ADC采集数据存储SD卡和读取示例程序

使用单层感知器网络解决与逻辑问题，也是很简单的神经网络程序，帮助大家理解算法。有问题的话希望和大家一起讨论。

600 多种协议的抓包,可以直接使用wireshark 打开

【内容介绍】 本书以仿真应用为中心，系统、详细地讲述了过程控制系统的仿真，并结合MATLAB/Simulink仿真工具的应用，通过大量经典的仿真实例，全面讲述过程控制系统的结构、原理、设计和参数整定等知识。 全书分为基础篇、实战篇和综合篇。基础篇包括过程控制及仿真概述、Simulink仿真基础、Simulink高级仿真技术，以及过程控制系统建模；实战篇包括PID控制、串级控制、比值控制、前馈控制、纯滞后和解耦控制系统；综合篇包括典型过程控制系统及仿真。 本书的特点是理论与仿真紧密结合，用仿真实例说话，通过仿真来加深对过程控制理论的理解，帮助读者掌握过程系

基于MATLAB 的直接序列扩频通信系统性能仿真分析研究基于Simulink的直接序列扩展频谱通信系统仿真研究基于MATLAB 的扩频通信系统仿真研究扩频通信系统及MATLAB 仿真直接序列扩频通信系统建模仿真分析直接序列扩频通信系统误码率的仿真分析

MSP430最小系统开发板，包括原理图和PCB，适合初学者

网上很多深度学习C++源码下载后都无法使用，总是有这样活那样的错误，但本源码可定好用，只要装了VS 2013就行，没用第三方库。这是一个深度学习--深度信念网络(Deep Belief Network)的C++源码，例子中带有数据，直接编译就可以使用，也可以断点调试，非常方便。

严格按照MODBUS协议实现的C代码，内有详细的移植说明。和使用说明。同时支持主站从站

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

实战Matlab之并行程序设计pdf及其代码

图像压缩算法JPEG基于DCT图像压缩算法JPEG基于DCT图像压缩算法JPEG基于DCT图像压缩算法JPEG基于DCT