Codejock.Xtreme.Toolkit.Pro.v15.3.1源码VS2013补丁

数学建模中常用的蒙特卡洛算法，很详细的，关于蒙特卡洛算法的介绍，误差分析以及实例运用

激光(Laser：Light Amplification by Stimulated Emission of Radiation)是光受激辐射放大的简称。原子受光子照射时不仅发生受激辐射同时还发生受激吸收。这两种过程是矛盾的。通常情况下吸收过程是主要的，受激辐射过程是次要的. 如果能够通过某种方法破坏粒子数的热平衡分布，受激辐射能量将大于吸收能量，受激过程将胜于吸收过程。这里E[v2]是单位为(m/s)2的速度平方平均值,离开地面高度h的单位为km,h的范围5~20km。近期实验证实了这个模型的近似合理性,并指出在儿百米以卜的近地面范围内,在白天Cn(h)≈C2()h43,在仅晚C2(h)≈C2()h23,另外Hal!发现8在草地覆盖面上空,Cn(h)≈C2()h3, Davidson发现海面上空C(h)≈C2()h23,1m≤h≤10m。一般m言,在近地面处C2的典型值从102m23(对于强湍流)到108m23(对于弱湍流)的范围内折射率功率谱密度折射率的随机起伏n1(r)主要是由温度空间分布中的随机微观结构而引起的,这种微观结构的起源则在于地球表面不同区域被太阳不同加热而引起的极大尺度的温度非均匀性,这种大尺度的温度非均匀性进而又引起大尺度的折射率非均匀性,它们最后被湍流风和对流冲碎,使非均匀性的尺度变得越来越小。湍流的大小范围通常从几毫米到几米,分别用内长度l和外长度L表示通常把大气折射率的非均匀性称为湍流“旋涡”,可以把他们想像成一些空气包,每个空气包鄞有一个特征的折射率。均匀湍流的功率谱密度Φ,(K)可以看成是尺度为L=2x/k,L=2x/和L,=2x/k的旋涡的相对丰度的一种量度。在各向同性湍流的情况下,Φ(K)仪是波数k的函数,k通过L=2x/k与旋涡大小L相联系。在 Kolmogorov关于湍流理论的终典工作的基础,普遍认为功率谱密度Φn(K)包括三个不同的区。对于很小的k=2n/L0(很大规模的尺寸)的区域叫输入区,在这个区域内谱的形状取决于特定的湍流是如何发生的,而且它通常是各向异性的。在这个区域被理论不能预言Φ(K)的数学形式。但当k大于某一临界波数λ时,Φ(K)的形状由制约着大湍流旋涡破碎为小旋涡的物理定律来决定。当k大于k0时,k0≈2x/,就进入了谱的惯性子区间。这里的Φn的形式可以由已确立的制约湍流的物理定律描述。由Kσ oImogoro湍流理论,Φ,为D(K)=0033C2k-1/32.5)当k达到了另一个临界值k的形式再次改变,这个区域叫耗散区,在这个区域里能量的耗散超过了动能。因此能量很小。所以,当k>k时,Φ很快下降。这里kn≈2π/l。 Tatarski川如下模型来概括k>k时Φn的快速下降:29C1994-2010ChinaAcademicJournalElcctronicPublishinghOusc.Allrightsrescrved.http://www.cnki.ncton(k)=0.033C, exp(k/km)(2.6)若选取kn=5.92/l,并且k>kn,上式是一个合理的近似。由式(25)和(2.6)所表示的谱在原点均偶不可积的极点,为了克服这种模型的缺点,常采用一种称为Ⅴ on karman谱的形式。这时谱近似地表示为0.033CΦ(k)≈(k2+k2)16 exp(- /km)Andrews提出了一个的近似谱8Φ(0.033 CR exp(-k2/k2)7/61+aQ2((k2+k2)16(28)k1k1其屮,a1=1.802,a2=0.254,k,-3.3/。注意,在a1=a2=0和作k=kn代换后Andrews模式简化为 Von karman谱;当k=l=0时,上式退化为(25)式。激光在大气中的传输方程假定大气的磁导率为常数,介电常量是随空间变化的。对于单色电磁波在地球大气中的传播,这时 Maxwell方程取以下形式l9V·H=0V×E=jboH(2.9)EOoEV·(EE)=0式(2.9)中,E是电场;H是磁场;a是角频率;而V矢量的分量为(O/ax,0/Cy,O/az)。把V×运算应用于式(29)的第二个方程,并将第二方程代入第三个方程,并考虑第四个方程,我们得到V·E+AHEE+V(E·Vlns)=0(2.10)这里代表以e为底的对数。波传播的局域速度即某点上的速度是(e)12,它也等于ch,式中,c是自由空间中的光速,而n是同一点上的局部折射率,因此u8=n/(2.11)由于和c是常数,有VIne=2vIn n(2.12)将式(2.11)和(2.12)代入式(210),得到C1994-2010ChinaAcademicJournalElcctronicPublishinghOusc.Allrightsrescrved.http://www.cnki.nct

