hfss 天线模型 22种

这是研究惯性导航的最好代码。记得自己添加测试数据。此为基于四元素法，角增量法的捷连惯导系统程序算法，飞行器飞行过程中飞行高度不变， 航向角以逆时针为正。以地理系为导航坐标系 ，运行程序时需导入比力信息及陀螺议角速率信息。

蜂窝网络TDOA定位方法的Fang算法研究及matlab仿真

微电子电路设计第五版,Richard C. Jaeger, Traveis N. Blalock编著。FIETH EDITIONMICROELECTRONICHM-M- CIRCUIT DESIGNRICHARD C. JAEGERAuburn UniversityTRAVIS N. BLALOCKUniversity of VirginiaMcGrawEducationGrawEducationMICROELECTRONIC CIRCUIT DESIGN. FIFTH EDITIOPublished by McGraw-Hill Education, 2 Penn Plaza, New York, NY 10121 CopyrightC 2016 by McGraw-Hill EducationAll rights reserved. Printed in the United States of America. Previous editions 2011, 2008, and 2004. No part of thispublication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system,without the prior written consent of McGraw-Hill Education, including, but not limited to, in any network or otherelectronic storage or transmission, or broadcast for distance learninSome ancillaries, including electronic and print components, may not be available to customers outside the United StatesThis book is printed on acid-free pape1234567890DOw/DOw1098765ISBN978-0-07-352960-8MHID0-07-352960-5sident Products markets Kurt LVice President, General Manager, Products Markets: Marty Langece President, Content Design Delivery: Kimberly Meriwether DavidManaging director: Thomas TimpGlobal Publisher Raghu srinivasanDirector. Prodrelopment: RoDirector, Digital Content Development: Thomas Scaife, Ph DProduct develoVincent brashMarketing manager: Nick Mc faddenDirector, Content Design Delivery: Linda avenariusProgram meSchillingContent Project Managers: Jane Mohr, Tammy Juran, and Sandra M. SchneeBuyer: Jennifer PickelDesign: Studio Montage, St Louis, MOContent Licensing Specialist: DeAnna DausenerCompositor: MPS LimitedPrinter.R. DonnellAll credits appearing on page or at the end of the book are considered to be an extension of the copyright pageLibrary of Congress Cataloging-in-Publication DataJaeger. Richard cMicroelectronic circuit design/Richard C. Jaeger, Auburn University,Travis N. Blalock, University of Virginia. --Fifth editionpages cmIncludes bibliographical references and indexISBN978-0-07-352960-8(alk. paper)-ISBN0-07-338045-8(alk. paper)d 1. Integrated circuits--Design and construction. 2. Semiconductors--Design and construction. 3. Electronic circuitesign. I. Blalock, Travis N. Il. TitleTK7874.J3332015621.3815-dc232014040020The Internet addresses listed in the text were accurate at the time of publication. The inclusion of a website does not indicatean endorsement by the authors or McGraw-Hill Education, and McGraw-Hill Education does not guarantee the accuracy ofthe information presented at these siteswww.mhhe.comTOTo Joan, my loving wife and life long partnerRichard C. JaegerIn memory of my father, Professor Theron vaughnBlalock, an inspiration to me and to the countlessstudents whom he mentored both in electronicdesign and in life.Travis n blalockBRIEF CONTENTSPreface xxChapter-by-Chapter Summary XXV12 Operational Amplifier Applications 685PART ONE13 Small-Signal Modeling and LinearSOLID-STATE ELECTRONICS AND DEVICESAmplification 77014 