fisher

describes the text to speech conversion using matlab

时间序列计算自相关系数acf和偏自相关系数pacf 以及金融时间序列的matlabGUI介绍(Time series calculations of acf and pacf)

一个典型闭环控制系统的组成是很复杂的。通常都由给定系统输入量的给定元件、产生偏差信号的比较元件、对偏差信号进行放大的放大元件、直接对被控对象起作用的执行元件、对系统进行补偿的校正元件及检测被控对象的测量元件等典型环节组成。而控制系统设计则是根据生产工艺的要求确定完成工作的必要的组成控制系统的环节，确定环节的参数、确定控制方式、对所设计的系统进行仿真、校正使其符合设计要求。同时根据生产工艺对系统的稳、快、准等具体指标选择合适的控制元件。自动控制原理的时域分析法，根轨迹法，频域分析法，以及各种补偿（校正）装置的作用及用法，能够利用不同的分析法对给定系统进行性能分析，能根据不同的系统性能指标要求进行合理的系统设计，并调试满足系统的指标。(A composition of the typical closed-loop control system is very complicated. Usually produced by a given component to given system input, resulting in a comparison of the deviation signal component, and the amplified error signal amplification components directly to the controlled object to the implementation of the role of components of the system correction components and testing of the compensation typical aspects of the composition of the measuring element of the control object. Control system design is part of necessary component for completing the work according to the requirements of the production process control system, to determine the link parameters to determine the control method, simulation of system design, calibration to meet the design requirements. Production process on the system stable, fast, accurate and specific indicators to select the appropriate control elements. Automatic control theory of time-domain analysis, root locus method, frequency domain analysis, as )

说明：  对心音信号进行小波三阶分解重构（默认阈值，软阈值）的matlab程序(wavelet decompose and redistribute matlab)

说明：  matlab命令大全，提供.doc文件格式(matlab command Guinness provide. doc file format)

DS扩频信号抑制正弦干扰性能仿真程序(DSSS signal sinusoidal interference suppression performance simulation program)

半监督学习(Semi-Supervised Learning，SSL)是模式识别和机器学习领域研究的重点问题，是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据，以及同时使用标记数据，来进行模式识别工作。当使用半监督学习时，将会要求尽量少的人员来从事工作，同时，又能够带来比较高的准确性，因此，半监督学习目前正越来越受到人们的重视。(Semi-Supervised Learning (SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method combining supervised learning with unsupervised learning. Semi-supervised learning uses a large number of unlabeled data, as well as labeled data, for pattern recognition. When using semi-supervised learning, it will require as few people as possible to work, and at the same time, it can bring relatively high accuracy. Therefore, semi-supervised learning is receiving more and more attention.)

Hierarchical Adaptive Fuzzy Sliding -Mode Controller for Multimachine Power Systems

都柏林大学《无线MIMO系统》（附matlab和C++仿真程序）(University College Dublin )

矩量法分析 半波阵子天线 电流分布 方向图(mom dipole current distrubution pattern simulation )