Multi-Objective Genetic Algorithm Optimization of CMOS Operational Amplifiers

被引：0

作者：

Barra, Samir ^{[1
]}

Dendouga, Abdelghani ^{[1
,2
]}

Kouda, Souhil ^{[3
]}

Bouguechal, Nour-Eddine ^{[1
]}

机构：

[1] Univ Batna, Dept Elect, Adv Elect Lab LEA, Chahid Boukhlouf M El Hadi Ave, Batna, Algeria

[2] Ctr Dev Adv Technol CDTA, Microelectron & Nanotechnol Div, Algiers, Algeria

[3] Univ Msila, Dept Elect, Msila, Algeria

来源：

2012 24TH INTERNATIONAL CONFERENCE ON MICROELECTRONICS (ICM) | 2012年

关键词：

Multi-objective Genetic Algorithm (MOGA); Optimization; CMOS Analog Circuit; Operational Amplifier; ANALOG;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

this work studies the problem of CMOS operational amplifiers (op-amps) optimization. A front Pareto based-MOGA (Multi-Objective Genetic Algorithm) methodology is proposed to optimize the operational amplifier. The proposed approach is used to find the optimal dimensional transistor parameters in order to obtain operational amplifier performances for analog and mixed CMOS-based circuit applications. To evaluate the proposed approach, an example in both time and frequency domains for a two-stage CMOS Operational Transconductance Amplifier (OTA) is presented in 0.18 mu m process. The simulation results confirm the efficiency of MOGA in determining the device sizes in an analog circuit.

引用

页数：4

共 23 条

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