QPSK

全书包含 390 多个计算范例。所有算例的程序是可靠、完整的。读者可以在自己的MATLAB 环境中 完全准确地重现本书所提供的算例结果。算例的举一反三，将使读者很快掌握要领，从模仿走向灵活应用。(Book contains more than 390 examples of the calculation. Examples of all the procedures are reliable and complete. Readers in their own MATLAB environment completely and accurately reproduce the book provided by the results of numerical example. An example of giving top priority, will allow readers to quickly grasp the essentials, from imitation to creative use.)

此函数用来演示自动控制系统中的饱和非线性特性的描述函数 此函数是要调用输入的A矩阵中的元素 输入变量a，k的含义分别为：(This function is used to demonstrate automatic control system of the description of the saturation nonlinearity function this function is to call the input of the A element in the input variables a, k means are:)

采用自适应均衡中的LMS算法进行仿真，并实用30个抽头的横向均衡器结构，面向新手的Matlab仿真(The LMS adaptive equalization algorithm simulation and practical transverse equalizer structure 30 taps, for novice Matlab simulation)

用相位谱法 时延估计 里面有很详细的分析 图形有点误差(delay matlab time delay estimation delay matlab identification using neural networks on matlab )

某小型公司有四类人员：总经理、技术人员、销售经理、推销员。设计一个基类Person，并派生出Employee（职员）(A small company has four categories of personnel: general manager, technical staff, sales manager, salesman)

本程序是一个lagrang插值基于在matlab程序上的实现。可以很好的满足精度的需求(This program is a lagrang interpolation procedure based on the matlab implementation. Accuracy can satisfy the needs )

鲸鱼优化算法（WOA）是一种用于解决优化问题的新优化技术。该算法包括三个算子，用于模拟猎捕鲸鱼的猎物，环绕猎物和泡泡网觅食行为。 压缩包具体包括该算法的发表论文、源代码、matlab工具箱。(Whale optimization algorithm (WOA) is a new optimization technology for solving optimization problems. The algorithm consists of three operators, which are used to simulate the hunting behavior of whale prey, surround the prey and bubble net. The compression package includes publishing papers, source code and Matlab toolbox of the algorithm.)

Import form iges to matlab and autocad

截断的核范数，可用于矩阵恢复。需要知道丢失点的像素位置。该算法是 2013 PAMI上一篇文章里的算法。感兴趣的看看(Nuclear norm truncated matrix can be used for recovery. Need to know the pixel positions lost points. The algorithm is an article on the 2013 PAMI algorithms. Look interested)

通过matlab代码实现PCA算法程序设计步骤： 包括1、去均值 2、计算协方差矩阵及其特征值和 qZHBpQ 特征向量 3、计算协方差矩阵的特征值大于阈值的个数以及 ixDqskB值 4、降序排列特征值，编译通过达到很高的性能。(PCA algorithm program realization by matlab code design steps include: 1, 2 to the mean, covariance matrix and its eigenvalues and eigenvectors qZHBpQ 3, calculate the covariance matrix of eigenvalues greater than the number of threshold values, and only 4 ixDqskB, in descending order eigenvalues, compiled by achieving high performance.)