A Neural Network Approach to Transistor Circuit Design

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Thomas L. Hemminger
Thomas L. Hemminger
α Pennsylvania State University Pennsylvania State University

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A Neural Network Approach to Transistor Circuit Design

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Abstract

Transistor amplifier design is an important and fundamental concept in electronics, typically encountered by students at the junior level in electrical engineering. This paper focuses on two configurations that employ neural networks to design bipolar junction transistor circuits. The purpose of this work is to determine which design best fits the required parameters. Engineers often need to develop transistor circuits using a particular topology, e.g., common emitter, common collector, or common base. These also include a set of parameters including voltage gain, input impedance, and output impedance. For the most part, there are several methodologies that can provide a suitable solution, however the objective of this work is to indicate which external resistors are necessary to yield useful designs by employing neural networks.

References

2 Cites in Article
  1. A Sedra,K Smith (2015). Microelectronic Circuits.
  2. R Jaeger (1997). M.D. Bryce Policies and Methods for Industrial Development. Mc Graw-Hill Series in International Development. New York, London, Sydney, Toronto, Mc Graw-Hill Book Company, 1965, X p. 309 p., 60/–..

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Thomas L. Hemminger. 2016. \u201cA Neural Network Approach to Transistor Circuit Design\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 16 (GJCST Volume 16 Issue D1): .

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Issue Cover
GJCST Volume 16 Issue D1
Pg. 15- 20
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-D Classification: C.2.1
Version of record

v1.2

Issue date

December 16, 2016

Language
en
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Published Article

Transistor amplifier design is an important and fundamental concept in electronics, typically encountered by students at the junior level in electrical engineering. This paper focuses on two configurations that employ neural networks to design bipolar junction transistor circuits. The purpose of this work is to determine which design best fits the required parameters. Engineers often need to develop transistor circuits using a particular topology, e.g., common emitter, common collector, or common base. These also include a set of parameters including voltage gain, input impedance, and output impedance. For the most part, there are several methodologies that can provide a suitable solution, however the objective of this work is to indicate which external resistors are necessary to yield useful designs by employing neural networks.

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A Neural Network Approach to Transistor Circuit Design

Thomas L. Hemminger
Thomas L. Hemminger Pennsylvania State University

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