《directshow实务精选》 光盘

双电机独立驱动电动车辆电子差速控制双电机独立驱动电动车辆电子差速控制双电机独立驱动电动车辆电子差速控制

Two Dimensional Phase Unwrapping Theory Algorithms and Software，扫描文档，清晰度一般。GTWO-DIMENSIONALPHASE UNWRAPPINGTHEORY ALGORITHMSAND SOFTWAREDennis C. ghigliaSandia National LaboratoriesAlbuquerque, New MexMark D. PrittLockheed Martin CorporationGaithersburg, Maryland藏A WILEY-INTERSCIENCE PUBLICATIONJOHN WILEY SONS, INCNew York Chichester Weinheim Brisbane Singapore / Toronto2005060radar interferogram generated byDeathon each pass, The terrain elevations can be computed from thebut the phase differences must fig problem In regions of steeprrupted where there are radar shadow and "layover"effects. Surfaceoccurred between the two passes, which were 24 days apar alsopThis image was acquired as part of a program for the Terrain Modeling Project Officended byEngineering Center. The SAR data was provided by Radarsat Intenational THinterferogram was generated and provided by Vexcel Corporation, Boulder, Coloradop00This text is printed on acid-free paper.Copyright o 1998 by John Wiley Sons, Inc. All rights reservedNo part of this publicationreproduced, stored in a retrievalsystem or transmitted in any form or by any means, elechanical photocopying, recording, scanning or otherwise,xcept as permitted under Sections 107 or 1O% of the 1976of the Publisher or authorization through payment of theontates Copyright Act, without cither theppropriate per-copy fee to the Copyright Clearance Center, 222750-4744. Requests to the Publisher for permission show(978)ood Drive, Danvers, MA 01923, (978)750-8400, faxnc.. 605 Third A venue. New York, NY 10158-0012(212)850-6011fax(212)850-6008,E-Mail:PERMREQ@WILEY.COMTwo-dimensional phase unwrapping: theory, algorithms, andsoftware/Dennis C Ghiglia and Mark D Pritt.SBN0-471-24935-1(cloth: alk. paper)1. Synthetic aperture radar. 2. Signal processing--Mathematics3. Interferometry. I Pritt. Mark D. [L. Title621.367-dc2l97-3803410987654321;4TWO-DIMENSIONALPHASE UNWRAPPINGFOREWORDTwo-dimensional phase unwrapping is the type of problem that is typically thedomain of the mathematician. It is both complex and abstract However, phaseunwrapping is also the core technology that enables radar interferometryOver the past decade interferometry has changed the way that we use radardata. Radar data are now used for precise measurement of surface topography inclouded regions. Additionally, spaceborne radar systems have proved effectivefor measuring surface changes from earthquakes and volcanic eruptions. Theseapplications have created a new class of radar data users primarily involved inmapping and remote sensing applicationIn Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Softwarethe authors unlock the mystery of phase unwrapping in interferometric datarocessing. This text provides a clear, concise treatment of phase unwrappingthat cannot be found in any other source. It presents for the first time therelationship between theory and application. Its uniform treatment of thevarious phase unwrapping techniques makes it a valuable resource for anyengineer or scientist involved in processing or exploitation of interferometricexpect that radar interferometry will increase in importance over the comingdecade with the development of airborne and spaceborne sensor systemsdesigned to optimally exploit this tcchnology. Two- Dimensionsping: Theory, Algorithms, and Software is an important contribution to ourinderstanding of radar interferometry that will bencfit both research intoadvanced techniques and the design of these future sensor systemsJOHN C. CURLANDEPresident and CEOVexcel CorporationPREFACETwo-dimensional phase unwrapping arises most naturally in, but is notrestricted to, interferometric applications. Measured or calculated phasevalues from two or more mutually coherent multidimensional signals are relatedn a nonlinear manner to a desired physical quantity of interest. The nonlinearityis in the form of"wraps"or cycle discontinuities where an underlying two-dimensional phase is wrapped into the interval (T, r. The wrapped phasemust somehow be unwrapped in order to provide an estimate of the underlyingphysical quantity. Estimation of surface topography from interferometricsynthetic aperture radar(SAR)or extremely accurate profiling of mechanicaparts by optical interferometers are two such examplesOriginally developed for military reconnaissance, SAR is now experiencingnew life in civil applications. In fact civilian and commercial interests are rapidlbecoming the drivers of technology. Clever utilization of the coherent SArimagery in interferometric configurations makes possible the measurement ofsurface topography to accuracies much better than the spatial resolution( 0.3meters to several meters)of the SaR images themselves. Indeed, as is commonplace with interferometers, measurement sensitivities are on the order of theoperating wavelength, which is typically a few centimeters for SAR. Imaginggeometries, noise, and other operational factors degrade performance some-what from centimeter-scale accuracies, but nevertheless SAR interferometrymakes possible global topographic mapping in a timely fashion, in daylight or atnight, in all weather conditions, and with unprecedented accuracyinterferometry also can detect deformations of the earths crust on the orderof millimeters, a capability that shows promise for the timely detection ofearthquakes or volcanic eruptionsThese exciting possibilities have led to an explosive growth in the field of phaseunwrapping as indicated by the increasing number of journal publicationsNewcomers to SAR interferometry and related disciplines will eventuallyonfront the phase unwrapping problem and, undoubtedly, will encounter arather bewildering variety of ideas and algorithms, including those based onneural networks, simulated annealing, cellular automata, genetic algorithms,and other unusual constructs. Which of these are good? Which are not? We doThroughout this book we use the notation(-丌,丌 to represent the interval-丌

