图像处理---关于像素坐标矩阵变换(平移，旋转，缩放，错切)

深度学习标注工--LabelImage 解压之后运行目录下的labelImg.py即可。

基于卷积神经网络的图像识别 基于卷积神经网络的图像识别关于学位论文独创声明和学术诚信承诺本人向河南大学提出硕士学位申请。本人郑重声明:所呈交的学位谂文是本人在导师的指导下独立完成的,对所研究的课题有新的见解。据我所知,除文中特别加以说明标注和致谢的地方外,论文中不包括其它人已经发表或撰写过的研究成果,也不包括其它人为获得任何教育、科研机构的学位或证书而使用过的材料。与我一同工作的同事对本研究所做的任何贡献均己在论文中作了明确的说明并表示了谢意在此本人郑重承诺:所呈交的学位论文不存在舞弊作伪行为,文责自负。学位申请人(学位论文作者)签名:亚强2015年5月20日关于学位论文著作权使用授权书本人经河南大学审核批准授予硕士学位。作为学位论文的作者,本人完全了解并同意河南大学有关保留、使用学位论文的要求,即河南大学有权向国家图书馆、科研信息机构、数据收集机构和本校图书馆等提供学位论文(纸质文本和电子文本)以供公众检索、查阅。本人授衩河南大学出于宣扬、展览学校学术发展和进行学术交流等目的,可以采取影印、缩印、扫描和拷贝等复制手段保存、汇编学位论文(纸质文本和电子文本)(涉及保密内容的学位论文在解密后适用本授权书)学位获得者(学位论文作者)签名:卫2015年5月20日学位论文指导教师签名:2015年5月20日摘要Deep learning是机器学习研究的新领域,掀起了机器学习的新浪潮,在各个行业都受到了广泛的关注。 Google brain项目、微软全自动同声传译系统、百度硏究院等都是 deep learning技术发展的见证。随着大数据和深度模型时代的来临,deeplearning技术也得到了广泛的重视和发展,它带来的技术进步也必将改变人们的生活随着机器学习领域的发展,最近几年对卷积神经网络的研究也越发深入。现在卷积神经网络已经广泛的应用到各种领域,并取得了巨大的成果。卷积神经网络是在人工神经网络的基础上发展起来的·种高效的识别算法。典型的积网络结构是由 Lecrn提出的 LeNe t-5,它包含多个阶段的卷积和抽样过程,然后将提取到的特征输入到全连接层进行分类结果的计算。卷积神经网络通过特征提取和特征映射过程,能够较好的学习到图像中的不变特征。现在研究人员在典型的 LeNet5的基础上,使用多种方法改善卷积网终的结构和性能,从而提高网终的通用性和对图像的识别效果。本文结合图像的特点,在深入硏究了卷积网络的理论和国内外研究成果的基础上主要做了以下工作:(1)研究了卷积网络的训练算法,通过对算法分析,调试并找到最优初始化参数和最适应的网络结构配置。(2)对于分类结果的计算,使用了多区域的测试方法,通过在测试的过程中对图像的多个区域进行计算能够提高图像识别的准确率。〔3)为系统设计了一个通用的数据集输入接口,可以将自己构建的图像薮据集输入到卷积神经网络的结构中,训练和查看图像分类的结果。(4)在卷积层使用了局部偏差垬亨和非共亨两种方法,在数据集上测试并进行结果分析。(5)在隐含层使用了网络泛化的方法 DROPOUT,在数据集上测试并进行结果分析。通过以上改进方法的使用,卷积网络的通用性和性能得到了提高。关键词:,图像识别,特征提取

fpga万年历设计，本文详细介绍万年历的设计过程，可以显示时间日期，还可以调整时间日期等功能。（1）显示准确的北京时间（年、月、日、时、分、秒，年号只显示最后两位）（2）随时可以调校时间即可以控制年、月、日、时、分的变化，可以跳到指定的时间。

