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多元逐步回归的matlab代码
本程序利用matlab实现多元逐步回归的基本原理
- 2020-12-10下载
- 积分：1
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ILI9325 驱动程序
开发环境MDK4.12 TFT ILI9325 芯片：STM32F103VET6使用FSMC 驱动
- 2020-11-29下载
- 积分：1
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基于matlab的yalmip+cplex的二阶锥SOCP-OPF的IEEE33算例潮流.zip
【实例简介】请注意！！！！本资料自2021.10.15更新了OLTC、DG的问题，解决了同学们提出的一些问题错
基于算例IEEE33还有PG69，使用CPLEX+YALMIP进行二阶锥松弛建模的多时间断面潮流，内容丰富，包含本人所有的复现资料，有主动管理OLTC，CB,SVC,ESS等，配电网重构，综合负荷，注释绝对清晰，程序易懂，可改写能力强，适用小白。复现自《主动配电网最优潮流研究及其应用实例》-高红均，约束什么都一样。
有主动配电网二阶锥最优潮流的所有学习资料，看完我这个，绝对不会有这方面的问题。运行问题可以帮忙解决！！！可答疑
- 2021-12-15 00:41:55下载
- 积分：1
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GPS仿真-matlab工具箱
MATLAB下的GPS工具箱，GPS TOOLBOX包含以下内容：1、GPS相关常量和转换因子；2、角度变换；3、坐标系转换： 点变换； 矩阵变换； 向量变换；4、专用测绘程序；5、专用统计函数；6、GPS时间工具；7、专用GPS数据处理函数；8、航迹和相关工具；9、卫星位置计算；10、高度和方位角判定，以及卫星可见性；11、DOP（dilution of precision）计算，卫星选取和相关函数；12、专用信号处理和Kalman滤波函数；13、伪距和误差判定及相关函数；14、用户位置判定及相关函数；15、RAIM/FDE可用性和完好性评估相
- 2020-06-26下载
- 积分：1
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模拟AM与FM调制解调系统
实验 1 ：模拟AM调制解调系统幅度调制解调技术是一种最简单的模拟调制方法，而且通过幅度调制容易理解调制的概念。本实验通过 LabVIEW 编程产生信号频率、幅度等参数可变的基带信号和载波信号，实现 AM 调制和解调，观察参数变化对已调信号的影响。并通过仿真运行整个 AM 调制解调系统，学习掌握代码调试方法，验证程序的正确性。实验 2 ：模拟FM调制解调系统利用 LABVIEW 仿真，产生基带信号频率、载波频率及频偏等参数可变的 FM 调制解调系统，观察参数变化对被调制信号以及其 FFT 功率谱的影响。并通过仿真运行整个 FM 调制解调系统，学习掌握代码调试方法，验证程序代码的正确性。通信原狸与系统实验报告【程序设计】1、总体程序实验1:模拟AM调制解调系统AM信亏波形翌(时)波信号上边带下边带正弦波形(时域)载波幅值制信号湖形图(时域)调制值颗谱测量AM洞制信号波形因(罚信号「·(峰值100000实验2:模拟FM调制解调系统载波率f(Hz)仿真信号3网回區最大偏移量f(Hz仿真信号2信号基带率和b(HzPower SpectruA圆周信号域仿真信号FM调制信号弦10000001000000导数dxdt)Simulate正弦通信原理与系统实验报告2、部分函数图音分函数图Hilbert变换函数部至复数转换复数至极坐标转换交流和直流分量估计归一化波形【实验内容】实验1:模拟AM调制解调系统1、按(P2713)的实验步骤1完成AM调制2、按(P2)的AM解调原理的提示完成AM解调根据实验教程,仿真信号快速ⅥI与频谱测量快速Ⅵ发其最终对话框选项设置如下:信号关型O幅(均方慢)加后的辅轴入信号5.583643幅度(峰直盐r变谱功增密赏占空比5.5050450D2040.60B口加难声声型099999阳果览种子值验时识相对于更开时间吧对(日期与时于均数日100000仍真平集时轴更信号采枉盈重置相位,种子和时标识乐月连续生成生递每次环口整数需吗数信号名称实玩无样数10o信号名称取商在前面板中设置参数如卜:载波幅值调制幅值11.:1戴冷200m1……4006008001000020406080100120140160180200调制频率0250500750100012501500175020000204060801001201401601802004通信原理与系统实验报告设置好参数后,运行程序,结果如图所示载波信号波形(时域)弦M4M制信号波形(时域正弦20020015050-15020020000.020.040.060.080.100.020.040.060.080.1时间时间AM调制信号形图(数城)开F:(值)四4M解号形(时城)5002050150200-15010020030040050000.020.040.060.080.1频率时间分析:观察“AM调制信号波形图(时域)”图可知:经过AM调制将调制信号加载到载波信号上后,形成的包络恰好与基带信号一致。观察“ΔM调制信号波形图(频域)”图可知:最左边的频谱为基带信号的频谱,而右边的三个频谱从左到右依次为下边带fc-fb,载波fe,上边带fc+fb的频谱。观察“AM解调信号波形图(时域)”图可知:解调后的信号与基带信号基本重合,说明运用包络检波法解调信号成功。改变实验参数增大基带信号的幅度,其他参数不变分析:如下图所示,前两幅图分別为增大基带信号幅度前的调制信号的时域图和频域图,后面两幅图为增大基带信号幅度后的调制信号的吋域图和频域图。通过观察图像可发现:增大基带信号樞度,其他参数不变的情况下:调制信号在时域上的幅度随基带信号幅度的增大而増大,而频域上不发生变化。5通信原狸与系统实验报告AM调制信号波形图(时域)AM调制信号波形(频域)应(F·(值)3005020050100200150300200-00.020.040.060.080.1100200300400500时间AM调周制信号波形图(时城)AM调制信号波形图(频域)正弦(FT·(峰值)50200100-1001002003000.020.040.060.080.10100200300400500时间频率增大基带信号的频率,其他参数不变分析:如下图所示,前两幅图分别为增大基带信号频率前旳调訇信号的时域图和频域图,后面两幅图为增大基带信号频率后的调制信号的时域图和频域图。通过观察图像可发现:增大基带信号频率,其他参数不变的情况下:调制信号在时域上的频率随基带信号频率的增大而增大,而频域上也发生了右移。AM调制信号波形图(时域MAM调制信号波形图(城)F·(峰值))M5020010050100200150-30020000.020.040.060.080.10100200300400500时间频率通信原理与系统实验报告AM调制信号波形图(时域)AM调制信号波形图(颈域)正弦·(峰值)50-200100500100-10020030020000.020.040.060.080.10100200300400500时间增大载波信号的幅度,其他参数不变分析:如下图所示,前两幅图分别为增大载波幅度前的调制信号的时域图和频域图,后面两幅图为增大载波幅度后的调制信号的时域图和频域图。