使用矩阵计算的数据流分析

O. V. Panchenko
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引用次数: 1

摘要

近几十年来,许多家居用品都已电脑化,收集数据并将其发送给进一步处理。因此,实时分析数据所需的数据流结构数量也在不断增加。此外,传感器、遥感、社交网络等活动领域以阵列的形式产生数据。然而,这些项目使用现有的统计数据流进行矩阵计算。从理论的角度来看,矩阵和矩阵变换被广泛用于解决计算机科学中的许多问题,如机器学习、电路分析、图像和图形处理。因此,基于基本的矩阵运算,将有可能为许多球体构建不同的算法。因此,这项工作的主要目标是为数据流分析提供矩阵计算。为此,您需要添加矩阵数据结构,以内置支持作为流元素和矩阵操作的矩阵。此外,这些矩阵类必须用于不改变或存储状态的操作符。
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Data Flow Analysis Using Matrix Calculations
In recent decades, many household items have become computerized, collecting data and sending it for further processing. Consequently, the number of data flow structure requirements to analyze data in real-time is steadily increasing. Besides, sensors, remote sensing, social networks, and other fields of activity generate data in the form of arrays. However, the projects use existing statistical data streams for matrix calculations. From a theoretical point of view, matrices and matrix transformations are widely used to solve many problems in computer science, such as machine learning, electrical circuit analysis, and image and graph processing. Thus, it will be possible to build different algorithms for many spheres, based on the basic matrix operations. Thus, the main goals of this work are to provide matrix calculations for data flow analysis. To do this, you need to add matrix data structures for built-in support for matrices as stream elements and matrix operations. Besides, these matrix classes must be used for operators that do not alter or storing state.
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