non_domination_sort_mod

使用Matlab来实现旅行商问题的一些代码，希望对用Matlab学习优化问题的人有些帮助(tere is some code about TSP problem which is written by matlab,i hope it is helpful to some people who is learning matlab.)

自适应噪声对消器，适用于采样信号的白噪声消除。(Adaptive noise cancellation, and applied to sample the signal to eliminate the white noise.)

Basic Digital Image Processing using MATLAB

人脸识别算法基本代码matlab源代码1(face recognition)

用MATLAB实现了最小二乘法，并有较为详尽的注释，望各位赐教(Implemented with MATLAB least squares method, and have more detailed comments, hope you can enlighten)

The book includes an inplicitly method to discretitize the PDEs, also provides solutions to the algebraic equations using matlab code.

matlab代码，用来实现adaboost算法的代码，具体的该算法的实现还需要进行一些细节的修改，确保程序的正确运行。(matlab achieve adaboost funtion)

多变量输入、输出、多干扰、非线性和强耦合的复杂系统控制是一个比较困难的问题，常用的控制器可能因为多变量耦合问题难以控制系统。PID神经元网络是一种多层前向神经元网络，它的各层神经元个数、连接方式、连接权值是按照PID控制规律的已有原则和经验确定的，是一种动态的符合控制系统的前向网络。但是由于PID网络初始权值随机取值的原因，每次控制的效果都有所差别，个别情况下控制效果还比较差。本案例研究了基于PID神经元的多变量耦合系统控制，并用PSO算法来优化控制器以取得更好的控制效果。(Multivariable input, output, and more interference, complex nonlinear and strong coupling system control is a more difficult problem, commonly used multivariable controller may be because the problem is difficult to control the coupling system. PID neural network is a multi-front to neural networks, its number of neurons in each layer, connection, connection weights are in accordance with the existing principles and experience to determine the PID control law is a dynamic compliance before the control system to the network. However, due to the random initial weights of the network PID values ​ ​ of reason, every time there are differences in the effect of control and in some cases the control effect is still relatively poor. This case study of multivariable coupling system based on PID control neurons, and with PSO algorithm to optimize the controller to achieve better control effect.)

matlab 可视化 微分方程 算法 超越方程 科学计算(matlab algorithm visualization differential equations beyond scientific computing)

Elman神经网络的数据预测—电力负荷预测模型研究(Data forecasting based on Elman neural network model of power load forecasting)