Back-Propagation

给定两个变量，计算自定义的数学方程的matlab GUI例子。(it takes input parameters(in the following order) when you call the gui, a system of equations file. Once the equation is called it will display each of them in their proper list boxes. )

MATLAB 程序设计基础ppt讲义 幻灯片 内容属于入门级(MATLAB-based program design ppt lecture slides are entry-level content)

matlab 算法检测 特征值提取(matlab )

微分进化算法matlab程序代码，可直接运行，给研究微分进化算法的朋友提供帮助(Differential evolution algorithm)

NR for economic dispatch

写一个MATLAB函数fibo.m来计算Fibonacci数列，其定义如下： fibo(n+2)=fibo(n+1)+fibo(n) 此数列的初始条件如下：fibo(1)=0,fibo(2)=1。(Fibo.m write a MATLAB function to calculate the Fibonacci sequence, which is defined as follows: fibo (n+2) = fibo (n+1)+fibo (n) the initial conditions in this series are as follows: fibo (1) = 0, fibo (2) = 1.)

对杨氏干涉matlab仿真。matlab仿真matlab仿真matlab仿真matlab仿真matlab仿真(yangshi shuangfeng ganshe matlab matlab matlab matlab)

Simple manual of project 2007 in spanish

本设计主要对4PSK调制方式的信号，利用MATLAB的m文件进行最佳接收机的设计与仿真。对输入的叠加噪声的4PSK调制信号进行接收，利用相关解调器来实现信号解调，及最大似然准则来实现检测器。在相关解调器中，接收信号分别与基函数 和 相乘再积分。在检测器中，利用相位来判断输出，从而最终得到接收的数据。采用随机二进制数通过4PSK调制后叠加高斯白噪声再对设计的接收机进行测试，从测试的结果可看出，在信噪比大于-8dB时，误码率为0，说明该接收机较好的实现了抗噪声性能。(The design of the main 4PSK modulation mode of the signal, the use of MATLAB m file for the best receiver design and simulation. The 4PSK modulated signal of the input superimposed noise is received, and the demodulator is realized by the relevant demodulator, and the maximum likelihood criterion is used to realize the detector. In the associated demodulator, the received signal is multiplied by the basis function and multiplied by the basis function. In the detector, the output is judged by the phase, and finally the received data is obtained. Using the random binary number through 4PSK modulation after the superposition of white noise and then the design of the receiver to test the test results can be seen in the signal to noise ratio greater than-8dB, the bit error rate is 0, indicating that the receiver is better The realization of the anti-noise performance.)

Parallel Algorithms for the Longest Common Subsequence Problem