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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Optimal Design of Colpitts Oscillator Using Bat Algorithm and Artificial Neural Network (BA-ANN)

verfasst von : E. N. Onwuka, S. Aliyu, M. Okwori, B. A. Salihu, A. J. Onumanyi, H. Bello-Salau

Erschienen in: Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018

Verlag: Springer International Publishing

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Abstract

Oscillators form a very important part of RF circuitry. Several oscillator designs exist among which the Colpitts oscillator have gained widespread application. In designing Colpitts oscillator, different methods have been suggested in the literature. These ranges from intuitive reasoning, mathematical analysis, and algorithmic techniques. In this paper, a new meta-heuristic Bat Algorithm (BA) is proposed for designing Colpitts oscillator. It involves a combination of BA and Artificial Neural Network (ANN). BA was used for selecting the optimum pair of resistors that will give the maximum Thevenin voltage while ANN was used to determine the transient time of the optimized pairs of resistors. The goal is to select, among the several optimized pairs of resistors, the pair that gives the minimum transient response. The results obtained showed that BA-ANN gave a better transient response when compared to a Genetic Algorithm based (GA-ANN) technique and it also consumed less computational time.

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Vorheriges Kapitel Case-Based Parametric Analysis: A Method for Design of Tailored Forming Hybrid Material Component
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Metadaten
Titel
Optimal Design of Colpitts Oscillator Using Bat Algorithm and Artificial Neural Network (BA-ANN)
verfasst von
E. N. Onwuka
S. Aliyu
M. Okwori
B. A. Salihu
A. J. Onumanyi
H. Bello-Salau
Copyright-Jahr
2019
Buch
Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018

Print ISBN: 978-3-319-99995-1

Electronic ISBN: 978-3-319-99996-8

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-99996-8_3