合并算法 meaning in English
merging algorithm
union algorithm
Examples
- Congener concept was introduced into the lattice union algorithm , which was used to update each child node in less time according to the order relation of the concepts
摘要提出了同类概念的观点，在格的合并算法中通过利用同域概念格之间的同类概念和概念的父子关系实现对其所有子节点的快速更新，以提高概念格横向合并算法的时间效率。 - As a preliminary investigation of the channel automatic routing , some of the channel router algorithm , such as left edge algorithm , the dogleg algorithm , net merge channel router and greedy channel router , are analyzed
作为通道自动布线的初步探索，论文分析了几种常见的通道布线算法如左边算法、狗腿算法、合并算法、贪婪算法。 - The improved parameterized matching algorithm has linear time and space complexity , fragment combining algorithm has 0 ( n2 ) time and space complexities ( n is the number of statements of the function which the fragment belongs to )
分析表明：改进的参数化匹配算法的复杂性同程序文件的行数成线性关系；碎片合并算法的复杂性是o ( n ~ 2 )的，其中n是碎片所在依赖单位的语句个数。 - In this dissertation , the research trends for the problem have been introduced ; the ‘ dim ’ and ‘ point ’ has been strictly defined in mathematics from machine vision and human vision ; the ideal clutter suppression system based on clutter predication and the realization and evaluation of evaluation index has been studied , in succession the clutter suppression technologies have been researched . firstly , the classic nonparametric algorithm has been analyzed in detail and systematically , for it ’ s weakness that it cannot remove the non - stationary clutter ideally , kalman filter algorithm for clutter suppression in 2d image signal has been built . secondly , fast adaptive kalman filter is presented based on fast wide - sense stationary areas partition algorithm : limited combination and division algorithm based on quarti - tree algorithm , new taxis filter route algorithm which can break through the limitation of the necessity of pixel neighborhood of 2d filter and laplace data model with two parameters which is perfectly suitable for the residual image of kalman clutter suppression
首先分析了经典的非参数法,对于四种具有代表性的核,从前述的三个性能评价方面做了分析和对比,指出了其速度快的优点和对非平稳图像适应性差的弱点,针对非参数法的弱点,重点研究了对非平稳图像适应良好的卡尔曼杂波抑制技术:建立了非平稳图像的类自回归模型,在此基础上建立了二维卡尔曼滤波基础的两个方程:状态方程和测量方程;建立了非平稳图像准平稳区域快速划分算法:基于四叉树法的有限分裂合并算法;二维空间的基于k排序的滤波路线算法,突破了空域滤波路线上区域相邻的限制;在这些研究的基础上实现了快速卡尔曼估计,实验验证了该方法相对逐点卡尔曼估计可以提高运算速度三倍左右;杂波抑制结果表明传统的高斯性检验并不适合卡尔曼估计后的残余图像,由此建立了残余图像的双参数拉普拉斯模型,实验表明其可以完好的吻合残余图像的概率密度曲线。