xindaorongniang

This is a matlab program for music synthesis (Twinkle twinkle)... This programme generate audio wave file for twinkle twinkle music.

MCC DIRECT CONTROL using pulse generators

说明：  单相全桥逆变器simulink仿真，内含SPWM输出模块，可以通过设置调制比/基波频率/载波频率查看逆变器的响应效果。(Single-phase full-bridge inverter simulink simulation, including SPWM output module, can check the response of the inverter by setting the modulation ratio / fundamental frequency / carrier frequency.)

离散信号处理 1、信号的生成方法 2、频域信号的分析 3、求正弦信号的频率 4、求正弦信号的加入时间 5、滤波器的设计 (1 discrete signal processing, signal generation method 2, the frequency domain analysis of signal 3, and 4 the frequency of sinusoidal signal, and added sinusoidal signal 5, filter design)

《MATLAB控制系统仿真与实例详解》一书的光盘源码。图书简介：本书详细地讲解了MATLAB 7.x的功能与相关操作以及MATLAB在控制系统中的仿真应用。本书内容包括控制系统仿真基础、MATLAB程序设计语言基础、控制系统理论基础、Simulink交互式仿真环境、控制系统建模、线性控制系统的分析与仿真、PID控制系统设计及仿真、最优控制系统设计、鲁棒控制系统设计、神经网络系统设计及其MATLAB实现、模糊控制系统设计和系统辨识。 (" MATLAB Control System Simulation and explain examples of" one-source book on CD-ROM. Book Description: This book explain in detail the function of the MATLAB 7.x and related operations and MATLAB in the control system simulation applications. The book includes basic control system simulation, MATLAB programming language basic, basic control system theory, Simulink interactive simulation environment, control system modeling, linear control system analysis and simulation, PID control system design and simulation, optimal control system design, robust control system design, neural network system design and MATLAB implementation, fuzzy control system design and system identification.)

Voting simulation in Matlab

说明：  相关向量机（Relevance Vector Machine，简称RVM）是Micnacl E.Tipping于2000年提出的一种与SVM（Support Vector Machine）类似的稀疏概率模型，是一种新的监督学习方法。 它的训练是在贝叶斯框架下进行的，在先验参数的结构下基于主动相关决策理论（automatic relevance determination，简称ARD）来移除不相关的点，从而获得稀疏化的模型。在样本数据的迭代学习过程中，大部分参数的后验分布趋于零，与预测值无关，那些非零参数对应的点被称作相关向量（Relevance Vectors），体现了数据中最核心的特征。同支持向量机相比，相关向量机最大的优点就是极大地减少了核函数的计算量，并且也克服了所选核函数必须满足Mercer条件的缺点。(Relevance Vector Machine (RVM) is a sparse probability model similar to SVM (Support Vector Machine) proposed by Micnacl E. Tipping in 2000. It is a new supervised learning method. Its training is carried out under the Bayesian framework. Under the structure of prior parameters, it is based on Automatic Relevance Determination (ARD) to remove the irrelevant points, so as to obtain the sparse model. In the iterative learning process of sample data, the posterior distribution of most parameters tends to zero, which is independent of the predicted value. The points corresponding to non-zero parameters are called Relevance Vectors, which represent the most core features of the data. Compared with support vector machine, the biggest advantage of correlation vector machine is that it greatly reduces the computation amount of kernel function, and also overcomes the shortcoming that the selected kernel function must meet Mercer's condition.)

An Introduction to Matlab Version 2.3 guide to matlab

LDPC编码的matlab实现，好用，利于初学者。(LDPC coding matlab implementation, easy to use, help for beginners.)

基于matlab 的贝叶斯算法，分类结果显示比较准确(Matlab-based Bayesian algorithm, more accurate classification results)