Trackingmovinginterfacesincomputationalgeometry,materialssciences,robotics,imageprocessing,andfluidmechanics;

对自抗扰控制器三部分组成:跟踪微分器(trackingdifferentiator)，扩展状态观测器(extendedstateobserver)和非线性状态误差反馈控制律(nonlinearstateerrorfeedbacklaw)的matlab仿真

OptimalEstimationofDynamicSystems,SecondEditionhighlightstheimportanceofbothphysicalandnumericalmodelinginsolvingdynamics-basedestimationproblemsfoundinengineeringsystems.Accessibletoengineeringstudents,appliedmathematicians,andpracticingengineers,thetextpresentsthecentralconceptsandmethodsofoptimalestimationtheoryandappliesthemethodstoproblemswithvaryingdegreesofanalyticalandnumericaldifficulty.Differentapproachesareoftencomparedtoshowtheirabsoluteandrelativeutility.Theauthorsalsoofferprototypealgorithmstostimulatethedevelopmentandproperuseofefficientcomputerprograms.MATLAB(R)codesfortheexamplesareavailableonthebook'swebsite.NewtotheSecondEditionWithmorethan100pagesofnewmaterial,thisreorganizededitionexpandsuponthebest-sellingoriginaltoincludecomprehensivedevelopmentsandupdates.Itincorporatesnewtheoreticalresults,anentirelynewchapteronadvancedsequentialstateestimation,andadditionalexamplesandexercises.Anidealself-studyguideforpracticingengineersaswellasseniorundergraduateandbeginninggraduatestudents,thebookintroducesthefundamentalsofestimationandhelpsnewcomerstounderstandtherelationshipsbetweentheestimationandmodelingofdynamicalsystems.Italsoillustratestheapplicationofthetheorytoreal-worldsituations,suchasspacecraftattitudedetermination,GPSnavigation,orbitdetermination,andaircrafttracking.

ThispaperproposesaHybridoptimization,whichcombinesintelligentgeneticalgorithmandnonlinearleastsquaresmethod.TheHybridoptimizationcanachievetheoptimaltuningvalueofADRCcontroller.UnderthecontrolstructureofMaximumPowerPointTracking(MPPT)strategyandActiveDisturbanc

TodaysComprehensiveandAuthoritativeGuidetoAugmentedRealityByoverlayingcomputer-generatedinformationontherealworld,augmentedreality(AR)amplifieshumanperceptionandcognitioninremarkableways.Workinginthisfast-growingfieldrequiresknowledgeofmultipledisciplines,includingcomputervision,computergraphics,andhuman-computerinteraction.AugmentedReality:PrinciplesandPracticeintegratesallthisknowledgeintoasingle-sourcereference,presentingtodaysmostsignificantworkwithscrupulousaccuracy.PioneeringresearchersDieterSchmalstiegandTobiasHollerercarefullybalanceprinciplesandpractice,illuminatingARfromtechnical,methodological,anduserperspectives.CoverageincludesDisplays:head-mounted,handheld,projective,auditory,andhapticTracking/sensing,includingphysicalprinciples,sensorfusion,andreal-timecomputervisionCalibration/registration,ensuringrepeatable,accurate,coherentbehaviorSeamlessblendingofrealandvirtualobjectsVisualizationtoenhanceintuitiveunderstandingInteractionfromsituatedbrowsingtofull3DinteractionModelingnewgeometriccontentAuthoringARpresentationsanddatabasesArchitectingARsystemswithreal-time,multimedia,anddistributedelementsThisguideisindispensableforanyoneinterestedinAR,includingdevelopers,engineers,students,instructors,researchers,andserioushobbyists.

视频目标跟踪领域经典论文MIL（RobustObjectTrackingwithOnlineMultipleInstanceLearning）对应的源码及论文原文（源码包含MATLAB代码和C++代码两个版本）。
官方页面上目前已经不再提供源码支持，这是本人以前下载的官方源码，现特此分享供网友学习研究用。
压缩包文件清单：1.gsoc11_tracking-master.zip2.MilTracker-V1.0.zip3.MilTrack_matlab_v1.0.rar4.MilTrack_matlab_v1.0_runnable_and_with_comment.rar5.Babenko-2011-RobustObjectTrackingwithOnlin.pdf其中1-3号文件为官方源代码。
4号文件主要增加了注释，其MATLAB源码经过本人亲自运行过

Asurveyonjointtrackingusingexpectation-maximizationbasedtechniques

本资源为随机有限集学习的matlab代码资源，如不能运行，请私聊联系博主！主要内容为随机有限集在多目标跟踪领域的应用，有PHD、Bernoulli、Cbmember、Glmb滤波的实现。

TrackingandKalmanFilteringMadeEasy

Inordertoimprovethetrackingandstabilizationperformanceofthree-axisgyrostabilizedplatform,anadaptivedecouplingcontrolbasedonneuralnetworksisdeveloped.Thedynamicmodelofthree-axisGSPisdevelopedbasedontraditionalNewton–Eulermethod.Thenonlinearityandcouplingsystemisfull-state-linearizedusingfeedbacklinearization,andneuralnetworksareusedtocompensateforthedisturbancesanduncertainties.Thestabilityoftheproposedschemeisanalyzedbythe

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。