java

混沌工具箱ver.2.0,程序没问题，可以用。有c-c法求时延和嵌入维数的，求最大李雅普诺夫指数的等。(Chaos Toolbox ver.2.0, the program is no problem, you can use. There cc method for delay and embedding dimension, for the largest Lyapunov exponent and so on.)

ROLE OF POWER ELECTRONICS IN RENEWABLE ENERGY SYSTEMS

code for fitness distance ratio PSO

说明：  用于人造视觉 256*256的图像缩小到25*25 用saliency提取显著性区域 并根据设定的阈值剪裁(256* 256 for artificial visual image reduced to 25* 25 with saliency extraction of significant regional and in accordance with thresholds set tailoring)

适用于多自由度的在MATLAB环境下的源代码，适用于工程力学等学科分析与学习(degrees of freedom )

t - time series y - value of series at time t w - cycle length, defined by user based on prior knowledge of time series alpha - type I error used for cofidence interval calculations. Usually set to be 0.05 which corresponds with 95 cofidence intervals(t- time series y- value of series at time t w- cycle length, defined by user based on prior knowledge of time series alpha- type I error used for cofidence interval calculations. Usually set to be 0.05 which corresponds with 95 cofidence intervals)

SVM数据挖掘分类实验系统，matlab svm工具箱使用实例(SVM data mining classification experimental system, matlab svm toolbox using examples)

粒子群优化算法的源程序和pdf课件，还包括几个应用粒子群算法解决优化函数的例子(Particle swarm optimization algorithm source and pdf courseware)

这是仿真跳时序列超宽带带的源代码，希望我能给所需的人提供一点帮助。(This is the simulation dancers sequence UWB with the source code, I hope I can provide the necessary assistance.)

BP神经网络：是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。(BP neural network: a Press the front back propagation algorithm to train multilayer feedforward network is one of the most widely used neural network model. BP network can learn and store large amounts of input- output mode mappings without prior reveal mathematical equations that describe this map. It' s learning rule is to use the steepest descent method, through a reverse spread to constantly adjust the network weights and thresholds, so that the minimum squared error of the network. BP neural network topology, including the input layer (input), hidden layer (hide layer) and output layer (output layer).)