包括风电场一年内的风速实测数据，并根据实测数据对风电场风速和输出功率进行预测和建模仿真，希望对大家有帮助

详细介绍了最优化方法，是学习最优化的比较好的参考讲义第一章引言第一章引言§1.1最优化问题概述学科简述最优化理论与方法:研究某些数学上定义的问题的最优解,即对于给出的实际问题,从众多的方案中选出最优方案。最优化是一门应用性很强的年轻学科。比如:●工程设计中怎样选择参数,使得设计既满足要求又能降低成本;资源分配中,怎样的分配方案既能满足各方面的基本要求,又能获得好的经济效益:生产计划安排中,选择怎样的计划方案才能提高产值和利润;·原料配比冋题中,怎样确定各种成分的比例才能提高质量、降低成本,最优化问题分类最优化问题分类表分类标志变量个数变量性质约束情况极值个数日标个数函数关系问题性质时间单变量连续无约朿单峰单目标线性确定性静态类型离散随机性多变量函数约束多峰多日标非线性模糊性动态比如:线性规划,非线性规划,随机规划,非光滑规划,多目标规划,整数规划,工作步骤:用最优化方法解决实际问题,一般经过下列步骤1.提出最优化问题,收集有关数据和资料2.建ν最优化问题的数学模型确定变量,列出目标函数和约束条件;3.分析模型,选择合适的最优化方法4.求解,一般通过编制程序,用计算机求最优解5.最优解的检验和实施上述5个步骤常常相互支持、相互制约,在实践中反复交叉进行。模型的三要素:1.变量:最优化问题中待确定的某些量;2.约束条件:求最优解时对变量的某些限制,包括技术上的约束、资源上的约束和时间上的约束等,用等式、不等式、或可行集表示;1.1最优化闩题概述3.目标函数:最优化评价标准的数学描述,一般用最大或最小表示。最优化方法:解析法,直接法,数值解法,二、线性与非线性规划问题例1.1.1[食谱问题设市场上可以买到n种不同的食品,每种食品含有m种营养成分.每单位的笫j种食品售价为c;,且含有第种营养成分为a;设每人每天对第种营养成分的需求量不少于b;,试确定在保证营养的要求下的最经济食谱建立数学模型(1)根据问题的需要设置变量:设每人每天需要各种食品的数量分别为x1,…,xn(2)用所设置的变量把所追求的目标和听受的约束,用数学语言表述出来,得该问题的数学模型:(1.1.3)这里a11表示购买了x;个第种食品所包含的第种营养量,其中min是 minimize的简写,读作“极小化”,s.t.是 subject tol的简写,读作“受限制于”或“约束条件是”。(1.1.1)称为日标函数,(1.1.2)-(1.1.3)称为约束条件例1.1.2[资金使用问题]设有400万元资金,要求4年内使用完,若在一年使用资金x万元,则可得到效益√万元(效益不能再使用),当年不用的资金可存入银行,年利率为10%。试制订出资金的使用规划,以使4年效益总和为最大。显然,不同的使用方案取得的效益总和是不同的。如(1)第一年就把400万元全部用完,则效益总和为√400=20.0(万元)(2)若前三年均不用而存入银行,则第四年把本息和:400×(1.1)3=532.4(万元)全部用完,则效益总和为√52.4-23.07(万元),比第一方案效益大3万元多;(3)若运用最优化方法,可得如下最优方案第年第二年第三年第四年现有资金400342265.1152.8使用金额86.2104.2126.2152.8第一章引言效益总和为√86.2+√104.2+√126.2+√152.8=43.1(万元),是第方案效益总和的两倍多。建立数学模型:设变量x(i-1,2,3,4)分别表示第所使用的资佥数。所追求的目标-4年的效益总和最大,表为+√3+所受到的约束为每年的使用数额既不能为负数又不能超过当年资金拥有数,即第一年00,存在正整数K>0,使得当k>K时,有|(8)-洲0,使得对于任意的k有|)川0,存在正整数K>0,使得当k,l>K时,有|x()-xO川

这是利用FPGA来读写SD卡的程序，是开源程序。

matlab函数两个：一个是能量谱。 一个是小波包分解与重构；可以自己更改成一个程序，可以达到能量特征提取的目的

一本用MATLAB讲解有限元方法原理的书，可以同时提高这二者的理论和应用水平。。这个PDF文件是我找到的，m文件源自本站网友zwlbb，为保持完整特地一起上传。。

java里用JFreeChart画柱状图、折线图、雷达图，三个封装好的方法，可以直接调用。

毕业设计论文人脸识别系统

【实例简介】RK3399 SCH PCB 设计， 完整的原理图，和pcb文件，可以直接发出去生产