基于Frenet优化轨迹的无人车动作规划实例，使用Python实现，高速场景

电力系统暂态分析MATLAB仿真程序

自适应滤波器的权威Sayed的大作，用大量的实例诠释自适应滤波器的各种算法原理，是不可多得的好书。ADAPTIVE FILTERSADAPTIVE FILTERSALIH SAYEDUniversity of California at Los Angeles◆旧EEEIEEE PressWIlEYNTERSCIENCEA JOHN WILEY SONS, INC, PUBLICATIONCover design by Michael RutkowskiCopyright C 2008 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 or bymeans, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under anySection 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of thePublisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center,Inc, 222 Rosewood Drive, Danvers, MA01923, (978)750-8400, fax(978)750-4470, or on the web atwww.copyright.comRequeststothePublisherforpermissionshouldbeaddressedtothePermissionsDepartment, John Wiley sons, Inc, 111 River Street, Hoboken, NJ,(201)748-6011, fax(201)748-6008,oronlineathttp:/www.wiley.com/go/permissionLimit 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 or completeness ofe contents of this book and specifically disclaim any implied warranties of merchantability or fitness for aarticular purpose. No warranty may be created or extended by sales representatives or written sales materialsThe advice and strategies contained herein may not be suitable for your situation. You should consult with aprofessional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or anyother commercial damages, including but not limited to special, incidental, consequential, or other damagesFor general information on our other products and services or for technical support, please contact our CustomerCare 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 may not beavailable in electronic formats. For more information about wiley products, visit our web site atwww.wlley.conLibrary of Congress Cataloging-in-Publication Data:Sayed, Ali hAdaptive filters/Ali H. Sayedp cmIncludes bibliographical references and indexISBN9780470-25388-5( cloth)Adaptive filters. I. TitleTK7872F5s285200862138l5324dc222008003731Printed in the united states of america10987654321To my parentsContentsPrefacexviiNotationXXVAcknowledgmentsXXXBACKGROUND MATERIALA Random variablesA 1 Variance of a random variableA2 Dependent random VariablesA3 Complex-Valued Random VariablesA 4 Vector -Valued Random variables3467A.5 Gaussian Random VectorsB Linear Algebra12B. Hermitian and Positive- Definite matricesB 2 Range spaces and nullspace of matrices14B3 Schur Complements16B 4 Cholesky factorizationB 5 QR DecompositionB6 Singular Value Decomposition20B 7 Kronecker productsC Complex Gradients25C 1 Cauchy-Riemann Conditions5C2 Scalar arguments26C3 Vector arguments26PART:。 PTIMAL ESTIMATIONScalar- Valued Data291. 1 Estimation Without observations1.2 Estimation Given Dependent observations1.3 Orthogonality Principl36CONTENTS1,4 Gaussian random variables382 Vector- Valued Data422. 1 Optimal Estimator in the vector Case422.2 Spherically Invariant Gaussian Variables462. 3 Equivalent Optimization Criterion49Summary and Notes51Problems and Computer Projects54PART I: LINEAR ESTIMATION3 Normal Equatlons603. 1 Mean-Square Error Criterion613.2 Minimization by Differentiation3.3 Minimization by Completion-of-Squares633.4 Minimization of the error Covariance matrix653.5 Optimal Linear estimator4 Orthogonality princlple4. 1 Design Examples4.2 Orthogonality Condition4.3 Existence of solutions744, 4 Nonzero-Mean variables5 Linear Models5.1 Estimation using Linear Relations5.2 Application: Channel Estimation5Application: Block Data Estimation815. 4 Application: Linear Channel equalization825.5 Application: Multiple-Antenna Receivers85Constralned estimation876.1 Minimum-Variance Unbiased estimation6.2 Example: Mean Estimation6.3 Application: Channel and Noise Estimation916.4 Application: Decision Feedback Equalization6.5 Application: Antenna Beamforming1017 Kalman Filter1047.1 Innovations process7.2 State-Space Model106

采用矢量控制的双馈风电机组低电压穿越仿真

用socket编写的 java网络五子棋，可以聊天，多人对战，类似游戏大厅

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