动态场景模型识别有效率数据集

本数据集主要用于支持动态场景下的滤波器模型识别研究，其核心目标是在调试过程中，基于已知的响应曲线、横向耦合矩阵以及特定的物理或工程特征，推导出当前拓扑结构下的耦合矩阵解。动态场景模型识别被定义为：在调试场景下，依据已有的响应数据和横向耦合矩阵，结合特定的结构特征，确定在目标拓扑下当前物理模型的耦合矩阵。
为实现该目标，本测试引入一系列具有扰动的耦合矩阵，模拟调试过程中可能出现的变化情况，并采用一组真实的滤波器电磁仿真数据作为性能评估的参考。在实验中共选取了50种不同的拓扑结构，对每种结构分别进行50次动态扰动测试。在每次测试中，对耦合矩阵施加一定幅度的扰动，以仿真实际应用中可能存在的不确定性。若某一拓扑结构在50次测试中有45次及以上成功识别出目标耦合矩阵，即成功率不低于90%，则认为该结构满足性能指标。此外，测试还包含一组基于电磁仿真的滤波器响应参数。该组数据通过在一个滤波器模型上施加不同扰动获得，旨在反映实际环境中的响应变化。在测试过程中，需依据初始耦合矩阵识别出与每组响应参数匹配的耦合矩阵解，并据此判断识别精度。若成功识别率不低于90%，则认定所使用的拓扑结构及识别方法有效。
数据集内容包括51组不同测试样例、动态场景模型识别所用的拓扑定义文档、各类测试产生的原始运行文件、扰动前后的S参数响应图、每组数据对应的拓扑结构图、识别结果与统计分析报告，以及对应的第三方测试验证资料。

This dataset is primarily developed to support research on filter model identification in dynamic scenarios. Its core objective is to derive the coupling matrix solutions under the current topology structure during the debugging process, based on known response curves, lateral coupling matrices, and specific physical or engineering features.
Dynamic scenario model identification is defined as: determining the coupling matrix of the current physical model under the target topology during the debugging scenario, based on existing response data and lateral coupling matrices, combined with specific structural features.
To achieve this objective, this test introduces a series of perturbed coupling matrices to simulate the possible changes during the debugging process, and adopts a set of real filter electromagnetic simulation data as the reference for performance evaluation. A total of 50 different topologies were selected in the experiment, and 50 dynamic perturbation tests were conducted for each topology respectively. In each test, a certain magnitude of perturbation is applied to the coupling matrix to simulate the possible uncertainties in practical applications. If a topology successfully identifies the target coupling matrix 45 times or more out of 50 tests, that is, the success rate is no less than 90%, the topology is considered to meet the performance indicators.
In addition, the test also includes a set of filter response parameters based on electromagnetic simulation. This set of data is obtained by applying different perturbations to a filter model, aiming to reflect the response changes in the actual environment. During the test, it is necessary to identify the coupling matrix solutions matching each set of response parameters based on the initial coupling matrix, and judge the identification accuracy accordingly. If the successful identification rate is no less than 90%, the topology and identification method used are considered valid.
The dataset includes 51 sets of different test samples, topology definition documents used for dynamic scenario model identification, original operation files generated by various tests, S-parameter response diagrams before and after perturbation, topology structure diagrams corresponding to each set of data, identification results and statistical analysis reports, as well as corresponding third-party test verification materials.