FFT高精度谐波检测方法研究

基于DSP28335的永磁同步电机无速度传感器程序

基于ICP的迭代配准算法，用matlab编写

matlab代码-雷达脉冲压缩及多普勒处理。本代码以雷达中常用的线性调频信号（LFM）为例，展示了雷达信号处理中的脉冲压缩及多普勒处理的过程。

【实例简介】

医院选址问题1. 问题描述n个村庄之间的交通图可以用有向网图来表示，图中边上的权值表示从村庄i到村庄j的道路长度。现在要从这n个村庄中选择一个村庄新建一所医院，问这所医院应建在哪个村庄，才能使所有的村庄离医院都比较近？2. 基本要求(1) 建立模型，设计存储结构；(2) 设计算法完成问题求解；(3) 分析算法的时间复杂度。3. 设计思想医院选址问题实际是求有向图中心点的问题。首先定义顶点的偏心度。设图G=（V，E），对任一顶点k，称E(k)=max{d(i, k)}（i∈V）为顶点k的偏心度。显然，偏心度最小的顶点即为图G的中心点。如图7(a)所示是一个带权

红绿灯识别 opencv 运动物体识别

把 G.Rilling 写的 EMD.m注释汉化了，同时根据个人理解添加了部分注释，最后附上一个EMD分解＋HHT谱＋边际谱的例子。例子程序中所用到的函数是G.Rilling提供的

1.启动即可检测所有雷电模拟器2.可自由选择启动模拟器3.可自由启动线程，点击全部启动，启动已选模拟器对应的线程。放心不会重复启动不会乱，只启动选择的，如果选择已经启动，会自动识别4.可实现单停，全停，暂停，恢复，单窗口重启线程5.直接按照我的说明写单开脚本，放入接口，即可完美时间多线程操作。6.中控功能给出案例，自己研究，后期我会陆续更新功能，包括找色全分辨率识别算法7.只要你不修改界面设置，你只需要在接口写入你单开操作的代码，就可以直接实现中控看懂我画箭头的提示即可 非常简单！！启动窗口标题，直接修改属性即可改变，下面2行字是状态条文本，0和1 2项直接在启动窗口创建事件中 状态条1.置文

基于C#的FTP上传Demo，基于FTP协议，无需服务端应用，只需服务端建立FTP站点，便可实现文件传输，代码简洁清晰，注释详细，方便学习

An introduction to stochastic processes through the use of RIntroduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The uINTRODUCTIONTO STOCHASTICPROCESSES WITH RINTRODUCTIONTO STOCHASTICPROCESSES WITH RROBERT P DOBROWWILEYCopyright o 2016 by John Wiley Sons, Inc. All rights reservedPublished by John Wiley Sons, Inc, Hoboken, New JerseyPublished simultaneously in CanadaNo part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form orby any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except aspermitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the priorwritten permission of the Publisher, or authorization through payment of the appropriate per-copy fee tothe Copyright Clearance Center, Inc, 222 Rosewood Drive, Danvers, MA,(978)750-8400, fax978)750-4470,oronthewebatwww.copyright.comRequeststothePublisherforpermissionshouldbe addressed to the Permissions Department, John Wiley sons, Inc, lll River Street, Hoboken, NJ07030,(201)748-6011,fax(201)748-6008,oronlineathttp://www.wiley.com/go/permissionsLimit of liability/ Disclaimer of warranty While the publisher and author have used their best efforts inpreparing this book, they make no representations or warranties with respect to the accuracy orcompleteness of the contents of this book and specifically disclaim any implied warranties ofmerchantability or fitness for a particular purpose. No warranty may be created or extended by salesrepresentatives or written sales materials. The advice and strategies contained herein may not be suitablefor your situation. You should consult with a professional where appropriate. Neither the publisher norauthor shall be liable for any loss of profit or any other commercial damages, including but not limited tospecial, incidental, consequential, or other damagesFor general information on our other products and services or for technical support, please contact ourCustomer Care Department within the United States at(800)762-2974, outside the United States at(317)572-3993 or fax(317)572-4002Wiley also publishes its books in a variety of electronic formats. Some content that appears in print maynot be available in electronic formats. For more information about Wiley products, visit our web site atwww.wiley.comLibrary of Congress Cataloging-in-Publication Data:Dobrow. Robert p. authorIntroduction to stochastic processes with r/ Robert P. Dobrowpages cmIncludes bibliographical references and indexISBN978-1-118-74065-1( cloth)1. Stochastic processes. 2. R( Computer program language)I. TitleQC20.7.S8D6320165192′302855133-dc232015032706Set in 10/12pt, Times-Roman by SPi Global, Chennai, IndiaPrinted in the united states of america1098765432112016To my familyCONTENTSPrefaceAcknowledgmentsList of Symbols and Notationabout the companion Website1 Introduction and review1.1 Deterministic and stochastic models. 11. 2 What is a Stochastic Process? 61. 3 Monte Carlo Simulation. 91.4 Conditional Probability, 101. 5 Conditional Expectation, 18Exercises. 342 Markov Chains: First Steps402.1 Introduction. 402.2 Markov Chain Cornucopia, 422.3 Basic Computations, 522. 4 Long-Term behavior-the Numerical evidence, 592.5 Simulation. 652.6 Mathematical Induction*. 68Exercises. 70CONTENTS3 Markov Chains for the long term763.1 Limiting Distrib763.2 Stationary Distribution, 803.3 Can you find the way to state a? 943.4 Irreducible markov Chains. 1033.5 Periodicity, 1063.6 Ergodic Markov Chains, 1093.7 Time Reversibility, 1143.8 Absorbing Chains, 1199 Regeneration and the strong markov property 1333.10 Proofs of limit Theorems*, 135Exercises. 1444 Branching processes1584.1 Introduction. 1584.2 Mean Generation Size. 1604.3 Probability Generating Functions, 1644.4 Extinction is Forever. 168Exercises. 1755 Markov Chain Monte Carlo1815.1 Introduction. 1815.2 Metropolis-Hastings Algorithm, 1875.3 Gibbs Sampler, 1975.4 Perfect Sampling*, 20.55.5 Rate of Convergence: the Eigenvalue Connection*, 2105.6 Card Shuffing and Total Variation Distance. 212Exercises. 2196 Poisson process2236.1 Introduction. 2236.2 Arrival. Interarrival Times. 2276.3 Infinitesimal Probabilities. 2346.4 Thinning, Superposition, 2386.5 Uniform Distribution. 2436.6 Spatial Poisson Process, 2496.7 Nonhomogeneous Poisson Process. 2536.8 Parting Paradox, 255Exercises. 2587 Continuous- Time markov Chains2657.1 Introduction. 265