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8节点潮流计算程序，matlab配电网。电力系统的分析和计算中，需要不同网络结构和参数。在应
用这些参数之前，收集和整理工作会花费大量的时间和精力。-8-node flow calculation program, matlab distribution network. Power system analysis and calculation, require different network structures and parameters. Before applying t
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该代码用来实现一个基本移动自组网的仿真，各个节点随机移动，通过相互交换数据观察最后运行结果，代码简洁，避免了一些大型仿真软件的复杂使用过程。-The code used to achieve a basic mobile ad hoc network simulation, each node random movement, through mutual exchange of data to observe the final results, the code is simple and
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matlab 仿真程序可用于kalman滤波应用。- INTRODUCTION
This example simulates distributed control of a DC-servo. The example
contains four computer nodes, each represented by a TrueTime kernel
block. A time-driven sensor node samples the process periodical
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Example: Distributed Wireless Control System，可用于无线传感器网络中-This example shows distributed control of a DC-servo using
communication over a wireless network. The example also shows how to
simulate power consumption and how to use the battery block.
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3d dvhop的算法，已知网络中几个锚节点就可以计算出网络中其他点的坐标-3d dvhop the algorithm, a number of known network anchor node on the network can calculate the coordinates of other points
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在某一网络拓扑结构中,检验是否使每一个节点都保持连通状态,在电网规划中有重要作用-In a network topology, the test is to enable each node to maintain connectivity of a state, in the grid plays an important role in planning
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无线传感器网络节点自定位算法matlab实现-Wireless sensor network node to achieve self-localization algorithm matlab
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复杂网络的拓扑辨识,通过复杂网络中节点的状态可以辨识出复杂网络的连接结构（洛仑兹系统）-topology identification of complex networks. According to the node state of complex network, we can know the topology of this complex networks(Lorentz system)
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Map matching is the process of assigning user s location to the nearest node one a network. Three algorithms of map matching, point to point, point to line and line to line are presented in this document.
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We propose an algorithm for facial expression recognition which can classify the given image into one of the seven basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral). PCA is used for dimensionality red
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改进的Salama网络拓扑随机生成算法通用Matlab程序，在随机抛撒节点的时候使用了K均值聚类，网络节点分布均匀且疏密得当，边的分布也比较均衡。-Improved algorithm for randomly generated network topology Salama General Matlab program, when the nodes in the random throw using K means clustering, the network node density
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无线传感器网络的节点覆盖的研究，覆盖度可达到100 -Wireless sensor network node covered by the study, up to 100 coverage
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比较无线传感网络节点在不同算法下的能耗
-Comparative wireless sensor network node in different algorithm of energy consumption
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matlab配网33节点用牛顿拉夫舜法求解电网潮流计算。-matlab distribution network node 33 Ralph Shun calculated using Newton method for solving power flow.
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33节点matlab配电网仿真模型与matpower潮流计算结果等-33 node distribution network matlab simulation model and matpower flow calculation results, etc.
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基于matlab的两机五节点网络潮流计算程序代码-Matlab based on the five machine two node network flow calculation program code
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用Matlab仿真RLNC，网络运行RLNC.m。网络的源节点发送一个windows.png采用随机线性网络编码和信宿节点创建一个图像（资料图片）接收的数据。
如果windows.png和data.jpg是相同的则RLNC运行成功(Thesis of network simulation with Matlab using RLNC,the source node of network send a windows.png using Random Linear Network Coding
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深度神经网络在测试时面对如此大的网络是很难克服过拟合问题的。
Dropout能够很好地解决这个问题。通过阻止特征检测器的共同作用来提高神经网络的性能。这种方法的关键步骤在于训练时随机丢失网络的节点单元包括与之连接的网络权值。在训练的时候，Dropout方法可以使得网络变得更为简单紧凑。在测试阶段，通过Dropout训练得到的网络能够更准确地预测网络的输出。这种方式有效的减少了网络的过拟合问题，并且比其他正则化的方法有了更明显的提升。
本文通过一个简单的实验来比较使用Dropout方法前后网络
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IEEE33节点搭建matlab模型，适用于电力系统配电网电压控制计算仿真(IEEE33 node builds matlab model, which is suitable for power system distribution network voltage control simulation.)
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节点收缩法完整代码，网络带入即可出结果，对网络的节点进行收缩，求得网络中节点的重要程度，用来评价网络中节点重要性的有效模型(The node shrinks the complete code, and the network brings in the result.)
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