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Published on 8 November 2024
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Zhang,L. (2024). Amplifier gain exploration: Technical or structural means of enhancing the gain of an amplifier. Applied and Computational Engineering,81,83-91.
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Amplifier gain exploration: Technical or structural means of enhancing the gain of an amplifier

Lu Zhang *,1,
  • 1 School of Information Science and Technology, Northwest University, Xi’an,710000, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/81/20241041

Abstract

The primary function of an amplification circuit is to amplify the input dynamic signal without distortion. Therefore, there is aproportional relationship between the output and input signals, which is referred to as ‘gain’. Gain, the ratio of output voltage to input voltage, is a crucial performance metric for amplifiers and plays a vital role in electronic circuits. Amplifiers are now an indispensable part of various fields. Amplifier circuit structures vary widely, and different amplification circuits are used in different applications and fields due to their unique advantages and inevitable drawbacks. Practically, it is necessary to maximize strengths and minimize weaknesses by sele cting the most suitable amplification circuit. This paper analyzes several typical structural methods for enhancing amplifier gain and discusses the advantages and disadvantages of each structure. Through theoretical derivation and Cadence software simulation, it is demonstrated that the cascode, five-transistor OTA structure, and cascade structure play important roles in achieving circuit gain.

Keywords

MOSFET, Cascode, Five-Transistor OTA.

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Cite this article

Zhang,L. (2024). Amplifier gain exploration: Technical or structural means of enhancing the gain of an amplifier. Applied and Computational Engineering,81,83-91.

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:978-1-83558-563-4(Print) / 978-1-83558-564-1(Online)
Conference date: 21 November 2024
Editor:Mustafa ISTANBULLU, Xinqing Xiao
Series: Applied and Computational Engineering
Volume number: Vol.81
ISSN:2755-2721(Print) / 2755-273X(Online)

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