Java注释：1、//……         单行注释2、/*……*/     多行注释3、/**            文档注释    *……    */    JavaScript和CSS注释：1、//……         单行注释2、/*……*/     多行注释HTML注释：1、2、//注释内容     （在css或javascript中插入单行注释）3、/*注释内容*/   （在css或javascript中插入多行注释)JSP注释  1> 显示注释          在显式注释中，注释部分可以使用表达式，因为显式注释会被JSP引擎解释; 在客户端     HTML文件的源代码中生成同样的注释信息，但不会在HTML页面上显示      如：      在客户端HTML文件的源代码中生成如下注释:            2> 隐式注释          隐式注释和显式注释一样不能在JSP页面显示， 但是隐式注释不能在客户端HTML文件的     源代码中生成同样的注释信息,也不能使用表达式；scriptlet    在 JSP Scriptlet 里可直接嵌入任何有效的java语言代码。可以在 scriptlet 内部可以使用java注释 //、/* .... */、/** .... */声明    在声明部分可以声明变量和方法，它们只当前JSP页面有效。表达式        在之间的表达式会被转化为字符串并显示在网页上。指令    JSP指令用于设置和整个JSP页面相关的属性，如页面的编码方法、包含文件以及是否为错误页面等。  MySQL注释：1、#……        单行注释2、-- ……        单行注释，两杆之后要加个空格3、/*……*/        多行注释SQLServer注释：--……        单行注释，两杆不用加空格PHP注释：1、//……         单行注释2、/*……*/     多行注释3、/**            块注释    *……    */4、/**            特别格式的块注释    *……    */

CH341驱动Win7,Win8,Win10.rar USB转串口CH341/CH340的WINDOWS驱动程序安装包 支持WINDOWS 98/ME/2000/XP/Server 2003/VISTA/ Server 2008/Win7/Win8/Win10 32位/64位，通过微软数字签名认证， 在计算机端将USB设备仿真为标准Serial串口设备COM? 包含识别CH34X串口号及监视CH34X设备插拔的库

目录1. 向量、矩阵对元素求导 21.1 行向量对元素求导 21.2 列向量对元素求导 21.3 矩阵对元素求导 22. 元素对向量、矩阵求导 32.1 元素对行向量求导 32.2 元素对列向量求导 32.3 元素对矩阵求导 33. 向量对向量求导 43.1 行向量对列向量求导 43.2 列向量对行向量求导 43.3 行向量对行向量求导 43.4 列向量对列向量求导 44. 矩阵对向量求导 54.1 矩阵对行向量求导 54.2 矩阵对列向量求导 55. 矩阵对向量求导 65.1 行向量对矩阵求导 65.2 列向量对矩阵求导 65.3 矩阵对矩阵求导 6

