MOEA

matlab工具箱应用简介，希望能有所帮助 (matlab toolbox application profile, hoping to be helpful)

把辨识分成两步进行：第一步：利用相关分析法获得对象的非参数模型（脉冲响应或相关函数）；第二步：利用最小二乘法、辅助变量法或增广最小二乘法等，进一步求的对象的参数模型。如果模型噪声与输入无关，则Cor-ls相关最小二乘法（二步法）可以得到较好的辨识结果。Cor-ls相关最小二乘法（二步法）实质上是先对数据进行一次相关分析，滤除了有色噪声的影响，再利用最小二乘法必然就会改善辨识结果。能适应较宽广的噪声范围，计算量不大，初始值对辨识结果影响较小。但要求输入信号与噪声不相关(The identification is divided into two steps: the first step: using the correlation analysis method for object nonparametric model (impulse response or related function) The second step: using the least squares method, auxiliary variable method or augmented least squares method and so on, further for the parameters of the object model. If the model input noise and independent, the Cor- ls related least squares (two footwork) can get good recognition results. Cor- ls related least squares (two footwork) is essentially the data to a correlation analysis, filter in addition to the influence of colored noise, using least squares inevitable will improve the identification result. To adapt to a wide range of noise and calculation is not big, the initial value to identification results less effect. But for the input signal and noise are not related)

数值资料变分同化风廓线雷达资料前需要对资料熟悉，并进行相应的质量控制。 通过对国内外主要风廓线雷达产品发展情况的介绍，比较了它们的主要技术指标和 测量性能，分析了天线、发射机采用不同技术体制时的优缺点。(Numerical data need to be familiar with the assimilation data of wind profile radar data, and the corresponding quality control. Based on the domestic and foreign main wind profile radar products development were introduced, compared and their main technical indexes The measurement of performance, analyzes the advantages and disadvantages of antenna, transmitter system when using different techniques. )

有小波分析的盲信号处理，matlab编写的元胞自动机，基于分段非线性权重值的Pso算法，包括主成分分析、因子分析、贝叶斯分析，滤波求和方式实现宽带波束形成，正确率可以达到98％。(There Wavelet Analysis Blind Signal Processing, matlab prepared cellular automata, Based on piecewise nonlinear weight value Pso algorithm, Including principal component analysis, factor analysis, Bayesian analysis, Filtering summation way broadband beamforming, Accuracy can reach 98 .)

NNDemo2.0是对神经网络实验演示系统NNDemo1.0的进一步增强与扩充， 可以形象的演示各种网络模型的一些应用或性质，其中仿真例题是《人工 神经网络原理及仿真实例》教材中所有的例题。该系统使用极其简便，即使 你对各种网络模型不是很深刻的了解，也可以很好的使用该系统。使用时， 你可以自己修改网络的各种参数，交互性较好，而且该系统通过大量的图示 及参数设置，可以让你了解每个应用实例实现的过程及详细步骤。如果你想 学习神经网络的Matlab仿真（编程），进一步提高自己的编程能力，下面的 文件说明可以帮助你很快的找到系统的每个源文件。 (NNDemo2.0 is a neural network system NNDemo1.0 experimental demonstration of the further enhanced and expanded)

本文件主要内容是讲解关于matlab gui的相关内容 (matlab gui)

适用于QAM、PSK信号的相位估计算法。用于纠正光纤通信中的相位噪声(phase noise estimation)

MATLAB初级图形演示系统，用于产生正余弦曲线，适合MATLAB初学者用于编程练习(MATLAB junior graphic presentation systems are used to generate cosine curve, suitable for MATLAB programming exercises for beginners)

仅通过动量效应筛选期货品种，从而构建期货多品种对冲策略(M effect for Multi-futures stratege)

Kalman滤波跟踪目标运行时需添加数据，并修改路径(Kalman filter tracking target runtime needs to add data, and modify the path )