Adaptive and precise peak detection algorithm for fibre Bragg grating using generative adversarial network

• Autorzy: Kumar Sunil , Sengupta Somnath

Identyfikatory

DOI

10.24425/opelre.2022.144227

• Języki publikacji: EN

Abstrakty

EN

An adaptive and precise peak wavelength detection algorithm for fibre Bragg grating using generative adversarial network is proposed. The algorithm consists of generative model and discriminative model. The generative model generates a synthetic signal and is sampled for training using a deep neural network. The discriminative model predicts the real fibre Bragg grating signal by the calculation of the loss functions. The maxima of loss function of the discriminative signal and the minima of loss function of the generative signal are matched and the desired peak wavelength of fibre Bragg grating is determined. The proposed algorithm is verified theoretically and experimentally for a single fibre Bragg grating peak. The accuracy has been obtained as ±0.2 pm. The proposed algorithm is adaptive in the sense that any random fibre Bragg grating peak can be identified within a short wavelength range.

Słowa kluczowe

EN

Fibre Bragg grating; generative model; discriminative model; loss function

• Wydawca: Stowarzyszenie Elektryków Polskich ; Polska Akademia Nauk ; Wojskowa Akademia Techniczna im. Jarosława Dąbrowskiego
• Czasopismo: Opto-Electronics Review
• Rocznik: 2022
• Tom: Vol. 30, No. 4
• Strony: art. no. e144227
• Opis fizyczny: Bibliogr. 24 poz., rys., tab., wykr.

Twórcy

autor

Kumar Sunil

• Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

autor

Sengupta Somnath

• Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

Bibliografia

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Uwagi

In the manuscript “Adaptive and precise peak detection algorithm for fibre Bragg grating using generative adversarial network”, the authors have contributed as follows: S. K carried out the study of all the parameters which are used in the proposed peak detection technique, the design of peak detection algorithm, and the result analysis. Drafting and writing of the manuscript was carried out by S. S.