adapBP

equations ode 45 for airplane

k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。(k-means algorithm accepts input k then n data objects into k clusters in order to make clustering satisfy obtained: the objects in the same cluster high similarity different clustering object similarity small. Cluster similarity is the use of the mean of each cluster of objects that get a " central object" (center of gravity) to perform the calculation.)

采用加权网络中节点强度和权重都是幂率分布的模型，双向PCS控制仿真，能量熵的计算，重要参数的提取，基于人工神经网络的常用数字信号调制，应用小区域方差对比，程序简单。( Using weighted model nodes in the network strength and weight are power law distribution, Two-way PCS control simulation, Energy entropy calculation, Extract important parameters, The commonly used digital signal modulation based on artificial neural network, Application of small area variance comparison, simple procedures.)

这是本论文的仿真部分，是对MIMO系统理论的验证。本论文将分别从两种情况来对系统进行仿真：不同的信噪比下，发射天线数 为4，接收天线 逐渐增大；不同的信噪比下，接收天线 为4，发射天线数 逐渐增大。然后分别绘出他们的仿真图，并对它进行分析(This is the simulation part of this paper is to verify the theory of MIMO systems. In this paper, two cases will come from the system simulation: different signal to noise ratio, the number of transmission antennas is 4, the receiving antenna is gradually increasing different signal to noise ratio, the receiving antenna 4, gradually increasing the number of transmission antennas Great. And then mapped to their respective simulation map, and analyze it)

matlab source code for image morphing..

说明：  基于二次型性能指标的单神经元pid控制程序(based on quadratic performance indicators single neuron pid control procedures)

new principle in RADAR and LIDAR with pulse compression and ifft and fft

泰克经典资料，详细阐述了探头的选择、使用、维护等。(Tektronix classical data, detailed probe selection, use and maintenance.)

神经计算的实验作业。用principle components analysis计算模式的主分量。提取线性输入的特征。(Neural computing experiment operations. Computing model using principle components analysis of the principal component)

说明：  基于蚁群算法求解对称非对称旅行商问题 (Solving Symmetrical and DisSymmetrical TSP base on Ant Colony Algorithm)