disanzhang

set partitioning in heirarchial tree

说明：  本例用matlab解决了数学建模中飞机精确定位问题。使用了优化函数‘constr’解决。（请在matlab 6.5以下运行）(Using matlab to solve this case, the mathematical modeling of precise positioning of the aircraft. The use of optimized function ' constr' solution. (Please run the following in matlab 6.5))

Describe Describe Describe Describe Describe Describe Describe Describe Describe Describe

本课件按逻辑编排，自始至终用实例描述；内容完整且每章相对独立；既适用于初学者，也适用于高级MATLAB用户。对MATLAB与FORTRAN、C等语言结合的描述更是一大特色。 本课件适合作为理工科高等院校研究生、本科生教学用，也可作为广大科研工程技术人员的自学。(The courseware is organized in a logical, throughout examples described complete and relatively independent of each chapter suitable for both beginners and for advanced MATLAB users. Combined with the description of MATLAB and FORTRAN, C, and other languages ​ ​ is a major feature. The courseware for science and engineering universities graduate, undergraduate teaching, can also be used as a self-study of the majority of scientific engineering and technical personnel.)

本部分为一个热物体的传热模拟程序，把物体进行分割为单元，依次计算传热(This section is a hot object heat transfer simulation program, the objects divided into units, followed by calculation of heat transfer)

说明：  利用wolf法求取Lyapunnov指数，并绘制图形(Method used to obtain Lyapunnov wolf index, and draw graphics)

利率模拟实验。Monte_Carlo过程应用之一。(Interest rate simulation. Monte_Carlo one application process.)

k均值算法用Matlab实现，这个不太确定(k-means algorithm using Matlab achieve, this is not so sure)

More material can be found at the web sites for EE364A (Stanford) or EE236B (UCLA), and our own web pages. Source code for almost all examples and figures in part 2 of the book is available in CVX (in the examples directory), in CVXOPT (in the book examples directory), and in CVXPY. Source code for examples in Chapters 9, 10, and 11 can be found here. Instructors can obtain complete solutions to exercises by email request to us please give us the URL of the course you are teaching.

The LMSE package contains two subroutines. LMSE computes the minimum mean square error (MSE) possible if one image is allowed to be linearly scaled in intensity. LMSEDIFF computes the difference image after the target image is scaled according to the scaling that minimizes the MSE. This is a better way to compare images if the absolute magnitude of the intensity has no meaning.