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CRC32校验程序源代码( C++)
CRC32校验程序源代码,vc6.0下编译通过，请放心使用。
- 2020-12-01下载
- 积分：1
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多维容积卡尔曼滤波（CKF）的函数
之前一直说要上传多维CKF滤波的例子，一直没时间，这次上传的是一个多维函数，在你的仿真中直接调用运行即可，程序都是自己一个一个敲出来的，并且经过测试的。
- 2020-12-03下载
- 积分：1
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考勤机SDK二次开发包接口
本接口sdk包含了vb/vb.net/c#等语言的接口代码，可以直接使用或是扩展开发
- 2020-12-02下载
- 积分：1
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稀疏自编码深度学习的Matlab实现
稀疏自编码深度学习的Matlab实现，sparse Auto coding，Matlab codetrain, m/7% CS294A/CS294W Programming Assignment Starter CodeInstructions%%%This file contains code that helps you get started ontheprogramming assignment. You will need to complete thecode in sampleIMAgEsml sparseAutoencoder Cost m and computeNumericalGradientml For the purpose of completing the assignment, you domot need tochange the code in this filecurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencodtrain.m∥%%========%6% STEP 0: Here we provide the relevant parameters valuesthat willl allow your sparse autoencoder to get good filters; youdo not need to9 change the parameters belowvisibleSize =8*8; number of input unitshiddensize 25number of hidden unitssparsity Param =0.01; desired average activation ofthe hidden units7 (This was denoted by the greek alpharho, which looks like a lower-case pcurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod4/57train.,m∥in the lecture notes)1 ambda=0.0001%o weight decay parameterbeta 3%o weight of sparsity penalty term%%==:79 STEP 1: Implement sampleIMAGESAfter implementing sampleIMAGES, the display_networkcommand shouldfo display a random sample of 200 patches from the datasetpatches sampleIMAgES;display_network(patches(:, randi(size(patches, 2), 204, 1)), 8)%为产生一个204维的列向量,每一维的值为0~10000curer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod5/57train.m/v%中的随机数,说明是随机取204个 patch来显示%o Obtain random parameters thetatheta= initializeParameters ( hiddenSize, visibleSize)%%=============三三三三====================================97 STEP 2: Implement sparseAutoencoder CostYou can implement all of the components (squared errorcost, weight decay termsparsity penalty) in the cost function at once, butit may be easier to do%o it step-by-step and run gradient checking (see STEP3 after each stepWecurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod6/57train. m vb suggest implementing the sparseAutoencoder Cost functionusing the following steps(a) Implement forward propagation in your neural networland implement the%squared error term of the cost function. Implementbackpropagation tocompute the derivatives. Then (using lambda=beta=(run gradient Checking%to verify that the calculations corresponding tothe squared error costterm are correctcurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod7/57train. m vl(b) Add in the weight decay term (in both the cost funcand the derivativecalculations), then re-run Gradient Checking toverify correctnessl (c) Add in the sparsity penalty term, then re-run gradiChecking toverify correctnessFeel free to change the training settings when debuggingyour%o code. (For example, reducing the training set sizecurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod8/57train m vl/number of hidden units may make your code run fasterand setting betaand/or lambda to zero may be helpful for debuggingHowever, in yourfinal submission of the visualized weights, please useparameters web gave in Step 0 abovecoS七grad]sparseAutoencoderCost(theta, visibleSize,hiddensize, lambda,sparsityParam, beta,patches)二〓二二二二二二二〓二〓二〓二〓=二====〓=curer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod9/57train.m vlll96% STeP 3: Gradient CheckingHint: If you are debugging your code, performing gradienchecking on smaller modelsand smaller training sets (e. g, using only 10 trainingexamples and 1-2 hiddenunits) may speed things upl First, lets make sure your numerical gradient computationis correct for a%o simple function. After you have implemented computeNumerun the followingcheckNumericalGradientocurer:YiBinYUyuyibintony@163.com,WuYiUniversityDeep Learning, MATLAB Code for Sparse Autoencode10/57
- 2020-12-05下载
- 积分：1
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多尺度熵 matlab程序
多尺度熵 matlab程序，可以运行 样本熵 模糊熵 排列熵 多尺度熵 层次熵 多尺度排列熵 信息熵
- 2020-11-28下载
- 积分：1
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C#编写《LED圆形灯》控件
使用c#编写的LED小灯控件，可以使用在工业控制中。开发环境：Visual Studio 2010开发语言：C#
- 2020-12-06下载
- 积分：1
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基于遗传算法求解0,1背包问题
基于遗传算法求解0,1背包问题，以遗传算法对求解0.1背包问题进行优化，优化计算时间等。。
- 2021-05-07下载
- 积分：1
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加窗傅里叶变换和小波变换的原理与程序
本文详细介绍了加窗傅里叶变换和小波变换的原理，并给出了加窗傅里叶变换和小波变换的主程序代码。
- 2020-12-01下载
- 积分：1
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Observers in Control Systems
