C#生成随机数字编码的例子

SPI通讯 学习之用 FreeScale-SPI communication

IEEEuwb信道模型下采用pam调整的超宽带通信仿真程序。-simulation program of ultra widebandth communicaiton using pam modulation,the channel model adopt is IEEE uwb channel model.

java 实现的雪花效果-朵朵雪花从天而降,效果生动.-achieve snowflakes effects-countless snowflakes fall from the sky and vivid effect.

本程序根据周晓云编写的VC教科书进行练习并编写！验证了部分算法和VC的实现方法-This program, prepared according to Xiao-Yun Zhou VC textbook exercises and the preparation! Validate some of the algorithm and the realization method of VC

俄罗斯方块,fdjkdkflfjldljkdflkdfkldlk dlk -Russia squares fdjkdkflfjldljkdflkdfkldlk dlk

ti-dsp2407的电动机控制和音频输出程序-ti-dsp2407 motor control and audio output procedures

在计算机系统中，为了提高主存利用率，往往把辅助存储器（如磁盘）作为主存储器的扩充，使多道运行的作业的全部逻辑地址空间总和可以超出主存的绝对地址空间。-in computer systems, in order to raise the utilization rate of main memory, often auxiliary memory (such as disk) as a main memory expansion. Multi-channel operation so that the operations of all logical address space can exceed the sum of the absolute main memory address space.

牛顿－拉夫逊法潮流计算 基本步骤： 　　（1）形成节点导纳矩阵 　　（2）将各节点电压设初值U， 　　（3）将节点初值代入相关求式，求出修正方程式的常数项向量 　　（4）将节点电压初值代入求式，求出雅可比矩阵元素 　　（5）求解修正方程，求修正向量 　　（6）求取节点电压的新值 　　（7）检查是否收敛，如不收敛，则以各节点电压的新值作为初值自第3步重新开始进行狭义次迭代，否则转入下一步 　　（8）计算支路功率分布，PV节点无功功率和平衡节点柱入功率。-Newton-Raphson method flow calculation basic steps : (1) formation of nodal admittance matrix (2) to set up the initial node voltage U, (3) the initial node-generation-related demand. calculated that the constant term formula Vector (4) nodes will be incorporated into the initial voltage-seeking, calculated Jacobian matrix elements (5) solving that equation, seek to amend the vector (6) to strike a new node voltage value (7) to check whether convergence, if not restrained. concentrated in the nodes of the new voltage as the initial value since the first three steps to re-start the narrow iterations. Otherwise, turn into the next (8) Calculation branch power distribution, PV nodes reactive power and balance-node into powe

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Hamming 神经网络从功能上来看是最小Hamming 距离分类器．利用它能够完成不完整输入信息与所存储模式的最小汉明距离分类． 　　 Hamming 网络是一个双层神经网络，第一层网（即匹配子网络）是用来计算输入模式与该网络已经学习过的各样本之间的匹配测度．第二层网（即竞争子网络）接收从匹配子网络送来的未知模式与已存各样本的匹配测度，然后经过多次迭代运算就可以求得与输入模式相匹配的样本．-Hamming neural network from the functional point of view is the smallest Hamming distance classifier. Use it to complete incomplete input information storage model with the smallest Hamming distance classifier. Hamming network is a double neural network, the first network layer (ie matching sub-network) is used to calculate the input model and the network has been studied by the match between the sample test degrees. The second layer network (that is, competitive-network) from the receiver-matching network sent an unknown model has been deposited with the samples matching measure, Then after many iterative computation can be obtained with the input mode matching sample.