.6.1∗MultivariateVariance-CovarianceMatrix...........1232.7TransformationsforSeveralRandomVariables............1262.8LinearCombinationsofRandomVariables...............1343SomeSpecialDistributions1393.1TheBinomialandRelatedDistributions................1393.2ThePoissonDistribution........................1503.3TheΓ,χ2,andβDistributions.....................1563.4TheNormalDistribution.........................1683.4.1ContaminatedNormals.....................174vviContents3.5TheMultivariateNormalDistribution.................1783.5.1∗Applications...........................1853.6t-andF-Distributions

ViewPager实现3D画廊效果，ViewPager的加载动画，主要介绍了ViewPager的setPageTransformer方法。

PetrifyisatoolforthesynthesisofboundedPetrinetsandlogicsynthesisofasynchronouscontrollers.PetrifyinitiallyperformsatokenflowanalysisofthePetrinetandproducesafinitetransitionsystem(TS).IntheinitialTS,alltransitionswiththesamelabelareconsideredasoneevent.TheTSisthentransformedandtransitionsrelabeledtofulfiltheconditionsrequiredtoobtainaPetrinetwithbisimilarortrace-equivalentbehavior.SomepropertiesforthesynthesizedPetrinetcanbeimposed(e.g.free-choice,uniquechoice,pure,state-machinedecomposable,etc.).Additionally,petrifycaninterpretthePetrinetasaSignalTransitionGraph(STG),inwhicheventsrepresentrising/fallingtransitionsofdigitalsignals.FromanSTG,petrifycansynthesizeaspeed-independentcircuitbysolvingtheproblemsofstateencoding,logicsynthesis,logicdecompositionandtechnologymappingontoagatelibrary.Petrifycanalsosynthesizecircuitundertimingassumptionsspecifiedbythedesignerorautomaticallygeneratedbythetool.PetrifyreadstheinputdescriptionfromstdinandwritestheresultingSTGtostdoutunlessotherwisespecified

在日常工作中，钉钉打卡成了我生活中不可或缺的一部分。然而，有时候这个看似简单的任务却给我带来了不少烦恼。 每天早晚，我总是得牢记打开钉钉应用，点击"工作台"，再找到"考勤打卡"进行签到。有时候因为工作忙碌，会忘记打卡，导致考勤异常，影响当月的工作评价。而且，由于我使用的是苹果手机，有时候系统更新后，钉钉的某些功能会出现异常，使得打卡变得更加麻烦。 另外，我的家人使用的是安卓手机，他们也经常抱怨钉钉打卡的繁琐。尤其是对于那些不太熟悉手机操作的长辈来说，每次打卡都是一次挑战。他们总是担心自己会操作失误，导致打卡失败。 为了解决这些烦恼，我开始思考是否可以通过编写一个全自动化脚本来实现钉钉打卡。经过一段时间的摸索和学习，我终于成功编写出了一个适用于苹果和安卓系统的钉钉打卡脚本。