演算

A boundary identification problem, i.e., inverse geometry problem of two-dimensional heat conduction was solved by using boundary element method and conjugate gradient method-based inverse algorithm.

采用基于边界元法和共轭梯度法的反演算法求解二维导热边界识别问题，即几何反问题。

A boundary identification problem of two-dimensional unsteady heat conduction was solved by using dual reciprocity boundary element method and conjugate gradient method-based inverse algorithm.

采用基于双倒易边界元法和共轭梯度法的反演算法求解二维非稳态导热边界识别问题。

In the refutation tree of predicate calculus, the proved conjunctive formula.

在谓词演算的反驳树中，被证明的合式公式。

First, by the composition theorem of acceleration of influence move, strict mechanical analysis and accurate mathematical computations, we have acquired the presentation formula of acceleration of the movable mass of the gyroscope rotating in a constant angular velocity in an inertia coordinate system.

利用牵连运动的加速度合成定理，通过严格的力学分析和严密的数学演算首先得到其活动质量当陀螺仪在惯性坐标系中作定常角速度转动时的加速度表达式。

However, the conventional CMAC has an enormous memory requirement so that it cannot be applied to solve higher dimensional problems.

因此，本研究提出一个具有自组织能力之阶层式小脑模型类神经网路，它可以依据分析学习样本的分布，自动建立网路的记忆体配置，并藉由阶层式的学习架构，来有效降低记忆体的需求，使其具有解决高维度问题的能力，而此类神经网路架构亦具有可扩充性，可以在不影响其他网路的学习架构下，任意的增减输出节点的个数，此外，我们也提出了一个渐进式学习的演算法来训练此一类神经网路。

Rader's algorithm, exploiting the existence of a generator for the multiplicative group modulo prime N, expresses a DFT of prime size n as a cyclic convolution of size N 1, which can then be computed by a pair of ordinary FFTs via the convolution theorem (although Winograd uses other convolution methods).

Rader演算法提出了利用点数为N的DFT进行长度为N-1的回旋摺积来表示原本的DFT，如此就可利用摺积用一对基本的FFT来计算DFT。

Because of ICP algorithm can identify a solution regarding the correspondence problem. In this study, I use ICP algorithm to calculate the transformation parameters of overlapped strips and compare the results with other adjusted Airborne LiDAR cloud point data to evaluate its feasibility.

本文即藉由ICP演算法能处理点云间误差的特性，对光达重叠航带的点云资料加以处理，将所得的成果进而与平差处理过后的光达点云资料做分析比较，以探讨其可行性。

In this study, we use LabVIEW programming language of PC-Based to carry out the reduction of actively noise with theoretical equations of acoustic feedback cancellation and incorporate Filtered-X LMS algorithm. Furthermore, it was to verify that the reliable of simulation and analysis for the processed of signal by the concept of cross correlation function.

而本研究中采用PC-Based作为控制处理器，透过LabVIEW图控程式实现消除声场回授的理论方程式，并且加入到Filtered-X LMS演算法则，当作控制器的输入讯号进行实验测试，以实现主动式噪音的消除，并且也同时验证本文中使用交互相关函数概念，辨识是否使用转移函数分离法之讯号模拟分析的可靠性。

To formalize this algorithm,crosscutting contract calculus and a set of contract elaboration rules are presented.

为了形式化这个算法，提出Crosscutting Contract演算和一组契约求解规则，并通过定义和证明契约完备性来保证契约求解过程的正确性。

In other words, localization can be performed based on a general scene. In this thesis, we adopt Spatial Gaussian Mixture Model in image segmentation to describe an image viewed by the robot in spatial domain without any artificial landmark. Secondly, we use a modified combination algorithm by Cyr and Kimia to combine similar data. It is found out that a monotonic relationship exists among the scene registered and its neighborhood in terms of distance. This phenomenon can be used to assist to localize the robot and this work demonstrate the feasibility by several experiments.

本论文中采用高斯混合模型(Gaussian Mixture Model， GMM)来描述空间中的场景，将场景概念化，这样任意的场景皆可以用高斯混合模型来表达，而无需加入大量的人工场景，接著将所获取的每个希望校正点的资料采用由修改后的Cyr and Kimia的结合演算法来减低及统合资料，当场景接近原本的当初建立的场景，经由最大可能性大体上会呈现单调的特色，将辅助机器人修正回原本的位置，以达到协助机器人定位的目标。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。