静态场景模型识别有效率数据集

在“面向5G通信基站核心射频器件滤波器的高性能拓扑设计及高精度自动化生产需求”的背景下，本数据集记录了滤波器静态场景模型识别问题的测试结果。静态场景模型识别问题源于滤波器综合中拓扑网络的多解性。其具体定义为：给定滤波器的频率响应及其对应的初始标准耦合矩阵（横向或折叠型），求解指定目标拓扑下所有满足该频率响应的耦合矩阵解。本数据集主要由Matlab软件生成，包含约20MB的Matlab运行结果文件、运行日志文件、S参数图片文件及拓扑结构图文件。此外，还包括约500KB的滤波器拓扑定义文档，以及约30MB的第三方资质测试报告。Against the backdrop of the demand for high-performance topological design and high-precision automated production of core radio frequency device filters in 5G communication base stations, this dataset records the test results of the static scene model recognition problem for filters. The static scene model recognition problem stems from the multiple solutions of topological networks in filter synthesis. Its specific definition is: given the frequency response of the filter and its corresponding initial standard coupling matrix (lateral or folded type), solve for all coupling matrix solutions that satisfy the frequency response under the specified target topology. This dataset is mainly generated using Matlab software, and contains approximately 20MB of Matlab runtime result files, runtime log files, S-parameter image files and topological structure diagram files. In addition, it also includes a filter topology definition document of approximately 500KB, as well as a third-party qualification test report of approximately 30MB.

搜集汇总

背景与挑战

背景概述

该数据集针对5G通信基站滤波器的高性能拓扑设计与自动化生产需求，记录了静态场景下模型识别问题的测试结果，旨在求解满足特定频率响应的耦合矩阵解。数据包含由Matlab生成的运行结果、日志、图像文件以及拓扑定义文档和第三方测试报告，总计约53.97MB。