SOLEIMANI, NASTARAN

SOLEIMANI, NASTARAN  

Dipartimento di Elettronica e Telecomunicazioni  

060366  

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Citazione Data di pubblicazione Autori File
Application of Different Learning Methods for the Modelling of Microstrip Characteristics / Soleimani, N.; Trinchero, R.; Canavero, F.. - 2020-:(2020), pp. 1-3. ((Intervento presentato al convegno 2020 IEEE Electrical Design of Advanced Packaging and Systems, EDAPS 2020 tenutosi a chn nel 2020 [10.1109/EDAPS50281.2020.9312887]. 1-gen-2020 Soleimani N.Trinchero R.Canavero F. EDAPS20_Soleimani.pdf09312887.pdf
Bridging the Gap Between Artificial Neural Networks and Kernel Regressions for Vector-Valued Problems in Microwave Applications / Soleimani, Nastaran; Trinchero, Riccardo; Canavero, Flavio G.. - In: IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. - ISSN 0018-9480. - STAMPA. - (2023), pp. 1-14. [10.1109/TMTT.2022.3232895] 1-gen-2023 Nastaran SoleimaniRiccardo TrincheroFlavio G. Canavero jnl-2023-TMTT-KRR-IEEE.pdf
Comparative Analysis of Prior Knowledge-Based Machine Learning Metamodels for Modeling Hybrid Copper–Graphene On-Chip Interconnects / Kushwaha, Suyash; Soleimani, Nastaran; Treviso, Felipe; Kumar, Rahul; Trinchero, Riccardo; Canavero, Flavio; Roy, Sourajeet; Sharma, Rohit. - In: IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY. - ISSN 0018-9375. - STAMPA. - (2022). [10.1109/TEMC.2022.3205869] 1-gen-2022 Soleimani, NastaranTreviso, FelipeTrinchero, RiccardoCanavero, Flavio + Comparative_Analysis_of_Prior_Knowledge-Based_Machine_Learning_Metamodels_for_Modeling_Hybrid_CopperGraphene_On-Chip_Interconnects.pdfTEMC-167-2022_Proof_hi.pdf
Compressed Complex-Valued Least Squares Support Vector Machine Regression for Modeling of the Frequency-Domain Responses of Electromagnetic Structures / Soleimani, N.; Trinchero, R.. - In: ELECTRONICS. - ISSN 2079-9292. - ELETTRONICO. - 11:4(2022), p. 551. [10.3390/electronics11040551] 1-gen-2022 Soleimani N.Trinchero R. electronics-11-00551-v2.pdfelectronics-1555570.pdf
Crosstalk analysis at near-end and far-end of the coupled transmission lines based on eigenvector decomposition / Soleimani, Nastaran; Alijani, Mohammad G. H.; Neshati, Mohammad H.. - In: AEÜ. INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS. - ISSN 1434-8411. - ELETTRONICO. - 112:(2019), p. 152944. [10.1016/j.aeue.2019.152944] 1-gen-2019 Soleimani, Nastaran + Crosstalk analysis at near-end and far-end of the coupled transmission.pdfNear end_Far_end.pdf
Crosstalk analysis of multi‐microstrip coupled lines using transmission line modeling / Soleimani, Nastaran; Alijani, Mohammad G. H.; Neshati, Mohammad H.. - In: INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING. - ISSN 1096-4290. - ELETTRONICO. - 29:6(2019), p. e21677. [10.1002/mmce.21677] 1-gen-2019 Soleimani, Nastaran + Crosstalk analysis of multi-microstrip coupled lines using.pdfRFMic-final-revised-03.pdf
Crosstalk analysis of uniform and nonuniform lossy microstrip-coupled transmission lines / Soleimani, N.; Alijani, M. G. H.; Neshati, M. H.. - In: INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING. - ISSN 1096-4290. - ELETTRONICO. - 29:11(2019). [10.1002/mmce.21916] 1-gen-2019 Soleimani N. + Crosstalk analysis of uniform and nonuniform lossy.pdfJournal Paper II.pdf
Detection of brain lesion location in MRI images using convolutional neural network and robust PCA / Ahmadi, Mohsen; Sharifi, Abbas; Jafarian Fard, Mahta; Soleimani, Nastaran. - In: INTERNATIONAL JOURNAL OF NEUROSCIENCE. - ISSN 0020-7454. - ELETTRONICO. - (2021), pp. 1-12. [10.1080/00207454.2021.1883602] 1-gen-2021 Soleimani, Nastaran + DetectionofbrainlesionlocationinMRIimagesusingconvolutionalneuralnetworkandrobustPCA.pdf
Power transmission through a single conductive element / GHadikolaei Alijani, Mohammad; Soleimani, Nastaran; Hassan Neshati, Mohammad. - (2019). 1-gen-2019 Nastaran Soleimani + US10868525.pdf
Vector-Valued Kernel Ridge Regression for the Modeling of High-Speed Links / Soleimani, Nastaran; Trinchero, Riccardo; Canavero, Flavio. - ELETTRONICO. - (2022), pp. 1-4. ((Intervento presentato al convegno 2022 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO) tenutosi a Limoges, France nel 06-08 July 2022 [10.1109/NEMO51452.2022.10038963]. 1-gen-2022 Soleimani, NastaranTrinchero, RiccardoCanavero, Flavio Soleimani_NEMO2022_FINAL.pdfVector-Valued_Kernel_Ridge_Regression_for_the_Modeling_of_High-Speed_Links.pdf