详细介绍了状态观测器及其在控制系统中的应用。Observers inControl SystemsA Practical guideGeorge ellisDanaher corporation4ACADEMIC PRESSAn imprint of elsevier ScienceAmsterdam Boston London New York Oxford ParisSan Diego San Francisco Singapore Sydney TokyoThis book is printed on acid-free paper ooCopyright 2002, Elsevier Science (USA)All rightsNo part of this publication may be reproduced or transmitted in any form or by anymeans, electronic or mechanical, including photocopy, recording, or any informationstorage and retrieval system, without permission in writing from the publisher. Requestsfor permission to make copies of any part of the work should be mailed to thefollowing address: Permissions Department, Harcourt, Inc, 6277 Sea Harbor DriveOrlando. Florida. 32887-6777.ACADEMIC PRESSAn imprint of Elsevier Science525 B Street, Suite 1900, San Diego, CA 92101-4495, USAhttp://www.academicpress.comAcademic pr84 Theobalds Road. London WCIX 8RR. UKhttp://www.academicpress.comLibrary of congress control Number: 2002104256International Standard book Number: 0-12-237472-XPrinted in the United States of america020304050607MB987654321TO Lee Ann, my loving wife, and our daughter Gretchen, who makes us both proud.Observers in Control Systems■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■Acknowledgments■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■Safety■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■1 Control Systems and the role of observers■■■■■■■■■■■■■■■■1.1 Overviewaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa1.2 Preview of observers21.3 Summary of the book2 Control-System Background52.1 Control-System Structures52.2 Goals of control systems132.3 Visual Model Simulation Environment2. 4 Software Experiments: Introduction to Visual ModelQ182.5 Exercises393 Review of the Frequency Domain.■■■■■■■■■■■■■■■■■■■■■■■■■■■■■3. 1 Overview of the s-domain413.2 Overview of the z-Domain543.3 The Open-Loop Method593.4 A Zone-Based Tuning Procedure623.5 Exercises664 The Luenberger observer: Correcting SensorProblems674. 1 What Is a luenberger observer?674.2 Experiments 4A-4C: Enhancing Stability with an Observer724.3 Predictor-Corrector Form of the Luenberger Observer774. 4 Filter Form of the luenberger observer. ..................................784.5 Designing a Luenberger observer824.6 Introduction to Tuning an observer compensator9047 Exercises955 The Luenberger Observer and Model Inaccuracy... 975.1 Model Inaccuracy.........….……,975.2 Effects of Model Inaccuracy .............................................1005.3 Experimental Evaluation1025.4 Exercises1146 The Luenberger observer and disturbances1156.1 Disturbances1156.2 Disturbance Response1236.3 Disturbance DecouplingIB..-.81296.4 Exercises1387 Noise in the Luenberger Observer…,,,…,,…,…,1417.1 Noise in Control Systems1417.2 Sensor noise and the luenberger observer1457.3 Noise Sensitivity when Using Disturbance Decoupling1567. 4 Reducing Noise Susceptibility in Observer-Based Systems1617.5 Exercises1708 Using the Luenberger Observer in Motion Control1738.1 The Luenberger observers in motion Systems1738.2 Observing Velocity to Reduce Phase Lag1858.3 Using observers to Improve Disturbance Response..... 2028.4 Exercises212Referencesn213A Observer-Based resolver conversion in industrialServo Systems1■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■217B Cures for mechanical resonance in IndustrialServo Systems227Introductionaaa日aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa日aaaaa.aaaaaaaaaaaaaaa日aa227TWo-Part Transfer function228LOW-Frequency Resonance229Velocity Control Law…...8....230Methods of Correction Applied to Low-Frequency Resonance231Conc| usion.…235Acknowledgments235References235C European Symbols for Block Diagrams237Part Linear functions237Part l: nonlinear functions238D Development of the bilinear transformation241Bilinear Transformation241Prewarning242Factoring polynomials243Phase Advancing………………………,243Solutions toChapter 2245Chapter 3245Chapter 4246Chapter 5重口m口m246Chapter 6247Chapter7.….B..8..8..8...248Chapter 8249Index251AcknowledgmentsWriting a book is a large task and requires support from numerous people, and thosepeople deserve thanks. First, I thank LeeAnn, my devoted wife of more than 20 yearsShe has been an unflagging fan, a counselor, and a demanding editor. She taught memuch of what I have managed to learn about how to express a thought in ink. Thanksto my mother who was sure I would grow into someone in whom she would be proudwhen facts should have dissuaded her Thanks also to my father for his insistence thatI obtain a college education; that privilege was denied to him, an intelligent man borninto a family of modest meansI am grateful for the education provided by Virginia Tech Go Hokies. The basicsof electrical engineering imparted to me over my years at school allowed me to graspthe concepts I apply regularly today. I am grateful to Mr. Emory Pace, a toughprofessor who led me through numerous calculus courses and, in doing so, gaveme the confidence on which I would rely throughout my college career and beyondI am especially grateful to Dr Charles Nunnally; having arrived at university froma successful career in industry, he provided my earliest exposure to the practicalapplication of the material I strove to learn. I also thank Dr robert lorenz of theUniversity of Wisconsin at Madison, who introduced me to observers some years agoHis instruction has been enlightening and practical. Several of his university coursesare available in video format and are recommended for those who would like toextend their knowledge of controls. In particular, readers should consider ME 746which presents observers and numerous other subjectsI thank those who reviewed the manuscript for this book. Special thanks goes toDan Carlson for his contributions to almost every chapter contained herein Thanksalso to Eric Berg for his numerous insights. Thanks to the people of KollmorgenCorporation(now, Danaher Corporation), my long-time employer, for their continuing support in writing this book. Finally, thanks to Academic Press, especially to JoelClaypool, my editor, for the opportunity to write this edition and for editing, printing, distributing, and performing the myriad other tasks required to publish a bookX1
- 2020-12-11下载
- 积分：1
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基于FPGA的直流电机PWM控制
用QII 9.1做的，可以实现加减速、启停、正反转、旋转圈数计数
- 2020-12-10下载
- 积分：1
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