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XFEM的程序
Matlab写的XFEM程序，用于求解裂纹，应力应变位移等变量
- 2020-12-04下载
- 积分：1
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遗传算法解决车辆的CVRP问题
本资源为遗传算法解决车辆的CVRP问题，CVRP是一个NP_HARD问题
- 2020-12-04下载
- 积分：1
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数字电子技术答案
数字电子技术基础课后习题答案，第五版，张锁良编写
- 2020-12-02下载
- 积分：1
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中国地面国际交换站气候资料日值数据集-风向风速
"中国地面国际交换站气候资料日值数据集（V3.0）"包含了中国194个站点1951年1月以来本站气压、气温、降水量、蒸发量、相对湿度、风向风速、日照时数和0cm地温要素的日值数据。数据量为1.89GB。
- 2020-11-28下载
- 积分：1
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C#设置双屏显示模式
C#实现在Win7下双屏扩展、双屏复制和停止扩展以及实现在xp下双屏扩展的功能
- 2020-12-04下载
- 积分：1
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MATLAB带通滤波器程序
应用切比雪夫滤波器，设计了带通滤波器function y=bandp(x,f1,f3,fsl,fsh,rp,rs,Fs)%带通滤波%使用注意事项：通带或阻带的截止频率与采样率的选取范围是不能超过采样率的一半%即，f1,f3,fs1,fsh,的值小于 Fs/2%x:需要带通滤波的序列% f 1：通带左边界% f 3：通带右边界% fs1：衰减截止左边界% fsh：衰变截止右边界%rp：边带区衰减DB数设置%rs：截止区衰减DB数设置%FS：序列x的采样频率% f1=300;f3=500;%通带截止频率上下限% fsl=200;fsh=600;%阻带截止频率上下限%
- 2020-12-09下载
- 积分：1
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【PDF】《Machine learning A Probabilistic Perspective》 MLAPP；by Kevin Murphy
完整版，带目录，机器学习必备经典；大部头要用力啃。Machine learning A Probabilistic PerspectiveMachine LearningA Probabilistic PerspectiveKevin P. MurphyThe mit PressCambridge, MassachusettsLondon, Englando 2012 Massachusetts Institute of TechnologyAll rights reserved. No part of this book may be reproduced in any form by any electronic or mechanicalmeans(including photocopying, recording, or information storage and retrieval)without permission inwriting from the publisherFor information about special quantity discounts, please email special_sales@mitpress. mit. eduThis book was set in the HEx programming language by the author. Printed and bound in the UnitedStates of AmLibrary of Congress Cataloging-in-Publication InformationMurphy, Kevin Png:a piobabilistctive/Kevin P. Murphyp. cm. -(Adaptive computation and machine learning series)Includes bibliographical references and indexisBn 978-0-262-01802-9 (hardcover: alk. paper1. Machine learning. 2. Probabilities. I. TitleQ325.5M872012006.31-dc232012004558109876This book is dedicated to alessandro, Michael and stefanoand to the memory of gerard Joseph murphyContentsPreactXXVII1 IntroductionMachine learning: what and why?1..1Types of machine learning1.2 Supervised learning1.2.1Classification 31.2.2 Regression 83 Unsupervised learning 91.3.11.3.2Discovering latent factors 111.3.3 Discovering graph structure 131.3.4 Matrix completion 141.4 Some basic concepts in machine learning 161.4.1Parametric vs non-parametric models 161.4.2 A simple non-parametric classifier: K-nearest neighbors 161.4.3 The curse of dimensionality 181.4.4 Parametric models for classification and regression 191.4.5Linear regression 191.4.6Logistic regression1.4.7 Overfitting 221.4.8Model selection1.4.9No free lunch theorem242 Probability2.1 Introduction 272.2 A brief review of probability theory 282. 2. 1 Discrete random variables 282. 2.2 Fundamental rules 282.2.3B292. 2. 4 Independence and conditional independence 302. 2. 