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There are good papers about underwater sensor networks.
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无线路由协议vbf，referred by (Efficient Error Recovery with Network Coding in
Underwater Sensor Networks)-vbf routing protocol （the implement on ns2)
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Channel Model Simulation for Underwater Acoustic Sensor Networks Using OPNET-Channel Model Simulation for Underwater Acoustic Sensor Networks Using OPNET
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硕士学位论文基于无线传感器网络的水下目标识别中的线谱特征提取，-Master' s degree thesis on wireless sensor networks for underwater target recognition in the line spectrum feature extraction,
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硕士学位论文，基于无线传感器网络的水下目标是吧，连续谱特征提取-Master' s degree thesis, based on wireless sensor networks for underwater target is right, a continuous spectrum feature extraction
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容延迟网络的质量性能测试，容延迟网络适用于深空和水下网络及自适应网络中-Capacity to delay the quality of the network performance testing, capacity-delay networks, applicable to deep space and underwater networks and adaptive network
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水下无线传感器网络的多个路由协议，包括VBF HH-VBF等-Underwater wireless sensor networks routing protocols
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利用径向基神经网络预测地下水量，已运行成功，预测效果良好。-RBF Neural Networks Groundwater forecast
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基于神经网络的水下机器人控制，里面有水下机器人的建模模型-Underwater robot control based on neural networks, there are underwater robot modeling model
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水下传感器网络的DV-Hop定位，matlab程序-localization for underwater acoustic sensor networks
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水下无线传感器网络NS2仿真代码，可添加路由协议-Underwater wireless sensor networks NS2 simulation code, you can add the routing protocol
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a matlab file to develop models for underwater acoustic communication networks
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适用于水声传感器网络的leach协议，修改了能量模型-the leach protocol which suitable for underwater acoustic sensor networks and modifying the energy model
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Mobicast Routing Protocol for underwater sensor networks.
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Localization issue is a crucial part of Wireless Sensor Networks (WSNs) including Underwater WSNs (UWSNs). Unlike in Terrestrial WSNs where the localization techniques are well established, localization for UWSNs is still at the infancy stage. Most o
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DeepLearnToolbox_CNN_lzbV2.0
深度学习,卷积神经网络,Matlab工具箱
参考文献:
[1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006
[2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998
[3] https://github.com/rasmusberg
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5下载：
CNN - 主程序
参考文献:
[1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006
[2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998
[3] https://github.com/rasmusbergpalm/DeepLearnToolbox
作者：陆振波
电子
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this characteristic code for underwater wireless sensor networks-this is characteristic code for underwater wireless sensor networks
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Time synchronization plays a critical role in distributed network systems. In this paper, we investigate the time synchronization problem in the context of underwater sensor networks (UWSNs). Although many time-synchronization protocols have been pro
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包括最小二乘法、SVM、神经网络、1_k近邻法,结合PCA的尺度不变特征变换(SIFT)算法，基于chebyshev的水声信号分析，有详细的注释，可以实现模式识别领域的数据的分类及回归，采用热核构造权重，可实现对二维数据的聚类，DC-DC部分采用定功率单环控制。- Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Combined with PCA scale invariant
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