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Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks
(Silicon, 2020)
In this paper, a simple multilayer perceptron neural network with forward signal propagation was designed and used to simultaneously determine the main physical parameters, such as: the thermal diffusivity, thermal expansion ...
Correction to: Photoacoustic Measurements of the Thermal and Elastic Properties of n-Type Silicon Using Neural Networks (Silicon, (2020), 12, 6, (1289-1300), 10.1007/s12633-019-00213-6)
(Silicon, 2020)
The original version of the article unfortunately contained an error. © 2020, Springer Nature B.V.
The author name ‘Кatarina Lj. Djordjevic’ was inadvertently
captured twice. The correct author group is shown above.
Improvement of Neural Networks Applied to Photoacoustic Signals of Semiconductors with Added Noise
(Silicon, 2021)
This paper provides an overview of the characteristics of different neural networks trained on the same theoretical database of n-type silicon photoacoustic signals. By adding different levels of random Gaussian noise to ...
Computationally intelligent description of a photoacoustic detector
(Optical and Quantum Electronics, 2020)
In this article, a method for determination of photoacoustic detector transfer function as an accurate representation of microphone frequency response is presented. The method is based on supervised machine learning ...
Photoacoustic optical semiconductor characterization based on machine learning and reverse-back procedure
(Optical and Quantum Electronics, 2020)
This paper introduces the possibility of the determination of optical absorption and reflexivity coefficient of silicon samples using neural networks and reverse-back procedure based on the photoacoustics response in the ...