5 Continuous random variable32CONTENTS2.2.6 Quantiles 332.2.7 Mean and variance 332.3 Some common discrete distributions 342.3.1The binomial and bernoulli distributions 342.3.2 The multinomial and multinoulli distributions 352. 3.3 The Poisson distribution 372.3.4 The empirical distribution 372.4 Some common continuous distributions 382.4.1 Gaussian (normal) distribution 382.4.2Dte pdf 392.4.3 The Laplace distribution 412.4.4 The gamma distribution 412.4.5 The beta distribution 422.4.6 Pareto distribution2.5 Joint probability distributions 442.5.1Covariance and correlation442.5.2 The multivariate gaussian2.5.3 Multivariate Student t distribution 462.5.4 Dirichlet distribution 472.6 Transformations of random variables 492. 6. 1 Linear transformations 492.6.2 General transformations 502.6.3 Central limit theorem 512.7 Monte Carlo approximation 522.7.1 Example: change of variables, the MC way 532.7.2 Example: estimating T by Monte Carlo integration2.7.3 Accuracy of Monte Carlo approximation 542.8 Information theory562.8.1Entropy2.8.2 KL dive572.8.3 Mutual information 593 Generative models for discrete data 653.1 Introducti653.2 Bayesian concept learning 653.2.1Likelihood673.2.2 Prior 673.2.3P683.2.4Postedictive distribution3.2.5 A more complex prior 723.3 The beta-binomial model 723.3.1 Likelihood 733.3.2Prior743.3.3 Poster3.3.4Posterior predictive distributionCONTENTS3.4 The Dirichlet-multinomial model 783. 4. 1 Likelihood 793.4.2 Prior 793.4.3 Posterior 793.4.4Posterior predictive813.5 Naive Bayes classifiers 823.5.1 Model fitting 833.5.2 Using the model for prediction 853.5.3 The log-sum-exp trick 803.5.4 Feature selection using mutual information 863.5.5 Classifying documents using bag of words 84 Gaussian models4.1 Introduction974.1.1Notation974. 1.2 Basics 974. 1.3 MlE for an mvn 994.1.4 Maximum entropy derivation of the gaussian 1014.2 Gaussian discriminant analysis 1014.2.1 Quadratic discriminant analysis(QDA) 1024.2.2 Linear discriminant analysis (LDA) 1034.2.3 Two-claSs LDA 1044.2.4 MLE for discriminant analysis 1064.2.5 Strategies for preventing overfitting 1064.2.6 Regularized LDA* 104.2.7 Diagonal LDA4.2.8 Nearest shrunken centroids classifier1094.3 Inference in jointly Gaussian distributions 1104.3.1Statement of the result 1114.3.2 Examples4.3.3 Information form 1154.3.4 Proof of the result 1164.4 Linear Gaussian systems 1194.4.1Statement of the result 1194.4.2 Examples 1204.4.3 Proof of the result1244.5 Digression: The Wishart distribution4.5. 1 Inverse Wishart distribution 1264.5.2 Visualizing the wishart distribution* 1274.6 Inferring the parameters of an MVn 1274.6.1 Posterior distribution of u 1284.6.2 Posterior distribution of e1284.6.3 Posterior distribution of u and 2* 1324.6.4 Sensor fusion with unknown precisions 138
- 2020-12-10下载
- 积分：1
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简单的基于MATLAB的手势识别
手势识别源代码,对学习手势识别的同学很有帮助,点匹配方法 简单的手势识别matlab代码,代码可以运行，可以作为入门之用。-gestures detection 内含剪刀石头布三种图片，根据摄像头采集到的手势，来和图片手势进行匹配，进而识别。 关键技术 应用数字图像处理相关技术 图像分割 边缘检测 模版匹配
- 2020-12-12下载
- 积分：1
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可随时控制的SWF播放器
一款swf播放器，对swf格式的文件，尤其是视频播放可以进行精确控制播放、暂停、快进等，swf大多是矢量格式，播放起来更是无损，新的福利
- 2020-12-11下载
- 积分：1
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MATLAB通信工程仿真源代码 张德峰
MATLAB通信工程仿真源代码 张德峰
- 2020-12-11下载
- 积分：1
