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estimation of parameter相关的网络例句

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与 estimation of parameter 相关的网络例句 [注:此内容来源于网络,仅供参考]

In our design, the main assumption is that the regressor vector satisfies certain Lipschitz condition; the key procedure is that we transform the error system to the traditional form with the parameter estimation error multiplying the"regressor vector"; and the"regressor vector-based"update law comes from the combination of the gradient algorithm with a σ-modified term.

基于回归向量的自适应律是在经典的梯度算法上增加一个σ修正项后得到的。

The main contents is: analyzing some detection method to moving target nowadays; particular studying the principle of detection moving target in SAR; analyzing SAR imaging theory and the echo model of moving target; discussing conventional SAR imaging , the movements of target cause the changes of doppler mass center and regulable frequency, and the changes cause effect the imaging result; introducing the estimation method of doppler parameter; analyzing theory of DPCA, derivating the formula needed, and validating it's validity and practicability through simulation; advancing the improved DPCA algorithm that combine the advantage of DPCA and ATI, and validating it through computer simulation; using the revision algorithm to range ambulate based on keystone transformation, and validating it through computer simulation; discussing the compensation art of SAR imaging.

主要内容有:分析了现有的一些动目标的检测方法;详细研究了SAR动目标检测的原理;分析了SAR成像理论和运动目标的回波模型;探讨常规SAR成像时,目标运动引起的多普勒质心和调频率变化,以及这些变化对成像结果的影响;介绍了多普勒参数的估计方法;分析了DPCA原理,推导所需要的基本公式,并仿真验证其有效性和实用性;提出了结合DPCA和ATI优点的改进DPCA算法,并仿真验证;探讨了SAR成像中的运动补偿技术。通过对仿真结果的分析,本文提出的方法具有一定的指导意义和参考价值。

Production function ; parameter estimation ; artificial fish school algorithm ; residual sum of squares

生产函数;参数估计;人工鱼群算法;残差平方和

This is a globally optimized algorithm and can derive a rheological parameter estimation, showing superior statistic features including near unbiasedness of fitting residual error and almost least variance.

新算法是一个全局优化算法,所得到的流变参数估计具有拟合残差近似无偏性和方差几乎为最小的特征。

This new algorithm can derive a rheological parameter estimation that shows superior statistic features of fitting residual error unbiasedness and least variance.

该算法不需要人工给定迭代初始值,迭代过程稳定收敛到最小点,不会陷入极小点陷阱,收敛速度很快,所得到的流变参数估计具有拟合残差无偏性和方差最小的优良统计特征。

Because of the sampling processing, we can take the simple concave domain analysis and ICM optimization in two different levels, so as to make both the parameter estimation and optimization much easier to implement, while delivering a satisfactory result; The third one is based on the multi-resolution analysis, robust statistics and majority game theory. 4. Propose a new clustering algorithm based on the entropy concept, which is used for unsupervised segmentation of color images.

重点讨论非监督的图象分割问题,并给出了三种新方法:一是基于贝叶斯学习和全局竞争策略的方法,把参数估计和图象分割有机地结合在一起;二是基于分层的框架,从抽样定理出发,在两个不同的层次上使用简单的凹域分析和ICM优化,可以使得参数估计和优化问题都变得简单易行,并得到满意的结果;三是基于多级分析、鲁棒统计的参数估计和多数博弈论的优化算法。

Furthermore, a motion estimation technique for sequential thermal images is presented which measures the parameters of global motion in the image plane due to zoom and pan of the camera or the process of the vehicle, and a motion compensation interpolation technique is also presented which can compensate the global motion. The algorithm is based on a three-parameter model for motion description, and some improyement is given in this method. Good results are shown in the computer simulation experiments.

在研究了帧内编码的情况后,本文进一步分析了序列图象的特点,并对由摄象机运动和车辆行进所造成的全局运动进行了运动估值和补偿研究,对现有的三参数估值算法进行了分析和改进,推导出热图的序列图象的平移及缩放的运动估值与补偿的公式,通过计算机模拟进行了全局运动的估值和内插实验,获得了较好的结果。

The main content of this course includes collecting and sorting statistical data, static data comparison and analysis; descriptive and inference statistics, time series analysis , statistical index, probability and distribution, sampling, parameter estimation, hypothesis testing;simple , multiple regression and correlation analysis .

重要内容有:统计数据的收集和整理、数据的静态比较分析、统计描述与统计推断、时间数列分析、统计指数、概率与概率分布、抽样分布、;参数估计、假设检验、简单回归和相关的统计推断、多元回归和多重相关分析。

In the first chapter, we give a brief account of the time series background and introducespecially on stationary time series in the parameter estimation.

主要内容如下:第一章,主要介绍时间序列的研究背景及平稳时间序列在参数估计上已有的研究成果。

Based on the theory of generalized estimating equations, this thesisstudies the parameter estimation in several statistical models for longitudinal data.

本文基于广义估计方程的理论研究了纵向数据下几类统计模型的参数估计问题。

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