通过观察图像可发现:增大载波幅度,其他参数不变的情况下:调制信号在时域上的幅度随载波信号幅度的增大而增大,而频域上不发生变化。AM调制信号波形图(时域)正弦AM调制信号波形圈(频域)H·(峰值)30050200010-500-100-200-150300-20000.020.040.060.080.10100200300400500时间频率AM调制信号波形图(时域)正弦AM制号形(炫)芷奸:()人503000200100细10020015030040020000.020.040.060.080.110200时间频率通信原狸与系统实验报告增大载波信号的频率,其他参数不变分析:如下图所示,前两幅图分别为增大载波频率前的调制信号的时域图和频域图,后面两幅图为增大载波频率后的调制信号的时域图和频域图。通过观察图像可发现:增大载波频率,其他参数不变的情况下:调制信号频率在时域上的频率随载波信号频率的增大而增大,而频域上也发生了右移。AM调制信号波形图(时城正弦AM调制信号波形图(颁域)正弦任FT·(峰值)3002000100200-300-20000.020.040.060.080.10100200300400500时间频率AM调制信号波形图(时域)正凶M制儒号形图(域):(峰)300502001000-100-20030020000.020.040.060.080.10100200300400500时间实验2:模拟FM调制解调系统、按(322.3)实验内容完成FM的调制2、按(3223)的实验内容元成FM的解调根据实验教程,仿真信号快速Ⅵ与频谱测量快速ⅥI及其最终对话框选项设置如下通信原理与系统实验报告配雪仿真信号[真台号3]生造量结果预范所选到早3、02691幅度(蜂值位(D功幸造C线性O功率造移量占空比O092Hanning君果候嚣均方根对测经开始间保待O姆对(日期与时词)半均数目C仿真菜对钟申仨号·以可达到最速度运行里相位种了和时标日相位軍预100日)来用端牛应信号名称O当平均时用信号类型名偏学会称□开相位150200250300350400450500阳确定联群取篇□帮数在前面板中设置参数如下:基带频率fb(Hz)载波频率fe(Hz)20000400006000080000100000110000033000005000007000009000001E+6最大偏移量t(Hz)20000400006000080000100000120000140000160000180000205410设置好参数后,运行程序,结果如图所示基带信号(时域正弦A载反信号(时域)正弦0.5000.5-0.505E-50.00010000150.00025E-50.00010.000150.0002时间时间时城须域FM调制信号(时域正弦0.50.52E-6E-58E-50.00010.000120.000140.000160.000180.0002时司通信原理与系统实验报告时域频域FM调制信号(域)正弦(功率-1002000500000150000025000003500000450000055000006500000750000085000001E+7频率FM解调信号(时域)正弦2E-56E-58E-50.00010.000120000140.000160.000180.0002时间分析:观察“FM调制信号(时域)”图与“FM调制信号(频域)”图可知:经过FM调制后产生的波形与原理相符合;观察“AM解调信号波形图(时域)”图可知:解调后的信号与基带信号基本重合,说明运用非相关包络检波法解调信号成功。改变实验参数≯增大基带信号的频率,其他参数不变分析:如下图所示,前两幅图分别为增大基带信号频率前的调制信号的时域图和频域图,后面两幅图为增大基带信号频率后的调制信号的时域图和频域图。通过观察图像可发现:增大基带信号频率,其他参数不变的情况下:调制信号在时域上的频率随基带信号的频率的增大而增大。
- 2021-05-06下载
- 积分：1
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无标度集聚网络上的博弈模型.rar
基于无标度集聚网络的博弈模型；采用囚徒困境博弈模型；内附.m文件和doc解释文件
- 2019-11-27下载
- 积分：1
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图像分割 高斯混合模型 马尔科夫 image segmentation MRF GMM ICM
image segmentation MRF GMM ICM 图像分割 马尔科夫随机场 高斯混合模型 ICM算法 另附详细的说明pdf 讲清GMM，MRF做分割的详细原理，可作为参考。
- 2020-12-05下载
- 积分：1
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四旋翼MATLAB仿真文件+实验报告
control_sys2 四旋翼MATLAB报告目录一、 需求分析 11. 背景介绍 12. 需求分析 2二、 系统原理 21. 技术方案 22. 数学模型 3三、 控制器的设计与仿真 41. 姿态回路控制器的设计 42. 位置回路控制器设计 53. 仿真结果 61． 位置仿真结果 72． 姿态仿真结果 83． 结果分析 9四、 实验总结 10
- 2020-12-03下载
- 积分：1
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系统辨识大牛Ljung编写的MATLAB系统辨识使用手册
系统辨识大牛Ljung编写的MATLAB系统辨识使用手册，这本书详细地介绍了在MATLAB已经所属simulink环境下，系统辨识工具箱的一些使用办法，是一本非常经典的教材！Revision Historypril 1988First printingJuly 1991Second printingMay1995Third printingNovember 2000 Fourth printingRevised for Version 5.0(Release 12)pril 2001Fifth printingJuly 2002Online onlyRevised for Version 5.0.2 Release 13)June 2004Sixth printingRevised for Version 6.0.1(Release 14)March 2005Online onlyRevised for Version 6.1.1Release 14SP2)September 2005 Seventh printingRevised for Version 6.1.2(Release 14SP3)March 2006Online onlyRevised for Version 6.1.3(Release 2006a)September 2006 Online onlyRevised for Version 6.2 Release 2006b)March 2007Online onlyRevised for Version 7.0 ( Release 2007a)September 2007 Online onlyRevised for Version 7.1 (Release 2007bMarch 2008Online onlyRevised for Version 7.2(Release 2008a)October 2008Online onlyRevised for Version 7.2.1 Release 2008b)March 2009Online onlyRevised for Version 7.3(Release 2009a)September 2009 Online onlyRevised for Version 7.3.1(Release 2009b)March 2010Online onlyRevised for Version 7. 