matrice

简明释义

英[ˈmeɪtrɪs]美[ˈmeɪtrɪs]

n. 矩阵；真值表；母式

n. （Matrice）（意、美、巴）马蒂斯（人名）

英英释义

单词用法

同义词

反义词

例句

1.The matrice is a key factor to determine the performances of a composite.

基体树脂是决定复合材料性能优劣的一个关键因素。

2.The inverse scattering problems of the matrice equation have been researched and the scattering data and the solution of the inverse scattering problem have been obtained.

研究了矩阵方程在离散情况下的反散射问题，通过推导得出了有关散射数据和反散射解。

3.The graph analysis method for topological equivalence of interconnection networks, and the concept of logical name matrice for describing logical name structure are proposed.

本文提出了互连网络拓扑等价的图分析法和描述网络逻辑名结构的逻辑名矩阵。

4.The graph analysis method for topological equivalence of interconnection networks, and the concept of logical name matrice for describing logical name structure are proposed.

本文提出了互连网络拓扑等价的图分析法和描述网络逻辑名结构的逻辑名矩阵。

5.Km is a parameter that is directly related with morphology of the matrice.

参数公里，是与此有直接关系的形态矩阵。

6.Then these matrice are transformed to arbitrary triangular element by the concept of subparameter.

应用亚参元的概念将这些矩阵推广应用于任意三角形单元。

7.In the fundamental operations of large scale matrice, computing speed of GPU can be 50 times faster than CPU on the suitable matrix blocking.

在基本的矩阵运算中，运用适当的矩阵分块，GPU的计算速度比CPU快50倍左右。

8.Researchers developed a new matrice to analyze genetic information.

研究人员开发了一种新的矩阵来分析基因信息。

9.The software utilizes a complex matrice for image processing.

该软件利用复杂的矩阵进行图像处理。

10.The engineer designed a new matrice to improve the efficiency of the machine.

工程师设计了一种新的矩阵以提高机器的效率。

11.In mathematics, a matrice is used to represent data in rows and columns.

在数学中，矩阵用于以行和列的形式表示数据。

12.The matrice of the transformation can be calculated using linear algebra.

变换的矩阵可以通过线性代数计算得出。

作文

In the realm of mathematics and science, the term matrice (矩阵) holds significant importance. A matrice is essentially a rectangular array of numbers, symbols, or expressions, arranged in rows and columns. This concept is not only fundamental in theoretical mathematics but also plays a critical role in various applied fields such as physics, engineering, and computer science. Understanding how to manipulate and utilize matrices can lead to profound insights and solutions to complex problems.To illustrate the significance of matrices, let's consider their application in solving systems of linear equations. In many real-world scenarios, we encounter multiple equations with several variables. These equations can often be represented succinctly using a matrice. For example, if we have the following system of equations:1. 2x + 3y = 52. 4x + y = 11We can express this system in matrice form as follows:| 2 3 | | x | | 5 || 4 1 | * | y | = | 11 |This representation not only simplifies the equations but also allows us to use various methods, such as Gaussian elimination or matrix inversion, to find the values of x and y efficiently.Moreover, matrices are indispensable in the field of computer graphics. When rendering images, transformations such as rotation, scaling, and translation can be performed using matrices. Each transformation can be represented by a specific matrice, and by multiplying these matrices together, we can achieve complex effects with minimal computational effort. For instance, a simple rotation of a point in a two-dimensional space can be accomplished with a rotation matrice that alters the coordinates of the point based on the angle of rotation.In addition to their mathematical applications, matrices are also prevalent in data science and machine learning. In these fields, data is often organized into matrices for analysis. Each row of a matrice might represent an individual data point, while each column could correspond to a feature or attribute of that data point. By applying various algorithms to these matrices, data scientists can uncover patterns, make predictions, and derive insights that inform decision-making processes across industries.The versatility of matrices extends even further into statistics, where they are used in multivariate analysis. Techniques such as principal component analysis (PCA) rely heavily on matrice manipulation to reduce the dimensionality of datasets while preserving as much variance as possible. This is particularly useful in situations where datasets contain numerous variables, making it challenging to visualize or analyze them effectively.In conclusion, the concept of a matrice (矩阵) is a cornerstone of modern mathematics and its applications. From solving linear equations to transforming graphics and analyzing data, matrices provide a powerful framework for understanding and manipulating information. As technology continues to advance, the importance of mastering matrices will only grow, making it essential for students and professionals alike to develop a strong grasp of this fundamental concept.

在数学和科学领域，术语matrice（矩阵）具有重要意义。matrice本质上是一个数字、符号或表达式的矩形数组，按行和列排列。这个概念不仅在理论数学中是基础，而且在物理、工程和计算机科学等多个应用领域中也发挥着关键作用。理解如何操作和利用matrice可以带来深刻的见解和解决复杂问题的方案。为了说明matrice的重要性，让我们考虑它在求解线性方程组中的应用。在许多现实世界的场景中，我们会遇到多个方程和几个变量。这些方程往往可以用matrice简洁地表示。例如，如果我们有以下方程组：1. 2x + 3y = 52. 4x + y = 11我们可以将此系统表示为matrice形式，如下所示：| 2 3 | | x | | 5 || 4 1 | * | y | = | 11 |这种表示不仅简化了方程，还允许我们使用高斯消元法或矩阵逆等各种方法有效地找到x和y的值。此外，matrice在计算机图形学领域也是不可或缺的。在渲染图像时，旋转、缩放和位移等变换可以通过使用matrice来执行。每个变换都可以用特定的matrice表示，通过将这些matrice相乘，我们可以以最小的计算努力实现复杂的效果。例如，在二维空间中简单地旋转一个点可以通过旋转matrice来完成，该矩阵根据旋转角度改变该点的坐标。除了数学应用，matrice在数据科学和机器学习中也很常见。在这些领域，数据通常组织成matrice进行分析。matrice的每一行可能代表一个单独的数据点，而每一列则对应于该数据点的特征或属性。通过对这些matrice应用各种算法，数据科学家可以发现模式、做出预测，并得出为各行业决策过程提供信息的见解。matrice的多功能性甚至扩展到统计学，其中它们在多变量分析中被使用。主成分分析（PCA）等技术在很大程度上依赖于matrice操作，以减少数据集的维度，同时尽可能保留方差。这在数据集包含众多变量的情况下尤其有用，使得有效可视化或分析它们变得具有挑战性。总之，matrice（矩阵）的概念是现代数学及其应用的基石。从求解线性方程到图形变换和数据分析，matrice提供了理解和操作信息的强大框架。随着技术的不断进步，掌握matrice的重要性只会增加，因此学生和专业人士都必须对这一基本概念有深入的了解。