完整後設資料紀錄
DC 欄位語言
dc.contributor.authorLi, Yimingen_US
dc.contributor.authorChou, Hung-Muen_US
dc.date.accessioned2014-12-08T15:25:28Z-
dc.date.available2014-12-08T15:25:28Z-
dc.date.issued2005en_US
dc.identifier.isbn90-6764-443-9en_US
dc.identifier.issn1573-4196en_US
dc.identifier.urihttp://hdl.handle.net/11536/17855-
dc.description.abstractIn this work we propose a hybrid intelligent circuit optimization technique for low noise amplifier (LNA) circuit. This method combines with the genetic algorithm (GA), Levenberg-Maxquardt (LM) method, and circuit simulator to perform automatic LNA circuit optimization. For a given LNA circuit, the optimization method considers the electrical specification such as S parameters: S-11, S-12, S-21, S-22, K factor, the noise figure, and the input third-order intercept point, simultaneously. The optimization procedure starts with loading the necessary parameters for circuit simulation, and then calls the circuit simulator for circuit simulation and evaluation. Sixteen optimized parameters of the LNA circuit composed with 0.18 mu m metal-oxide-silicon filed effect transistors (MOS-FETs) are acquired by our developed optimization prototype, where the aforementioned seven specifications axe all matched. The proposed circuit optimization method shows its robustness and practicability on radio-frequency (RF) circuit and wireless system on chip (SoC) design.en_US
dc.language.isoen_USen_US
dc.subjectlow noise amplifieren_US
dc.subjectgenetic algorithmen_US
dc.subjectLevenberg-Marquardten_US
dc.subjectcircuit designen_US
dc.subjectoptimizationen_US
dc.titleHybrid evolutionary approach to optimal design of CMOS LNA integrated circuitsen_US
dc.typeProceedings Paperen_US
dc.identifier.journalAdvances in Computational Methods in Sciences and Engineering 2005, Vols 4 A & 4 Ben_US
dc.citation.volume4A-4Ben_US
dc.citation.spage1088en_US
dc.citation.epage1091en_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.identifier.wosnumberWOS:000238054400264-
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