4 (Release 2010a)eptember2010 Online onlyRevised for Version 7.4.1(Release 2010b)pril 2011Online onlRevised for Version 7.4.2(Release 2011a)September 2011 Online onlyRevised for Version 7.4.3(Release 2011b)March 2012Online onlyRevised for Version 8.0( Release 2012aabout the DevelopersAbout the Developersystem Identification Toolbox software is developed in association with thefollowing leading researchers in the system identification fieldLennart Ljung. Professor Lennart Ljung is with the department ofElectrical Engineering at Linkoping University in Sweden. He is a recognizedleader in system identification and has published numerous papers and booksin this areaQinghua Zhang. Dr. Qinghua Zhang is a researcher at Institut Nationalde recherche en Informatique et en Automatique(INria) and at Institut deRecherche en Informatique et systemes Aleatoires (Irisa), both in rennesFrance. He conducts research in the areas of nonlinear system identificationfault diagnosis, and signal processing with applications in the fields of energyautomotive, and biomedical systemsPeter Lindskog. Dr. Peter Lindskog is employed by nira dynamiAB, Sweden. He conducts research in the areas of system identificationsignal processing, and automatic control with a focus on vehicle industryapplicationsAnatoli Juditsky. Professor Anatoli Juditsky is with the laboratoire JeanKuntzmann at the Universite Joseph Fourier, Grenoble, france. He conductsresearch in the areas of nonparametric statistics, system identification, andstochastic optimizationAbout the developersContentsChoosing Your System Identification ApproachLinear model structures1-2What Are Model objects?Model objects represent linear systemsAbout model data1-5Types of Model objectsDynamic System Models1-9Numeric Models1-11umeric Linear Time Invariant (LTD Models1-11Identified LTI modelsIdentified Nonlinear models1-12Nonlinear model structures1-13Recommended Model Estimation Sequence1-14Supported Models for Time- and Frequency-DomainData,,,,,,,1-16Supported Models for Time-Domain Data1-16Supported Models for Frequency-Domain Data1-17See also1-18Supported Continuous-and Discrete-Time Models1-19Model estimation commands1-21Creating Model Structures at the command Line ... 1-22about system Identification Toolbox Model Objects ... 1-22When to Construct a Model Structure Independently ofEstimation1-23Commands for Constructing Model Structures1-24Model Properties1-25See als1-27Modeling Multiple-Output Systems ......... 1-28About Modeling multiple-Output Systems1-28Modeling Multiple Outputs Directly1-29Modeling multiple outputs as a Combination ofSingle-Output Models.......1-29Improving Multiple-Output Estimation Results byWeighing Outputs During Estimation ....... 