SLIC超像素分割matlab代码

国外大牛 Andrew Fitzgibbon写的ICP算法实现代码，含2D和3D，工具包，可以打开主目录下的Untitled3看一下效果。

C语言-遗传算法的排课源码，遗传算法、使用c语言开发，源码

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

GH 风机设计软件Bladed介绍文档。Bladed 基础资料，朋友们可以学习下，也是来源于网络。风机很复杂( Wind turbines are complicated它是以下各个方面交互作用的结果 Interaction o风空气动力学 aerodynamics波浪 Waves结构动力学( Structural dynamics)传动系统 (Power train控制系统 [ Control systems)Introduction to GH BladedGARRADHASSAN风机是与众不同的设备 Wind turbines are unusual叶片翼型运行在失速的状态下( Aerofoils operatein stall)很有可能产生结构共振 (Structural resonance islikely)载荷很不规则,而且是非线性的 (Loading ishighly irregular and non-linear)高周疲劳 (High cycle fatigue)Introduction to GH BladedGARRADHASSAN对设计工具的要求 Design tool requirements能够模拟非线性载荷和响应的严格数学棋型→时域仿真( Rigorousmathematical model able to model non-linearities in loading and response - time-domain simulations集成了空气动力学、结构动力学、流体力学、控制系统响应(Integration of aerodynamics, structural dynamics, hydrodynamics, control systemresponse准确的风和海浪环境模型( Accurate modelling of wind and wave environment)功率特性的计算( Power performance calculations)载荷计算:疲劳和极限 (Load calculations: fatigue and extreme)方便设计使用 (Designer-friendly与当前的标准相一致( Compatible with current design standards)快速、稳定、经过验证的方法( Rapid, robust, validated methods)Introduction to Gh BladedGARRADHASSANGHB|aded的历史 (The history of GH Bladed)从1984年开始 Bladed(From1984: Bladed)研兜用程序( Research code性能和稳态载荷( Performance and steady loads)从1985年开始 Bladed(From1985: Bladed气弹模型( Aeroelastic model)从1992年视窗版 Bladed(From1992: Bladed for windows集成的综合设计工具( ntegrated design tool)视窗界面 Windows interface)1996:商业发行(1996: Commercial launch)2006:全球有150个许可证用户(2006:150| cences worldwide)15个国家的50个客户(50 clients in15 countries)Introduction to GH BladedGARRADHASSANBladed的性能( Bladed capabilities空气动力学特性( Aerodynamic performance)稳态载荷和功率曲线 teady loads and power curves)动力响应仿真( Dynamic simulations动态学功率曲线( Dynamic power curves)疲劳和极限载荷( Fatigue and extreme loads)地震模型 Earthquake modelling.控制器测试 Controller testing)为设计控制用的线性化模块 Linearisation for controldesign)Introduction to gh BladedGARRADHASSANBladed: (schematic)时域风场Time结构屑性传动系统和控随机或周期波浪domain wind field)( Structural制系统 Power(Random or regularproperties)traini& controlwayes)s/stem空气动力学流体动力学(Aerodynamics)(Hydrodynamics)风载荷时间序结构动力响应波浪载荷时间序列 Wind load(Structural列 Wave loadhistories)dynamicshistories响应时间序列(Responsehistories)疲劳载荷时序分析(Tme极限载荷(Fatigueseries analysis(EXtreme loadsLoadsIntroduction to GH BladedGARRADHASSAN风场的建模空间变化 Wind modelling- Spatial variations)风剪切 Wind shear指数的、对数的或者用户指定( exponentia, logarithmicor user-specified上升流(Upnw)塔架阴影( Tower shadow势能流模型和下风经验模型( potential flow/ downwindempirical models上风风机尾流分布( Upwind turbine wake profileIntroduction to gh BladedGARRADHASSAN风的建模-湍流 Wind modelling- Turbulence)3维湍流风场(3 D turbulence)1,2或3个方向分量(1,2or3 componentsvon Karman或者 Kaimal频谱和相关谱模型 on Karmanor Kaimal spectrum and coherence modelsIntroduction to GH BladedGARRADHASSA

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。

小波软阈值去噪，具有较高的SNR,是一种自适应阈值算法

惯导轨迹标准值(空中盘旋)和陀螺仪及加速度计值数据，内含matlab分析程序。对于进行惯导解算及组合导航研究有帮助。

DB9 DB15 DB25 等各种DB接口封装库 ,库都是经过项目验证的，能够节省不少开发时间，与大家分享。

之前学习并详细总结了一篇k-均值（k-means）算法思想与实现步骤的文章，于是顺便提供Matlab代码实现，使得更好的理解算法的思想。本代码有详细的注释使初学者能更好的学习Matlab这门工具语言。

通信原理MATLAB仿真实验指导书V2.0林志谋 通信原理MATLAB仿真实验指导书 ，采用MATLAB SIMULINK 仿真2ASK,2PSK,2FSK,AM,DSB,SSB，以及PCM编码解码，差错控制编码等等，还用SIMULINK仿真了CDMA通信系统。