Single-Transistor Amplifiers 8411 Introduction to Electronics 32 Solid-State Electronics 4115 Differential Amplifiers and Operational Amplifier3 Solid-state Diodes and Diode circuits 72Design 9524 Field-Effect Transistors 14416 Analog Integrated Circuit Design Techniques 10315 Bipolar Junction Transistors 21517 Amplifier Frequency Response 111318 Transistor Feedback Amplifiers andPART TWOOscillators 1217DIGITAL ELECTRONICSAPPENDICES6 Introduction to Digital Electronics 2837 Complementary MOS (CMOS) Logic Design 359A Standard Discrete Component Values 12918 MOS Memory Circuits 414B Solid-State Device Models and sPIce simulationParameters 12949 Bipolar Logic Circuits 455C TWo-Port Review 1299PART THREIndex 1303ANALOG ELECTRONICS10 Analog Systems and Ideal OperationalAmplifiers 51711 Nonideal Operational Amplifiers and FeedbackAmplifier Stability 587CONTENTSPreface xxCHAPTER 2Chapter-by-Chapter Summary XXVSOLID-STATE ELECTRONICS 41PART ONE2.1 Solid-State Electronic materials 432.2 Covalent bond model 44SOLID-STATE ELECTRONICS2.3 Drift Currents and mobility inAND DEVICES 1Semiconductors 472.3.1 Drift Currents 47CHAPTER 12.3.2 Mobility 48INTRODUCTION TO ELECTRONICS 32.3.3 Velocity Saturation 482.4 Resistivity of Intrinsic Silicon 491.1 A Brief History of Electronics: From2.5 Impurities in Semiconductors 50Vacuum Tubes to Giga-Scale Integration 52.5.1 Donor Impurities in silicon 511.2 Classification of Electronic Signals 82.5.2 Acceptor Impurities in Silicon 511.2.1 Digital signals 92.6 Electron and hole concentrations in1.2.2 Analog Signals 9Doped semiconductors 511.2.3 A/D and D/A Converters--Bridging2.6.1Type Material (ND >NA)52the analog and Digital2.6.2 p-Type Material (N,A>ND)53Domains 102.7 Mobility and Resistivity in Doped1.3 Notational conventions 12Semiconductors 541.4 Problem-Solving Approach 132.8 Diffusion currents 581.5 Important Concepts from Circuit2. 9 Total Current 59Theory 152.10 Energy Band Model 601.5.1 Voltage and current Division 152.10.1 Electron-Hole pair generation in1.5.2 Thevenin and norton circuitan intrinsic semiconductor 60Representations 162.10.2 Energy Band Model for a Doped1.6 Frequency Spectrum of ElectronicSemiconductor 61Signals 212.10.3 Compensated semiconductors 611.7 Amplifiers 222.11 Overview of Integrated circuit1.7.1 Ideal operational amplifiers 23Fabrication 631.7.2 Amplifier Frequency Response 25Summary 661.8 Element Variations in Circuit Design 26Key Terms 671.8.1 Mathematical modeling ofReference 68Tolerances 26Additional Reading 681.8.2 Worst-Case Analysis 27Problems 688.3 Monte Carlo analysis 291.8.4 Temperature Coefficients 32CHAPTER 31.9 Numeric Precision 34SOLID-STATE DIODES AND DIODE CIRCUITS 72Summary 34Key Terms 353.1 The pn Junction Diode 73References 363.1.1 pn Junction Electrostatics 73Additional Reading 363.1.2 nternal diode currents 77Problems 363.2 The i-v Characteristics of the diode 78VIllContents3.3 The Diode Equation: A Mathematica3.15 Full-Wave Bridge Rectification 123Model for the diode 803.16 Rectifier Comparison and Design3.4 Diode Characteristics under reverse, ZeroTradeoffs 124and forward bias 833.17 Dynamic Switching Behavior of the Diode 1283.4.1 Reverse bias 833.18 Photo diodes, solar cells, and3. 