1-30Identified linear Time-Invariant models1-32IDLTI Models1-32Configuration of the Structure of Measured and Noise oRepresentation of the Measured and noise Components foVarious model Types1-33Components ....1-35Imposing Constraints on the Values of ModeParameters1-37Estimation of Linear models1-8Data Import and Processing2「Supported Data ...2-3Ways to Obtain Identification DataWays to Prepare Data for System Identification ... 2-6Requirements on Data SamplingRepresenting Data in MATLAB Workspace·····Time-Domain Data Representation2-9Time-Series Data Representation2-10ContentsFrequency-Domain Data Representation ....... 2-11Importing Data into the Gui2-17Types of Data You Can import into the GUi2-17Importing time-Domain Data into the GUI2-18Importing Frequency-Domain Data into the GUI2-22Importing Data Objects into the GUI ......... 2-30Specifying the data sampling interval2-34Specifying estimation and validation Data2-35Preping data Using Quick StartCreating Data Sets from a Subset of Signal Channelo2-362-37Creating multiexperiment Data Sets in the gUi2-39Managing data in the gui ............. 2-46Representing Time- and Frequency-Domain Data Usingiddata object2-55iddata constructor2-55iddata Properties.........2-58Creating Multiexperiment Data at the Command Line .. 2-61Select Data Channels, I/O Data and Experiments in iddataObjects2-63Increasing Number of Channels or Data Points of iddataObjects2-67Managing iddata Objects2-69Representing Frequency-Response Data Using idfrdObiec2-76idfrd Constructor2-76idfrd Properties2-77Select I/o Channels and Data in idfrd Objects ..... 2-79Adding Input or Output Channels in idfrd Objects2-80Managing idfrd Objects2-83Operations That Create idfrd Objects2-83Analyzing Data quality2-85Is your data ready for modeling?2-85Plotting Data in the guI Versus at the command line2-86How to plot data in the gui2-86How to plot data at the command line2-92How to Analyze Data Using the advice Command2-94Selecting Subsets of Data2-96IXWhy Select Subsets of Data?2-96Extract Subsets of Data Using the GUI2-97Extract Subsets of data at the Command Line2-99Handling Missing Data and outliers2-100Handling missing data2-100Handling outliers2-101Extract and Model Specific Data Segments2-102See also2-103Handling offsets and Trends in Data2-104When to detrend data2-104Alternatives for Detrending Data in GUi or at theCommand-Line2-105Next Steps After detrending2-107How to Detrend Data Using the Gui2-108How to detrend data at the Command line2-109Detrending Steady-State Dat109cending transient Dat2-109See also2-110Resampling Data2-111What Is resampling?...,,.,,,,,,,,,,,.2-111Resampling data without Aliasing Effects2-112See also2-116Resampling data Using the GUi.,,,,2-117Resampling Data at the Command line2-118Filtering Data2-120Supported Filters2-120Choosing to Prefilter Your Data2-120See also2-121How to Filter Data Using the gui2-122Filtering Time-Domain Data in the GuI........ 2-122Content
- 2020-12-11下载
- 积分：1
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ISO 15031 (1~7全套) OBD最新版
ISO_15031-1_2010,ISO_15031-2_2010,ISO_15031-3_2016,15031-4_2014,15031-5_2016,15031-6_2015,15031-7_2013
- 2020-12-05下载
- 积分：1
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