volume | PIER Journals

Abstract

To address the challenges in constructing the measurement matrix within the compressive sensing-based method of moments (CS-MoM) framework, this paper presents a novel dynamic extraction method based on row norm significance for impedance matrix compression. The proposed method first sorts the impedance matrix rows in descending order according to their row norm importance, followed by a dynamic extraction process that adapts the extraction density based on row significance. This strategy ensures dense extraction of high-importance rows to maintain matrix representativeness, while sparse extraction of low-importance rows preserves global structural coverage. Finally, through the validation of numerical results from three different computational models, it is demonstrated that the proposed method improves computational accuracy while ensuring computational efficiency compared to the uniform extraction-based novel CS-MoM method.

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Professor Zhonggen Wang

Dr. Yang Liu

Professor Wenyan Nie