5G无线通信系统关键技术（剑桥大学出版社） 2017年出版 对于5G所有最新技术进行了详细说明 很全的工具书Key Technologies for5G Wireless SystemsVINCENT W. S, WONGUniversity of British ColumbiaROBERT SCHOBERUniversity of Erlangen-NurembergDERRICK WING KWAN NGUniversity of New South WalesLI-CHUN WANGNational Chiao-Tung University即CAMBRIDGEUNIVERSITY PRESSCAMBRIDGEUNIVERSITY PRESSUniversity Printing House. Cambridge CB2 SBS. United KindomOne Liberty Plaza, 20h Floor New York, NY I(H0X, USA477 williamstown Road, port Melbourne, yic 3207 australia48424, 2nd Floor, Ansar Rod, Daryaganj. Delhi- I l4XH2, India79 Anson Road, #o6-(/ 00, Singapore 079%MCambridge University Press is part of the Lniversity of CambridgeIt furthers the University s mission by disseminating knowledge in the pursuit ofeducation, leaming and research at the highest international levels of excellence.www.cermbrid吧eInformtiononthistitlewww.cambridgeorg/978110713241810,1017③781316771655C Cambridge University Press 2017This puhlication is in copyright. Subjcct to sututonry exceptionand to the provisions of relewant collective licensing agreementsno reproduction of any part may take place without the writtenpermission of Cutmbridgre University Press.First published 2(117Printed in the United Kingdom by TJ International Ltd. Padstow, CornwallA catalogue recor for this pudlieafiove is aailable fromm the British LibraryLibrary of Congress Cataloging- in Pi hlicaiomz dataNames: Wong, Vincent W.S., editorTitle: Key technologies for 5G wireless systems/edited by Vincent W.S. Wong [and 3 otherOther titles key technologies for five g wireless svstemsDescription: Carmbrisige: New York, NY: Cambridge Lniversity Press, 2017.Identifiers: l CCN 2016045220)1 ISBN 9781 172418 (hardback)Subjects: LCSH: Wireless communication systems, I Machine-to-machinecommunications. Internet of things.Classitication: LCC TKs1032K49 2(17 DDC 621.38450-dc23LcrecordavailaBleathttps://lccnioc-gov/2016m5220)ISBN 978-1-107-17241- HardbackCambridge University Press has no responsibility for the persistence or accuracy ofURLs for extermal or third-party Internet websites referred to in this puhlication,and does not guarantee that any content on such websites is, or will remainaccurate of appropriateContentsList of Contributorspage xvIPrefaceKXIOverview of New Technolog ies for 5G SystemsVincent W S, Wong, Robert Schober, Derrick Wing Kwan Ng, and Li-Chun Wang1.1 Introduction1.2 Cloud Radio Access Networks1.3 Cloud Computing and Fog Computing1. 4 Non-orthogonal Multiple Access1. 5 Flexible Physical Layer Design334.4671. 6 Massive MIMo1. 7 Full-Duplex Communications1. 8 Millimeter wave1.9 Mobile Data Offloading, LTE-Unlicensed, and Smart Data Pricing131. 10 IoT M2M. and D2D1. I1 Radio Resource Management, Interference Mitigation, and Caching61. 12 Energy Harvesting Communications1. 13 Visible Light Communication19Acknowledgments20ReferencesPart I Communication Network Architectures for 5G Systems25Cloud Radio Access Networks for 5G Systems27Chih-Lin I, Jinn Huang, Xueyan Husang, Rongwved Ren, and Yami. Chen2.1 Rethinking the Fundamentals for 5G Systems272 User- Centric Networks2923 C-RAN Basics292.3.1 C-RAN Challenges Toward SGI302.4 Next Generation Fronthaul Interface (NGFI: The FH Solutionfor SGC-RAN312. 4.1 Proof-of-Concept Development of NGFI33Contents2.5 Proof-of-Concept Verification of Virtualized C-RAN2.5.1 Data packets3725.2 Test Procedure382.5.3 Test Results392. 6 Rethinking the Protocol Stack for C-RAN2.6.1 Motivation402.6.2 Multilevel Centralized and Distributed Protocol Stack402.7 Conclusion45AcknowledgmentsReferencesFronthaul-Aware Design for Cloud Radio Access Networks48Liang Liu, Wei Yu, and Osvaldo Simeone3. 1 Introduction483.2 Fronthaul-Aware Cooperative Transmission and Reception493. 2.1 Uplink513.2.2 Downlink573.3 Fronthaul-Aware Data Link and Physical layers61.3. I Uplink633.3.2 Downlink693.4 Conclusion73Acknowledgments74References74MobEdge computing76Ben Liang4.1 Introduction764.2 Mobile Edge Computing774.3 Reference architecture794.4 Benefits and Application Scenarios804 4.1 User-Oriented Use cases4. 4.2 Operator-Oriented Use Ca814 5 Research challenges824.5.1 Computation Offloading824.5.2 Communication Access to Computational Resources834.5.3 Multi-resource Schedulin844.5 4 Mobility Management854.5.5 Resource Allocation and Pricing4.5.6 Network functions virtualization864.5, 7 Security and Pri864.5.8 Integration with Emerging Technologies874.6 Conclusion88ReferencesContentsDecentralized Radio Resource Management for Dense HeterogeneousWireless networksAbolfazl Mehhodniya and Fumiyuki Adach5.1 Introduction925.2 System Model935.2.1 SINR Expression5.2.2 Load and Cost Function Expressions955.3 Joint BSCSA/UECSA ON/OFF Switching Scheme965.3.1 StrateTy Selection and Beacon Transmission53.2 UE AssocIation5.3.3 Proposed Channel Segregation Algorithms985.3.4 Mixed-Strategy Update3.4 Computer Simulation5.5 Conclusion104Acknowledgments04References105Part ll Physical Layer Communication Techniques107Non-Orthogonal Multiple Access(NOMA)for 5G Systems109Wei Llang, Zhiguo Ding, and H. Vincent Poor6.1 Introduction1106.2 NOMA in Single-Input Single-Output(SISO)Systems1126.2.1 The basics of nomaI126. 