They are called quantum because it takes a packet of energy of a very specific size - a quantum - to create the states.
它们被称作量子因为物质只能接受一份份特定的能量——一个量子——来建立状态。
Kraft, an American food manufacturer, made Biskuat, an "energy biscuit" with lots of extra vitamins and minerals, into a bestseller in Indonesia by charging the equivalent of just 5 cents a packet.
美国食品生产商卡夫生产的Biskuat饼干，这是一种“能源饼干“，里面还有额外的维生素和矿物质，5美分一包的价格，让该饼干在印度尼西亚十分畅销。
Light particles - called photons - carry a packet of energy that depends on their frequency.
光束粒子——称为光子——携带的能量取决于它们的频率。
A routing path selected algorithm based on the minimization product of packet delay and packet energy consumption is proposed.
提出了一种基于平均分组时延与分组能量消耗乘积最小的路由路径选择算法。
The new arithmetic constructed the best wavelet packet based on the wavelet library with the criterion of fusing energy cost function and contract the most valuable features of the signals.
新算法以融合能量代价函数为标准，在整个小波库中构造最优小波包基，从小波包基上提取信号最有价值的特征值。
According to the method, the energy of different frequency bands after wavelet packet decomposition constitutes the input vectors of support vector machine as feature vectors.
该方法将振动信号小波包分解后的频带能量作为特征向量，输入到由多个支持向量机构成的多故障分类器中进行故障识别和分类。
Simulation demonstrated that the algorithm could dynamic adjust the route which can make the product of packet delay and energy consumption of routing path to be minimization in AD hoc networks.
仿真表明，该算法可以动态调整网络路由路径，使所选路径的平均分组时延与分组能量消耗乘积达到最小。
Enclosing damage diagnosis, this pape studies modal experiment in ambient excitation, optimal placement of sensors and structural damage alarming using wavelet packet energy spectrum.
本文围绕结构损伤诊断，研究基于环境激励的模态试验方法、传感器优化布置原理和小波包能量谱损伤预警方法三方面的内容。
The characteristic frequency band of the fault can be identified by wavelet packet decomposition and its energy spectrum conveniently, and the quantification analysis are then performed.
应用小波包分解及其能量谱直观地识别出故障的特征频带，并进行了量化分析。
Dynamic signals measured from experiment beams are first decomposed into wavelet packet components, then the wavelet energy rate index is computed and used to detect location of damage.
首先，将得到的结构响应信号进行小波包分解，然后通过小波包能量变化率指标来进行损伤定位。
Dynamic signals measured from experiment beams are first decomposed into wavelet packet components, then wavelet energy rate index is computed and used to detect location of damage.
首先将所得的结构响应信号进行小波包分解，然后通过小波包能量变化率指标进行损伤定位。
The cause of the packet energy variation is wave-flow interaction produced by temporal variation of the wind.
能量变化的实质是，风场的时变性引起了波流相互作用。
By decreasing the transmission power of the data packet, the energy consumption of mobile nodes was decreased.
同时结合功率控制技术对数据包传输功率进行控制，降低了节点的能量消耗。
Secondly, three single deck blast vibration signals were analyzed by wavelet packet based on software MATLAB and the change of energy distribution curve at different frequency bands was obtained.
其次，基于MATLAB时爆破振动信号进行小波包分析，得到了爆破振动信号在不同频带上的能量分布图。
Experimental results show the scheme has high energy efficiency, meanwhile, drops the packet error rate effectively.
实验结果表明，该方案具有较高的能量效率，能够有效降低误包率。
In this paper, the optimization of the transmitted signal energy for a data packet unit in UWB radio communications in additive white Gaussian noise(AWGN) channel is firstly investigated.
首次研究白高斯噪声（AWGN）信道下超宽带无线电通信系统中单个数据包单元发射信号能量的优化。
Whichever of the two receivers has a lower resulting error energy, in one example, is selected for processing the received signal (e. g., a high speed packet data signal on the uplink).
在一个例子中，两个接收机中引起更低误差能量的一个被选择用于处理接收的信号(例如上行链路上的高速分组数据信号)。
Then, the damage location can be identified by the change of the wavelet packet component energy.
通过各频段能量的变化进行损伤位置的识别。
Based on the frequency domain feature, energy eigenvector of frequency domain is presented using wavelet packet analysis method, and the way of best tree is used to choose symptom.
分析了用小波包能量分析方法提取故障信号特征向量的方法，并改进算法解决了小波包分解中的混频现象，根据最佳分解树进行了特征选择。
To diagnose accurately the rotation machine fault, this paper presents a new method of fault diagnosis based on wavelet packet energy eigenvector and neural network.
为精确诊断旋转机械的故障，提出一种基于小波包特征向量的神经网络故障诊断方法。
The wavelet packet method characterized by good time-frequency localization can be used to make signal reconstruction and energy analysis of blasting vibration wave.
利用小波分析良好的时频局部化性质，可以很好地对爆破地震波进行信号重构和能量分析。
The methods of Time Averaged Wavelet Spectrum and Wavelet Packet Energy can respectively determine its own Euclidean distance as the only quality inspection threshold of the Rear Bridge.
在时间平均小波谱和小波包能量法中，分别以各自确定的欧式距离作为后桥质量检测的阈值。
In addition, in order to avoid broadcast storms and the impact of information overlap, using mechanisms for the registration packet, thereby saving energy.
另外，为了避免广播风暴和信息重叠的影响，采用了数据包登记的机制，从而节约能耗。
And also the variation of the wave packet amplitude and energy has been discussed.
此外，还讨论了沿波射线波包振幅和能量的变化。
After noise reduction in the signal, using "wavelet packet-energy" to extract the characteristic vector and input them to the neural network for fault identification.
在对采集到的信号降噪后，利用“小波包-能量”法提取特征量，并将其输入到神经网络中进行故障识别。
On the basis of conventional cross correlation, the detector can complete packet detection and fine symbol timing at the same time by accumulating multi-path energy.
在改进传统互相关算法的基础上，通过累积多径能量，该分组检测器可以同时实现分组检测和符号精定时。
On the base of conventional cross correlation, the detector can complete packet detection and fine symbol timing at the same time by accumulating multi-path energy.
在改进传统互相关算法的基础上，通过累积多径能量，使得该分组检测器可以同时实现分组检测和符号精定时。
Then, wavelet packet was used to decompose and de-noise the milling force signal, as well as extracts the signals 'energy characteristics as import vectors of BP Neural Network.
然后，采用小波包对采集的铣削力信号进行分解和消噪处理，并提取其能量特征作为BP神经网络的输入向量。
Simulation results show that EB-TDMA has a better performance in terms of packet latency and energy consumption for burst traffic application with high-density deployment and high traffic load.
仿真结果表明，对节点密集时的突发业务，该协议在时延和节能方面都具有良好的性能。
Simulation results show that EB-TDMA has a better performance in terms of packet latency and energy consumption for burst traffic application with high-density deployment and high traffic load.
仿真结果表明，对节点密集时的突发业务，该协议在时延和节能方面都具有良好的性能。
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