alphabet

recnstitution重构相空间，在非线性系统分析中有重要的作用 (recnstitution reconstructed phase space, in the analysis of nonlinear systems plays an important role in the)

模糊自适应PID 更改模糊规则、隶属函数、系统传递函数即可获得不同系统的模糊自适应PID控制算法(Fuzzy adaptive PID change the fuzzy rules, membership function, the system transfer function can be obtained fuzzy adaptive PID control algorithm of the system)

直接序列扩频（Direct Sequence Spread Spectrum）工作方式，简称直扩方式（DS方式）。就是用高速率的扩频序列在发射端扩展信号的频谱，而在接收端用相同的扩频码序列进行解扩，把展开的扩频信号还原成原来的信号。(irect Sequence Spread Spectrum (Direct Sequence Spread Spectrum), hereinafter referred to as Direct expansion mode (DS). Is a high rate of spread spectrum sequence extension in signal spectrum, and at the receiving end with the same spread spectrum code sequence for expansion, the expansion of the spread spectrum signal back into the original signal. )

LIMITATION OF SWITCHING OVERVOLTAGES BY USE OF TRANSMISSION LINE SURGE ARRESTERS

电动执行机构是连接控制器与执行器(阀门)的部件，从控制出来的是离散信号，经零阶保持器后成为一个方波 信号，值都是阶跃跳动，而阀门的实际工作是有一定的行程时间的，即实际上阀门是不可能实现阶跃跳动的，故此需要一个电动执行器，将控制器的阶跃信号变为连续变化信号，假定阀门的行程时间与阀门开度变化成正比。(Electric Actuator is connected controller and actuator (valve) parts, from the control out of the discrete signal by zero-order cage became a square wave signal, values are step-beating, but the actual work of the valve there is a certain amount of travel time, that is, in fact the valve can not be achieved step beat, and therefore need an electric actuator, the controller of the step change in the signal into a continuous signal, assuming that the valve and the valve travel time changes in direct proportion to the door opening.)

说明：  SAR雷达，点目标仿真，程序+文献，包教包会(SAR radar, point-target simulation, the program+ documentation.)

Mfcc 提取语音特征参数 可以分辨出不同情感(Mfcc speech feature extraction can distinguish between different emotions)

说明：  CSTR modelling is done in the code. useful to understand the basics.

matlab stateflow 入门教程，里面有详细的例子介绍每一个功能如何使用，非常适合初学者。(matlab stateflow Getting Started Guide, which describes detailed examples of how to use each function, very suitable for beginners.)

ML gradient descend ，Stanford course(machine learning ，Andrew Ng)