2. 2 Impact of User Pairing on NOMA136.2,3 Cognitive Radio Inspired NOMA6. 3 NOMA in MIMO Systems1206.3.1 System Model for MIMO-NOMA Schemes1216.3.2 Design of Precoding and Detection Matrices with Limited CSIT 1236.3.3 Design of Precoding and Detection Matrices with Perfect CSIT 1266.4 Summary and Future Directions128ReferencesFlexible Physical Layer Design133Maximilian Matthe, Martin Danneberg, Dan Zhang, and Gerhard Fettweis7.1 Introduction1337. 2 Generalized Frequency Division Multiplexing357.3 Software-Defined waveform1377. 3. 1 Time Domain Processing1387.3.2 Implementation Architecture1387.4 GFDM Receiver Design14174 Synchronization unit1427. 4.2 Channel Estimation Unit1474.3 MIMo-GFDM Detection Unit145Contents7.5 Summary and Outlook147Acknowledgments148References488Distributed Massive MIMO in Cellular Networks15IMichail Matthaiou and Shi Jin8. I Introduction15l8. 2 Massive MIMO: Basic Principles1528.2.1 Uplink Downlink Channel Models1538.2.2Favorable Propagation1548.3 Performance of Linear Receivers in a Massive MIMO Uplink1548.4 performance of linear precoders in a massive mimo downlink1578. s Channel estimation in massive mimo systems1588.5.1 Uplink Transmission1598.5.2 Downlink Transmission1608.6 Applications of Massive MIMO Technology1618.6.1 Full-Duplex Relaying with Massive Antenna Arrays1618.6.2 Joint Wireless Information Transfer and Energy Transfer forDistributed massive mimo1638.7 Open Future Research Directions1678. 8 Conclusionl68References169Full-Duplex Protocol Design for 5G Networks172Tanelf Ahonen and Risto wichman9.1 Introduction1729. 2 Basics of Full-Duplex Systems1739.2.1 In-Band Full-Duplex Operation Mode1739.2.2 Self-Interference and Co-channel Interference1749.2.3 Full-Duplex Transceivers in Communication Links1759. 2. 4 Other Applications of Full-Duplex Transceivers1789.3 Design of Full-Duplex Protocols1799.3, 1 Challenges and Opportunities in Full-Duplex Operation1799.3.2 Full-Duplex Communication Scenarios in 5G NetworksR9.4 Analysis of Full-Duplex Protocols1829.4.1 Operation Modes in Wideband Fading Channels1829. 4, 2 Full- Duplex Versus Half-Duplex in Wideband Transmission1849.5 Conclusion1849.5.1 Prospective Scientific Research DirectionsI849.5.2 Full-Duplex in Commercial 5G Networks185RLItrtncekl8610Millimeter Wave Communications for 5G Networks188Jiho Song, Miguel R Castellanos, and David J. LoweContentsⅸx10.1 Motivations and Opportunities18810.2 Millimeter Wave Radio Propagation18910. 2.1 Radio Attenuation1890. 2. 2. Free-Space Path LOSs19I10.2.3 Severe shadow19310.2 4 Millimeter Wave Channel model19310.2.5 Link Budget Analysis19410.3 Beamforming Architectures19510.3, Analog beamforming solutions19610.3.2 Hybrid Beamforming Solutions20010.3.3 Low-Resolution Receiver Architecture2010.4 Channel Acquisition Techniques20110.4.1 Subspace Sampling for Beam Alignment20210.4.2 Compressed Channel estimation Techniques20510.5 Deployment Challenges and Applications20710.5.1 EM Exposure at Millimeter Wave Frequencies20710.5.2 Heterogeneous and Small-Cell Networks208Acknowledgments209References209Interference Mitigation Techniques for Wireless Networks214Koralia N Pappi and George K, Karag annidis1 1.1 Introduction21411.2 The Interference Management Challenge in the 5G vision21411. 2. 1 The 5G Primary Goals and Their Impact on Interference2141 1.2.2 Enabling Technologies for Improving Network Efficiencyand Mitigating Interference21611.3 Improving the Cell-Edge User Experience: Coordinated Multipoint218I 1.3.1 Deployment Scenarios and Network Architecture2181 13. 2 CoMP Techniques for the Uplink22011.3.3 CoMP Techniques for the Downlink2211 1.4 Interference Alignment: Exploiting Signal Space Dimensions2231 1.4.1 The Concept of Linear Interference Alignment224L1. 4.2 The Example of the X-Channel225I 1. 4.3 The K-User Interference Channel and Cellular NetworksAsymptotic Interference Alignment22611.4.4 Cooperative Interferenee Networks22711.4.5 Insight from IA into the Capacity Limits of Wireless Networks 22711.5 Compute-and-Forward Protocol: Cooperation at the ReceiverSide for the Uplink22811.5.1 Encoding and Decoding of the CoF Protocol22811.5.2 Achievable-Rate Region and Integer Equation Selection23011.5.3 Advantages and Challenges of the CoF Protocol232IL6 Conclusion233References233

包括两个主程序，分别执行JPEG编解码、给出相关参数结果。Jpeg没有对整体系数进行位移，而Jpeg2则在编码前，将整个数据减去128，这样可能可以提高性能。但是对这幅图像而言，Jpeg2性能比Jpeg稍有下降。

校园跑腿（后台+微信小程序）.zip

对想学习永磁电机控制的同学，无疑这是一份很好的学习资料。废话不多说，谁拥有谁知道。