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Published on 8 November 2024
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Jiang,Y.;Zhao,L. (2024). Research and optimization of the gain characteristics of cascode amplifiers. Applied and Computational Engineering,101,247-255.
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Research and optimization of the gain characteristics of cascode amplifiers

Yancheng Jiang 1, Lechen Zhao *,2,
  • 1 School of Microelectronics, Shanghai University, Shanghai, 200444, China
  • 2 School of Microelectronics, Xi’an jiaotong University, Xi’an, 710100, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/101/20241054

Abstract

With the continuous development of IC technology, high-performance operational amplifiers are widely used in various circuit systems such as high-speed Analog-to-Digital Converters (ADCs), Digital-to-Analog Converters (DACs), switched capacitor filters, bandgap voltage reference sources, precision comparators. The amplifier has become the core unit circuit of analog IC and mixed-signal IC design, and its performance directly affects the overall performance of the circuit and system. The design of high-performance operational amplifiers has always been one of the hotspots in the research of analog IC design in order to meet the needs of various application fields. Cascode Amplifier is a classic structure widely used in high-frequency and high-gain electronic circuits. This project aims to study the gain characteristics of cascode amplifiers, explore the main factors affecting their gain, and propose methods to optimize the gain. Through theoretical analysis and simulation, the influence of different parameters on gain is verified. Then the optimization strategy is summarized to provide a reference for actual circuit design.

Keywords

Folded-cascode, gain, operational amplifier.

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Cite this article

Jiang,Y.;Zhao,L. (2024). Research and optimization of the gain characteristics of cascode amplifiers. Applied and Computational Engineering,101,247-255.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation

Conference website: https://2024.confmla.org/
ISBN:978-1-83558-691-4(Print) / 978-1-83558-692-1(Online)
Conference date: 12 January 2025
Editor:Mustafa ISTANBULLU
Series: Applied and Computational Engineering
Volume number: Vol.101
ISSN:2755-2721(Print) / 2755-273X(Online)

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