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In this algorithm, the Received Signal Strength Indicator ranging technique is employed to replace the distance measurement of one hop away from the anchor node in DV-Hop algorithm. Also a 2-D Hyperbolic algorithm is used to replace the trilateration algorithm in DV-Hop.

算法引入接收信号强度指示器测距技术代替DV-Hop算法中到锚节点一跳距离测量并采用2-D Hyperbolic算法代替DV-Hop算法中三边测量法。

The equal distance 3-improved-coverage number of beacon sending position is presented according the acreage of ROI.Then a simple method is put forward to calculate the coordinates of the sending positions in rectangular ROI.Aiming at the shortage of the existent sequence algorithm,when beacon moves according to the path and emits RF signals at every position,the ant colony algorithm is applied to the position sequence so as to get the beacon sending position.Further,in this algorithm the sensors could work out their position with trilateration.

根据ROI面积给出了等距三重优化覆盖此ROI所需要的信标发射位置数量计算方法;随后对矩形ROI提出了一种简单的信标发射位置确定方法;针对现有的遍历发射位置点的路径遍历算法的不足,提出了一种新的应用蚁群算法的信标发射位置点的遍历算法,并利用该算法对基于三边测量方法进行传感器节点定位。

From three aspects including the speed of convergences,correcting equation and the adopted grid form,the research development of SIMPLE and SIMPLER、SIMPLEC、SIMPLEX and so on,had been discussed.

算法的收敛速度;校正方程;所采用的网格形式三个方面对SIMPLE算法以及在该算法的基础上经改进得到的SIMPLER、SIM-PLEC、SIMPLEX等SIMPLE类算法的研究状况进行了论述。

The advantage of this algorithm is that it has no failure possibility but it is only useful for completely controllable quantum systems.(4) The probability controllability is presented and a control strategy is also presented for a certain kind of eigenstate controllable system.

该控制算法的优点在于不像基于Grover迭代的算法那样存在失败的可能性,控制算法本身没有随机性,是完全确定性的,但该算法只适用于完全能控的量子系统。

A smooth approximation algorithm is then proposed based on hinge-finding algorithm via curved faces approximated to the hinging hyperplanes model, which can obtain a smooth approximation result and hold some good properties of hinge-finding algorithm such as simplicity and effectiveness.

本文对找链接算法做了两点改进,其一是扩充了链接超平面模型,在二维空间上弥补了链接超平面模型表示能力不足这一弱点。仿真实验显示使用扩充后的模型得到了更好的分片线性逼近结果。另一点改进是使用双曲光滑函数构造出了基于找链接算法的光滑逼近算法。理论分析证明了算法的可行性。仿真实验验证了理论分析。

To overcome the drawback that the traditional Linear Grouping Algorithm, when extracting linear structures, is sensitive to outliers in datasets, a new finite step according to existence of optimal linear grouping in data set and a new algorithm based on k-means clustering, total least absolute deviation and resampling were proposed, which detected several different linear relations at once to minimize the total orthogonal distances from n given points to its nearest hyperplanes.

为克服传统提取数据集中线性结构的LGA对噪声数据比较敏感的缺陷,提出了两种基于稳健的全最小一乘准则下的LGA新算法。首先证明了全最小一乘准则下数据集最优划分的存在性,并据此给出一种有限步终止算法。其次为提高计算速度,根据k-means算法、全最小一乘准则和重抽样方法给出另一种快速收敛算法

In the fourth part, we propose a level-value estimation method, construct a conceptual algorithm and an implementable approach, and then prove that they are convergent.

第四章中提出了水平集估计方法,构造了理论算法和实现算法,并证明了理论算法和实现算法收敛性。

Analysis and simulation results indicate that the computation complexity of the proposed algorithm does not increase while oversampling rate increases and the proposed algorithm has advantages in computation complexity and is feasible in practical hardware systems.

相比于传统的相关算法和现有的两种改进型时域相关算法以及基于FFT的频域相关算法,该算法在运算复杂度上具有优势,有利于在实际硬件系统中实现。

In this paper, a consistent decision algorithm for multi frames continuous scene matching is proposed. The core of the algorithm is to make use of the information of the primary and secondary peaks of correlation matrix and the displacement of inertial guidance to delete false matched points.

它涉及到飞行器的制导控制、信号与信息处理和模式识别等学科就下视景象匹配系统的算法而言,通常包含有图像的预处理算法、图像的配准相似性度量和搜索算法以及配准结果的后处理算法等。

Under the given project scheduling specified by the upper-level algorithm, combined with a critical chain-based heuristic, the lower-level genetic algorithm reallocates the resources to shorten the project duration so that the rate of converging to the global optimum district is improved, and a variable mutation probability is developed to avoid premature convergence.

在由上层算法确定的调度顺序下,下层遗传算法结合基于关键链的启发式算法,对系统资源重新优化配置,使算法加速向最优解区域收敛,并在下层设计了随迭代代数增加的可变变异概率,以避免早熟收敛。

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