a priori bound

a priori bound的基本解释

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先验界限

与a priori bound相关的网络例句 [注：此内容来源于网络，仅供参考]

Next, after analyzing the nets′relationship in three layer channel routing, setting up the objective function toward channel area minimization, we propose some new terms, for example, the withstand bound columns, valid complete cover net sets, TRACK valid routing, etc.. The conceptions and natures of static bound of nets, dynamic bound of unrouted net set and the lower bound value of the horizontal tracks are discussed; and the methods of calculating static bound, dynamic bound and lower bound are put forward.

文章接着分析了线网在三层通道区布线中的相互关系，为了以完成布线所需通道区面积最小化为目标解决三层通道区布线问题，提出了柱界列、完全有效覆盖线网集、TRACK有效布线等一些新的概念，讨论了三层通道区布线问题中线网定界、未布线网集动界和水平通道数Lower-Bound等概念和它们的性质，给出了定界、动界、Lower-Bound值的计算方法。

Applying the De Caen"s inequality of sum of the squares of the degree and Cauchy"s inequality, we obtain a strict lower bound and a strict upper bound of the largest Laplace eigenvalues only in terms of vertex number of a unicycle graph. Applying the Laplace matrix theorem of trees, we obtain an upper bound of the second smallest Laplace eigenvalues of a unicycle. Extremal graph whose second smallest Laplace eigenvalues reach the obtained upper bound is determined. We also obtain an upper bound of the second largest Laplace eigenvalues in terms of vertex number of the largest connected branch of unicycle graph, and obtain a theoretical method to calculate the second largest Laplace eigenvalues of unicycle graph. We obtain an upper bound of any Laplace eigenvalues in terms of vertex number of a unicycle graph. We also obtain the distribution of Laplace eigenvalues in the inter [0,n] in terms of the matching number.

本文得到了以下几个方面的结果： 1、利用图度平方和的De Caen不等式和Cauchy不等式给出单圈图的最大Laplace特征值仅依赖于顶点数的严格的上下界；利用树的Laplace理论给出了单圈图次小Laplace特征值的一个上界，并刻画了达到该上界的极图；利用子图的连通分支的顶点个数给出了单圈图次大Laplace特征值的一个上界，并给出了单圈图次大Laplace特征值一个理论上的一个求法；利用单圈图的阶数给出了其一般Laplace特征值的一个上界；利用单圈图的匹配数给出其Laplace矩阵谱在区间[0，n]上的分布情况。

However, currently, the retrieval of multiangular remote sensing seldom considers the use of spectral information. We use MSAVI2 as an index to get the a priori knowledge of LAI. As a result, the a priori knowledge is more objective. From the comparison of using or not using this MSAVI predicted a priori knowledge, we found that this approach is effective.

与以往的反演方法相区别，该文利用行播作物二向反射模型，将多角度与多光谱数据结合进行行播作物LAI反演实验，并对反演算法进行了详细的敏感性分析实验，结果表明采用多角度、多光谱遥感数据相结合的方法可以有效反演行播作物的叶面积指数。

与a priori bound相关的网络解释 [注：此内容来源于网络，仅供参考]

a priori bound：先验界限

a priori bound 先验界限 | a priori distribution 先验分布 | a priori probability 先验概率