OD终结版加强版

TMS320F28335例程，内容丰富，满足入门级学习需要，并且还有清晰的注释，方便学习

用C语言实现密码学中的快速取模算法源代码

使用VC++编写的串口示波器，代码简洁，容易移植，需要的可以根据自己的需求进行修改，默认波特率为9600，通讯口为COM1口，16位16进制显示，进行了数据转换，在另一个框内显示double型，可以用做单片机AD数据采集系统的上位机，个人可以根据自己需求修改。

原博客地址：http://blog.csdn.net/frank3543/article/details/45042977测试可使用，方便大家，有什么问题的请指出。我是qt5，配置照着项目应该没问题。

这是最新的emd去噪的程序，并且有和小波去噪的比较。采用的是符合emd分解特性的阈值去噪方法。

密码算法主要分为四大部分，分别是分组密码、公钥密码、Hash算法和数字签名算法，其中分组密码包括DES、AES和SM4算法；公钥算法包括RSA公钥密码算法、ECC密码算法和SM2密码算法；Hash算法包括SHA-1算法、SHA-3算法和SM3算法；数字签名算法包括ECC签名算法和DSA签名算法。

在国外大学的网页上下载的，mean shift用于分割，分类图像。大家都知道 mean shift算法的应用领域是很广泛的，在跟踪，分割方面效果还是不错的。所以嘛，下载看看喽！

【实例简介】雷达信号集锦：文档+matlab仿真 常规雷达信号、 相位编码信号、 线性调频信号、 非线性调频信号（S型、正弦型、正切型） 噪声调幅、调频、调相干扰信号

LogViewPro中文版 超大文本文件打开利器 不论多少G的文本文件 全部秒开，秒杀ultraedit 等一切自称能够秒开的程序。

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