相干光通信的matlab离线处理代码 DSP

本书荣获2005年第十五届Jolt通用类图书震撼大奖。 继 Effective C++ 之后，Scott Meyers 于 1996 推出这本「续集」。本书与现今之 C++ 标准规格几乎相同。可能变化的几个弹性之处，Meyers 也都有所说明与提示。(the book won the 2005 session of the 15th General Books Jolt Awards shock. Following the Effective C, Scott Meyers in 1996 to launch the "sequel." The book's C with the current standard is almost the same. Several possible changes in flexibility, Meyers also has suggested and described.)

《高等光学仿真》matlab源程序，对光学中的主要衍射机理进行仿真。(Higher optical simulation matlab source code, mainly in the optical diffraction mechanism simulation.)

用matlab实现基于时间序列的最小二乘支持向量机预测，代码简单易懂，适合初学者使用(achieve the lssvm regression based on time series using matlab)

蒙特卡洛法空间点的离散应用，包含相应作图程序(Monte Carlo method of discrete points in space that contains the corresponding drawing program)

以线性最小约束方差算法为约束条件的自适应波束形成算法(An adaptive beamforming algorithm with linear minimum constraint variance as the constraint condition)

一个不错的用MATLAB对OFDM系统的仿真程序。(a good use of OFDM MATLAB system simulation program.)

二型模糊系统经典降型算法Karnik-Mendel算法(Classic type reduction algorithm of type-2 fuzzy logic systems. Karnik-Mendel algorithm (KMA))

用经典的pca k邻域方法估计点云法向量的程序，带有matlab gui，使用matlab 2016b编译运行成功，输入点云最好为列向量的txt文件，gui中内置了点云显示模块以及生成的点云法向量显示，并且可以输出法向量到txt文件中。(The program of estimating point cloud vector with the classical PCA K neighborhood method, with Matlab GUI, uses MATLAB 2016b to compile and run successfully, the input point cloud is the best column vector TXT file, the point cloud display module and the generated point cloud vector display in GUI are built in Gui, and the normal vector can be output to the txt file.)

Bundler v0.3 Installation Guide copyright 2009 Noah Snavely (snavely@cs.cornell.edu) based on the Photo Tourism work of Noah Snavely, Steven M. Seitz, (University of Washington) and Richard Szeliski (Microsoft Research) For more technical information, visit http://phototour.cs.washington.edu The source provided in this distribution can be accessed at http://phototour.cs.washington.edu/bundler/

matlab code for EmbeddingDimension_cao