OFDM

本matlab程序的功能是利用人工神经网进行故障模式识别(Fault recognition using ANN)

有循环检测，周期性检测，部分实现了追踪测速迭代松弛算法，内含心电信号数据及运用MATLAB写的源代码。( There are cycle detection, periodic testing, Partially achieved tracking speed iterative relaxation algorithm, ECG data and includes source code written in MATLAB.)

说明：  压缩包为模糊PID控制的直流电机的速度控制系统仿真，可进行相关学习(The simulation of the speed control system of DC motor with the compression package of fuzzy PID control can be used for relevant learning)

脉冲宽度调制（PWM）是英文“Pulse Width Modulation”的缩写，简称脉宽调制。它是利用微处理器的数字输出来对模拟电路进行控制的一种非常有效的技术，广泛应用于测量，通信，功率控制与变换等许多领域。一种模拟控制方式，根据相应载荷的变化来调制晶体管栅极或基极的偏置，来实现开关稳压电源输出晶 体管或晶体管导通时间的改变，这种方式能使电源的输出电压在工作条件变化时保持恒定。　　脉冲宽 (Pulse width modulation (PWM) is the English " Pulse Width Modulation" acronym, or pulse width modulation. It is the use of the microprocessor to the digital output of analog circuits for the control of a very effective technology, widely used in measurement, communications, power control and many other fields with the transformation. An analog control means, in accordance with the corresponding changes in load modulation transistor gate or base bias, switching power supply to achieve the output transistors or transistor on-time changes in power in this way can the output voltage in the workplace conditions of constant change. Pulse width)

说明：  卡尔曼滤波简单例子，二维情况。模拟一个小车在平面内运动(Kalman filter simple example, two-dimensional situation. Simulation of a car movement in the plane)

在MATLAB用滤波器对采集到的心电图信号进行滤波，并用图像显示滤波前后的心电图波形，及滤波器波形，(Collected with a filter in MATLAB to the ECG signal is filtered, and before and after filtering with the image display ECG waveforms and wave filters)

图像分割的matlab代码，运行效果很好的。(Image segmentation matlab code, run very good.)

encoding bch in dvb-t2 standards

图像分析程序，他有效地实现了对输入图像的特征提取，并用MATLAB实现，它包括图像(Image analysis process, he effectively to achieve the input image feature extraction, and use MATLAB to achieve, which includes the image)

function pi = solve2(count,m,cc) 借助布冯投针实验 仿真求pi的值 pi=0 frq=0 randNo = binornd(1,cc,1,m) pro=zeros(1,count) for j=1:count for i = 1:m if randNo(1,i) == 1 frq = frq + 1 end pro(i) = frq/i end pi = (2*m)/frq pro(j) = pi end pro = pro,num =1:count plot(num,pro) (function pi = solve2 (count, m, cc) to vote with Buffon needle experiment simulation find the value of pi pi = 0 frq = 0 randNo = binornd (1, cc, 1, m) pro = zeros (1, count) for j = 1: count for i = 1: m if randNo (1, i) == 1 frq = frq+ 1 end pro (i) = frq/i end pi = (2* m )/frq pro (j) = pi end pro = pro, num = 1: count plot (num, pro) )