Muhammad A. Khattak;Daniele Romano;Giulio Antonini;Francesco Ferranti
{"title":"Derivatives-Enhanced Proper Orthogonal Decomposition for PEEC Models With Delays","authors":"Muhammad A. Khattak;Daniele Romano;Giulio Antonini;Francesco Ferranti","doi":"10.1109/LMWT.2024.3439595","DOIUrl":null,"url":null,"abstract":"This letter proposes a novel model order reduction (MOR) approach leveraging frequency-domain proper orthogonal decomposition (POD) for partial element equivalent circuit (PEEC) models characterized by neutral delayed differential equations (NDDEs). Our technique incorporates frequency-domain derivatives snapshots alongside frequency-domain response snapshots, thereby enhancing the accuracy of the reduced-order model while minimizing the computational overhead compared with solely utilizing frequency-domain response snapshots. A numerical example is provided to demonstrate the effectiveness and efficiency of the proposed method in both the frequency domain and the time domain.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"34 10","pages":"1135-1138"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10652252","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE microwave and wireless technology letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10652252/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This letter proposes a novel model order reduction (MOR) approach leveraging frequency-domain proper orthogonal decomposition (POD) for partial element equivalent circuit (PEEC) models characterized by neutral delayed differential equations (NDDEs). Our technique incorporates frequency-domain derivatives snapshots alongside frequency-domain response snapshots, thereby enhancing the accuracy of the reduced-order model while minimizing the computational overhead compared with solely utilizing frequency-domain response snapshots. A numerical example is provided to demonstrate the effectiveness and efficiency of the proposed method in both the frequency domain and the time domain.