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感知网络
相关语句
  sensor network
     Research and Realization of Mote Wireless Sensor Network
     Mote无线感知网络的研究与实现
短句来源
     Wireless Sensor Network was first brought forward at the end of 90s. it is integration of sensor techniques. nested computation techniques.
     无线感知网络是九十年代末开始出现的一门综合了传感器技术、嵌入式计算技术、分布式信息处理技术和无线通信技术的无线网络。
短句来源
     In sensor network constructed by randomly distribution, better sensor coverage could be achieved by topology adjustment utilizing mobility of sensor node.
     对于随机分布方式产生的感知网络,可以利用节点的移动性对特定感知节点的位置进行调整从而改善网络整体的感知覆盖范围。
短句来源
  perceptron networks
     Decision Feedback Equalizer Using Two-layer Perceptron Networks
     一种基于二层感知网络的判决反馈均衡器
短句来源
  “感知网络”译为未确定词的双语例句
     Freescale PowerQUICC~(TM)Ⅲ Processor Architecture for Next-generation Application Awareness Networks
     飞思卡尔针对下一代应用感知网络的PowerQUICC~(TM)Ⅲ处理器架构
短句来源
     Information Description Technique on Context-aware Network Management
     环境感知网络管理的信息描述技术
短句来源
     Mobile agent,which is sensitiv e to network status,can monitor the system and communicate with other agents.
     移动Agent可在异构的网络各个节点间自由地移动,它能感知网络的状态,监控系统并与其他Agent进行交互。
短句来源
     Post PC Periods and Wireless Sensing Networks and its Application in National Economy
     后PC时代与无线感知网络在国民经济中的应用研究
短句来源
     Edge Detection Algorithm Based on Fordward Sensing Network
     基于前馈多层感知网络的图像边缘检测算法
短句来源
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  相似匹配句对
     Networking
     网络
短句来源
     NETWORK
     网络
短句来源
     Survey of Network Situation Awareness System
     网络态势感知系统研究综述
短句来源
     Information Description Technique on Context-aware Network Management
     环境感知网络管理的信息描述技术
短句来源
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  sensor network
In order to increase the multiplexing capacity, decrease the measurement cost of each sensor, and improve the ability of reliability of the sensor network, a double-port interrogating technology was used.
      
An effective method for extending wireless sensor network lifetime is presented for redundancy nodes.
      
The least redundancy coverage strategy (LRCS) strategy takes the smallest redundant coverage as the criterion whose goal is to maximize the lifetime of the sensor network.
      
It effectively reduces the number of active nodes and extends the lifetime of the sensor network.
      
A new latency-reducing and energy-efficient protocol for the wireless sensor network
      
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  perceptron networks
The main result of this paper is that multilayer perceptron networks, of the type used in backpropagation, do not have the best approximation property.
      
A neural networks model was developed based on MLP (multi-layer perceptron) networks and the Levenberg-Marquardt optimization algorithm.
      
Comparison shows that the multi layer perceptron networks overperform the SVR and time series model (GARCH).
      
The problem of the rejection of patterns not belonging to identified training classes is investigated with respect to Multilayer Perceptron Networks (MLP).
      
Learning Nonoverlapping Perceptron Networks from Examples and Membership Queries
      
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This peper proposes a new approach for nonlinear channel equalization using a two-layer perceptron-based decision feedback equalizer(DFE).An error back-propagation learning algorithm to adjust the weights is derived. A special and effecient weight-initialization method is also given. Both two-layer perceptron DFE and the general MLP DFE are applied to equalize a nonlinear channel with severe intersymbol interference and Gausian colored noise. The equalization performances are obtained and compered by computer...

This peper proposes a new approach for nonlinear channel equalization using a two-layer perceptron-based decision feedback equalizer(DFE).An error back-propagation learning algorithm to adjust the weights is derived. A special and effecient weight-initialization method is also given. Both two-layer perceptron DFE and the general MLP DFE are applied to equalize a nonlinear channel with severe intersymbol interference and Gausian colored noise. The equalization performances are obtained and compered by computer simulations. It is shown that the two-layer perceptron-based DFE provides better performances in convergence speed,bit errorrate,and computation complexity than the ordinary three-layer perceptron-based DFE.

采用基于二层感知网络的判决反馈均衡器结构实现非线性信道均衡,导出了其权值自适应调整的学习算法,给出了一种有效的权值初始化方法。针对一种具有严重码间干扰与有色噪声的非线性信道,分别应用文中提出的二层感知网络判决反馈均衡器和一般的三层感知网络判决反馈均衡器对该信道进行均衡,对其均衡性能进行了计算机模拟,并作了分析和比较。研究表明所提出的二层感知网络判决反馈均衡器无论是收敛速度、误比特率,还是计算复杂度方面都明显优于文献[5]提出的多层感知判决反馈均衡器。

Mobile Agents are autonomous programs. They can move through a heterogeneous network of computers and migrat from a host to another host. They can sense the states of network, monitor system conditions, and interact with other Agents or resources. The Agent\|sensing tools allow agents to adapt to the network Enviroment and to get the information user required by navigating.

介绍了可移动 Agent的特性 ,可移动 Agent可在异质计算机网络中移动 ,它能感知网络的状态 ,监控系统并与其它 Agent进行交互 ,导航模型可以让 Agent适应网络的变化并自主制定导航计划 ,从而方便、有效、智能地完成信息检索的任务

Human brain is hypothesized to store a geometry and dynamic model of the limb.A multilayer perceptron (or MLP) network is used to stand for the model.In this paper the human elbow joint rhythmic movement is simulated in three cases:1)Parameters of the MLP,the limb geometry and dynamic model match completely,2)Parameters mismatch between them,and 3)Disturbance exists.The results show that parameters mismatch is the main error source,which causes the elbow joint movement to be aberrant.From this we can infer that...

Human brain is hypothesized to store a geometry and dynamic model of the limb.A multilayer perceptron (or MLP) network is used to stand for the model.In this paper the human elbow joint rhythmic movement is simulated in three cases:1)Parameters of the MLP,the limb geometry and dynamic model match completely,2)Parameters mismatch between them,and 3)Disturbance exists.The results show that parameters mismatch is the main error source,which causes the elbow joint movement to be aberrant.From this we can infer that movement study is a process in which the internal model is updated continuously to match the geometry and dynamic model of limb.

假设人脑存储着肢体的几何和动力学模型 ,以一个多层感知网络代表这个内部模型 ,仿真了在三种不同情况下人体肘关节韵律运动 :1)内部模型的参数与肢体的几何和动力学模型参数完全匹配 ,2 )上述参数不匹配 ,3 )存在外界干扰 .仿真结果显示模型的参数不匹配是导致肢体韵律运动误差的主要原因 .由此可见 ,运动学习过程就是内部模型不断更新以匹配肢体几何和动力学模型的过程

 
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