4.2 Zero bias 83Light-Emitting Diodes 1293.4.3 Forward Bias 843.18.1 Photo diodes and3.5 Diode Temperature Coefficient 86Photodetectors 1293.6 Diodes under reverse bias 863.18.2 Power Generation from Solar Cells 1303.6.1 Saturation Current in real3.18. 3 Light-Emitting Diodes(LEDs)13Diodes 87Summary 1323.6.2 Reverse Breakdown 89Key Terms 1333.6.3 Diode model for the breakdownReference 134Region 90Additional Reading 1343.7 pn Junction Capacitance 90Problems 1343.7.1 Reverse bias 903.7.2 Forward Bias 91CHAPTER 43.8 Schottky Barrier Diode 933.9 Diode SPICE Model and layout 93FIELD-EFFECT TRANSISTORS 1443.9.1 Diode Layout 944.1 Characteristics of the MOS Capacitor 1453.10 Diode Circuit Analysis 954.1.1 Accumulation Region 1463.10.1 Load-Line Analysis 964.1.2 Depletion Region 1473.10.2 Analysis Using the Mathematical4.1.3 Inversion Region 147Model for the diode 974.2 The nmos transistor 1473.10.3 The Ideal diode model 1014.2.1 Qualitative i-v Behavior of the3.10.4 Constant Voltage Drop Model 103NMOS Transistor 1483.10.5 Model Comparison and4.2.2 Triode Region Characteristics ofDiscussion 104the nmos transistor 1493.11 Multiple-Diode Circuits 1054.2.3 On Resistance 1523.12 Analysis of Diodes Operating in the4.2.4 Transconductance 153Breakdown Region 1084.2.5 Saturation of the i-v3.12.1 Load-Line Analysis 108Characteristics 1543.12.2 Analysis with the Piecewise4.2.6 Mathematical model in theLinear model 108Saturation (Pinch-off)3.12.3 Voltage regulation 109Region 1553.12.4 Analysis Including Zener4.2.7 Transconductance in saturation 156Resistance 1104.2.8 Channel-Length Modulation 1563.12.5 Line and Load Regulation 1114.2.9 Transfer characteristics and3.13 Half-Wave Rectifier Circuits 112Depletion-Mode MosFETs 1573.13.1 Half-Wave Rectifier with resistor4.2.10 Body Effect or SubstrateLoad 112Sensitivity 1593.13.2 Rectifier Filter Capacitor 1134.3 PMOS Transistors 1603.13.3 Half-Wave Rectifier with rc load 1144.4 MOSFET Circuit Symbols 1623. 13.4 Ripple Voltage and Conduction4.5 Capacitances in MOS Transistors 165Interval 1154.5.1 NMOs Transistor Capacitances in3.13.5 Diode Current 117the Triode region 1653.13.6 Surge Current 1194.5.2 Capacitances in the Saturation3.13.7 Peak-Inverse-Voltage(PlV)Rating 119Region 1663.13.8 Diode Power Dissipation 1194.5.3 Capacitances in Cutoff 1663.13.9 Half-Wave Rectifier with Negative4.6 MOSFET Modeling in SPICE 167Output Voltage 1204.7 MOS Transistor Scaling 1683.14 Full-Wave Rectifier Circuits 1224.7.1 Drain Current 1693. 14.1 Full-Wave Rectifier with Negative4.7.2 Gate Capacitance 169Output Voltage 1234.7.3 Circuit and power densities 169ContentsIX4.7.4 Power-Delay Product 1705.3 The pnp Transistor 2234.7.5 Cutoff Frequency 1705.4 Equivalent Circuit Representations for the4.7.6 High Field Limitations 171Transport Models 2254.7.7 The unified mos transistor model5.5 The i-v Characteristics of the bipolarIncluding High Field Limitations 172Transistor 2264.7.8 Subthreshold conduction 