MatlabMoments

支持向量机是用于分类与回归的技术。由于其自身的诸多缺点，如无法获得概率输出，需要估计一个误 差参数C，以及必须使用Mercer 核函数等。相关向量机算法，克服了SVM 上述缺点，RVM 能获得与SVM 相比拟的推 广性能，并且更为稀疏。在此基础上，文中介绍了一种RVM 回归用于分类的新分类方法，用RVRC 来表示。并通过 实验证明了它的可行性。(Support vector machines for classification and regression techniques. Due to its many shortcomings, such as the probability that the output can not be obtained, need to estimate an error parameter C, and the need to use Mercer kernel function and so on. Relevance vector machine algorithm to overcome these shortcomings of SVM, RVM and SVM can be obtained comparable to promote performance and more sparse. On this basis, the paper introduces a RVM regression was used to classify new classification method, RVRC to represent. And through experiments proved its feasibility.)

关于ALHOA matlab仿真 希望能帮助大家。有图标和具体的方法。(About ALHOA matlab simulation we hope to help. Logos and specific method.)

matlab实现滑模控制，m文件编写，结构清晰，简单易懂，(SMC controller)

说明：  基于六自由度的弹道仿真,包含数据参数，运行结果，代码备份可在记事本打开(Trajectory simulation based on six degrees of freedoom)

首先，对太阳能光伏电池的基本原理和I-V、P-V特性进行分析。其次，建立电池的等效电路并初步设计仿真模型。(First, the basic principle and IV, PV characteristics of solar photovoltaic cells for analysis. Secondly, the establishment of the equivalent circuit of the battery and the preliminary design of the simulation model.)

Retinex和小波变换去除遥感图像云雾方法分析(Retinex and the wavelet transform method to remove cloud remote sensing image analysis)

一个MATLAB的GUI界面编程实例，类似于一般的软件界面，开发环境MATLAB7.4（R2007b）(A MATLAB-GUI interface for programming examples, similar to the general software interface, development environment MATLAB7.4 (R2007b))

A toolkit for Gaussian mixtures. flexible tools for: Generating univariate, multivariate, or mixtures of gaussians Interactive viewing tools allows viewing of multidimensional data and models. Initialize models, add and remove dimensions or clusters and inspect the fit in real-time. Also includes tools to subset the data using model-based (pseudo-)metrics.

说明：  神经网络pid的模型仿真建立，可以有效的控制参数(The model simulation of neural network PID can effectively control parameters)

It describes how to use the Homomorphic filter and find its quality measures in the form of gui in matlab.