数据输出

In this paper,we propose a novel model named distribution-free data density estimation,which is based on distribution-free(i.e.,independent of data distributions) sampling on global cumulative distribution to achieve high estimation accuracy with low estimation cost regardless of distribution models of the underlying data.

分布无关密度估计算法首先将底层数据的任意分布转换成一中间分布——累计概率分布函数。由于累计概率分布函数的输出在[0，1]之间均匀分布，因此接着对累计概率分布函数的输出随机采样，可以准确估计当前网络中数据的密度分布。

Using sensor output data as the compensator input, and the sensor input data as the compensator output, the compensator is designed based on the nonlinear dynamic Laguerre function.

用传感器的输出数据作为补偿器的输入，传感器的输入数据作为补偿器的输出，进行基于Laguerre函数的非线性动态补偿器的设计研究。

Firstly this paper dissertates the significance, principle, workflow and characteristics of remote digital proof. Moreover, it puts forward the color management scheme of remote digital proof. And then, through experiments, it describes the process of native digital proof, including setting up ICC Profile which reflects printing characteristics, basic linearization and digital proofer's linearization, setting up ICC Profile which reflects characteristics of digital proofer's paper and ink, and so on. On the basis of that, the process of remote digital proof is set up and realized, including setting up original proof and remote proof. Besides, the chromatism and resolvent is analysised. The color consistency between the two digital proofers is realized. Finally, by setting up RSA digital signature of remote digital proof, the security of network transmission and validity of digital signature is assured.

本论文首先阐述了远程数码打样的意义、原理、组成及特点，并提出了远程数码打样的色彩管理解决方案；然后，通过实验说明了本地数码打样的输出过程，包括创建反映印刷工艺特性ICC Profile、数码打样机基本线性化及数码打样机线性化、创建反映数码打样机纸张、墨水特性的ICC Profile等等；在实现本地数码打样输出的基础上，基于Best Remoteproof建立和实现了远程数码打样，包括创建本地校样和远端校样；并且分析了色差数据以及解决方法，实现了两台远程数码打样机之间的色彩一致性；最后，通过建立远程数码打样的RSA数字签名方案，保证了网络传输数据的安全性以及数字签名的有效性。

Of all the above, the constructor is used mainly to generate and set ports and parameters; Ports acting as the channel for data transmission among actors are defined as input ports, output ports or input/output ports. They are also set as single port or multiple ports; parameters are used to allocate actors. In the document, it may be set as an default value or as vacancy to define the data type of parameters, while the specific function to be implemented by the actor shall be defined by public method. Within the actor, the implementing sequence and functions of the method is generally seen as follows

其中构造函数主要用于创建和设置端口和参数；端口作为角色间数据传输通道，它被定义为输入端口，输出端口或输入/输出端口，并被设置为单端口或多端口；参数用于配置角色，它在文件中可设有默认值或为空，并定义参数的数据类型；而角色执行的具体功能由公有方法定义，角色内这此方法的执行顺序及功能一般如下

In order to look for fast calculation model of a linear oscillation motor, which can express the transitive relation between parameters and performance. The basic mathematic model of a linear oscillation motor is established by finite analysis method and the regression modeling method for the support vector machines is introduced. Then, the SVM calculation model is set up. A shortcut online calculation method is provided for the process of the parameter optimization of linear motors.

为了寻找反映直线振荡电机参数与性能输入输出传递关系的快速计算模型，利用有限元分析法，建立了直线振荡电机非参数建模的基本数据计算模型，根据基本数据计算模型，引入支持向量机(Support Vector Machines， SVM)非参数回归建模方法，建立了用于直线振荡电机参数与性能之间输入输出传递关系的SVM计算模型，为电机参数优化过程提供了方便快捷的在线计算方法。

The method of prediction on stochastical simulating 3D parameter field of rock mechanics is brought forward in this paper. Namely, rock mechanics parameters- curve obtained by known and limited conventional log materials is took as inputs of hard data;and seismic attribute data body, hydrating of mud shale and rock environmental parameters data is took as constraint of soft data. By simulating stochastically through optimizing algorithm of Sequential Gauss Simulation,dynamical data field of rock mechanics parameter of three-dimensional space are gotten, then log response of rock mechanics parameters in position of any point in space is predicted.