1735.5.1 Output Characteristics 2264.8 MOs Transistor Fabrication and layout5.5.2 Transfer characteristics 227Design Rules 1745.6 The Operating Regions of the Bipolar4.8.1 Minimum Feature size andTransistor 227Alignment Tolerance 1745.7 Transport Model Simplifications 2284.8.2 Mos Transistor Layout 1745.7.1 Simplified Model for the Cutoff4.9 Biasing the NMOS Field-EffectRegion 229Transistor 1785.7.2 Model Simplifications for the4.9.1 Why Do We Need Bias? 178Forward-Active Region 2314.9.2 Four-Resistor Biasing 1805.7.3 Diodes in Bipolar Integrated4.9.3 Constant Gate-Source VoltageCircuits 237Bias 1845.7.4 Simplified Model for the4.9.4 Graphical analysis for theReverse-Active Region 238Q-Point 1845.7.5 Modeling Operation in the4.9.5 Analysis Including Body Effect 184Saturation Region 2404.9.6 Analysis Using the Unified5.8 Nonideal Behavior of the bipolarModel 187Transistor 2434.10 Biasing the PMos Field-Effect Transistor 1885.8.1 Junction Breakdown Voltages 2444.11 The junction Field-Effect Transistor5.8.2 Minority-Carrier Transport in theUFET190Base Region 2444.11.1 The JFET With Bias Applied 195.8.3 Base Transit time 2454.11.2 JFET Channel with Drain-Source5.8.4 Diffusion Capacitance 247Bias 1935.8.5 Frequency Dependence of the4.11.3 n-Channel jfet i-v Characteristics 193Common-Emitter current gain 2484.11.4 The p-Channel JFET 1955.8.6 The Early Effect and Early4.11.5 Circuit Symbols and JFET ModelVoltage 248Summary 1955.8.7 Modeling the Early Effect 2494.11.6 JFET Capacitances 1965.8.8 Origin of the Early Effect 2494.12 JFET Modeling in Spice 1965.9 Transconductance 2504.13 Biasing the JFET and Depletion-Mode5.10 Bipolar Technology and sPiCe Model 251MOSFET 1975.10.1 Qualitative Description 251Summary 2005.10.2 SPICE Model Equations 252Key Terms 2025.10.3 High-Performance BipolarReferences 202Transistors 253Problems 2035.11 Practical bias circuits for the bjt 2545.11.1 Four-Resistor bias network 256CHAPTER 55.11.2 Design Objectives for theBIPOLAR JUNCTION TRANSISTORS 215Four-Resistor bias network 2585.11.3 terative Analysis of the5.1 Physical Structure of the BipolarFour-Resistor bias circuit 262Transistor 2165.12 Tolerances in bias circuits 2625.2 The Transport Model for the npn5. 12.1 Worst-Case Analysis 263Transistor 2175. 12.2 Monte Carlo Analysis 2655.2.1 Forward Characteristics 218Summary 2685.2.2 Reverse Characteristics 220Key Terms 2705.2.3 The Complete Transport ModelReferences 270Equations for Arbitrary BiasProblems 271Conditions 221

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本文档较为详细的介绍了多相滤波器的概念以及一种新的简化方法

程序中使用ACCESS数据库来保存数据，使用LabSQL工具包来连接数据库，打开之前请确认安装了这个工具包。程序一运行时会先弹出密码登录系统，用户名和密码都为“vihome”。这个程序实现的功能或者说使用到的知识点还是比较多的，主要有以下几种：1，简单的密码登录。 之前已经上传过一个密码登录的程序了，这里只是很简单的一个登录判断，有些会员不了解怎么样从密码程序到主程序的转换，这里是直接调用，如果在密码登录时选择取消，则通过输出错误的方法使主程序不执行而直接退出。2，简单的错误处理。 会对错误进行提示，发生错误时用户可以选择继续或停止，如果在调试时记录一些

【实例简介】蓝牙PIF天线和蛇形PCB天线设计指导 蓝牙PIF天线和蛇形PCB天线设计指导

php网络直播聊天室源码财经直播聊天室系统喊单直播间系统源码

SVM的两个例子（详细，有实验报告），这是之前找资料的时候花了很多积分下载的，我觉得还是蛮有用的，至少比网上很多人的没有用的错的代码强的多，这是SVM的分类，有对文本的分类，还有SVM最基础的例子。

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