提出三维岩石力学参数场随机模拟预测的方法，即以已知有限的常规测井资料计算出来的岩石力学参数曲线作为硬数据输入，以已知地震属性数据体及泥页岩水化和岩石环境参数数据作为软数据约束，选择序贯高斯模拟方法，随机模拟得到动态规律变化的岩石力学参数的三维空间数据场，然后由岩石力学参数的三维空间数据场预测空间任一位置的岩石力学参数在井上的测井响应，并把该反映动态规律变化的测井响应按照油田勘探开发的要求输出成特定格式，供生产和工程上使用。

The research which is the important part of the tunable erbium-doped fiber laser is composed of two main parts: 1. the gain part of the tunable erbium-doped fiber laser, which in fact is an erbium-doped fiber amplifier, its output characteristics are discussed both in theory and experiment, and the differences are also discussed between theory and experiment; 2. the saturated absorber part of the tunable erbium-doped fiber laser, also the part to narrow the line width of the fiber laser. The line-width narrowing mechanism in fiber laser induced by unpumped Er-doped fiber is presented from the aspect of coupling wave equation, and the main factor is considered as the standing wave induced by interference. The line-width is narrower when the standing wave is stronger, and the narrowing effect disappears with the disappearance of the standing wave. In the experiment, when adding a Faraday mirror in the laser cavity to remove the standing wave , the narrowing effect disappears. So the theory is proved by the result of the experiment.

本课题的研究内容是集成光学声光可调谐掺铒光纤激光器的重要组成部分，主要分两部分：1、声光可调谐掺铒光纤激光器中增益部分的研究，相当于对掺铒光纤放大器的研究，理论上对掺铒光纤放大器的输出特性进行分析，实验上实现了掺铒光纤放大器系统，并将实验数据与理论计算数据进行对比，分析了误差产生原因；2、声光可调谐掺铒光纤激光器中饱和吸收体部分的研究，即压窄光纤激光器输出线宽的研究，从耦合波方程出发，理论上解释了未泵浦掺铒光纤压窄光纤激光器线宽的原理，分析了影响该作用的主要因素是未泵浦掺铒光纤中相对传输的光干涉形成的驻波：驻波越强，压窄效果越好，相反当没有驻波时，没有压窄效果，在实验上通过在激光器腔内加入法拉第旋转镜使驻波消失，同时压窄效果消失，从而验证了理论分析的正确性。

Adopting the system and method in the invention tessellates to exchange the data according to bit and realizes the function of executing non-blocking exchange according to the bit in time slot; the invention is able to output any input bit on the appointed position of all needed outputting channel, which not only improves the flexibility of the data exchange, but also decreases the cost and has high cost performance.

采用本发明的系统及方法，细化到将数据按照比特进行交换，并且实现了按照时隙中的比特进行无阻塞交换的功能，可以让任意一个输入的比特在所有需要输出通道上的指定位置输出；不仅提高了数据交换的灵活性，而且降低了成本，性价比高。

The design of this dissertation begins with the definition of audience data structure based on considering the embedded developing environment features. The dissertation uses the STi5518 chip by ST Microtones to collect audience data, and then the SI analysis and OSD interactive function are used to gain the user watching information. Then collect audience data in EEPROM of STB, use STB and serial to transmit the data, then use the RS232 serial port and RJ-45 converter to realize the data Return of Serial to Ethernet, in the process of data Return it completes the conversion of data format.

本设计首先在嵌入式环境的前提下，在用户数据采集和回传工作中采用了ST Microtones公司提供的STi5518芯片作为机顶盒主芯片，根据收视率调查需要制定出用户的收视信息数据结构，并结合数字电视业务信息分析以及机顶盒的屏幕显示互动功能，对用户的收视情况进行记录；然后把记录的数据存储到机顶盒的EEPROM中，并利用机顶盒串口输出数据，再利用RS232串口与RJ-45转换器实现串口转以太网的数据回传，在回传过程中完成了数据格式的转换。

The system implemented forest fire model selection automatically and intelligently. BP artificial neural network model of forest fire model selection was build by treating forest fire environment data as inputting variable and treating appropriate forest fire model as outputting variable. At the same time, we studied the methods of acquiring and calculating data of inputting and outputting. The system implemented machine of model selection automatically based on dynamic data driven technology. We selected 72 items experimental data from historical forest fire records in Beijing to experiment and confirm the validity of model selection. It turned out that the reliability of model selection is more than 80 percent.

3基于BP人工神经网络方法设计了林火模型适宜性选择技术框架结构，通过神经网络形成林火模型选择知识，实现了林火模型的自动化和智能化选择；以火场环境因子为输入变量，以适宜火场环境模拟的林火蔓延模型作为输出变量，构建了林火模型选择神经网络模型；研究了输入、输出因子数据的获取与计算方式，实现了动态数据驱动的林火模型自动选择机制；以本京市为例，选择了有详细火场情况记录的72场林火作为实验样本，其中60条记录作为学习样本集，12条记录作为验证样本，对神经网络进行了学习和验证，实验结果表明，模型选择精度可达到80%以上。

Singer Leona Lewis and former Led Zeppelin guitarist Jimmy Page emerged as the bus transformed into a grass-covered carnival float, and the pair combined for a rendition of "Whole Lotta Love".

歌手leona刘易斯和前率领的飞艇的吉他手吉米页出现巴士转化为基层所涵盖的嘉年华花车，和一双合并为一移交&整个lotta爱&。

This is Kate, and that's Erin.

这是凯特，那个是爱朗。