In this paper, the influence of the input and output data scaling and normalization on the
neural network overall performances is investigated aimed at inverse problem-solving in …

The objective of this paper is to present methodology of the precise and reliable
determination of thermal diffusivity and linear coefficient of thermal expansion of the …

In this paper, a self-consistent inverse procedure is developed for the estimation of linear
thermal expansion coefficient and thermal diffusivity of solids from transmission …

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 …

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 …

In this paper, the possibility of determining the thermal, elastic and geometric characteristics
of a thin TiO2 film deposited on a silicon substrate, with a thickness of 30 μm, in the …

In this work, theoretically/mathematically simulated models are derived for the photoacoustic
(PA) frequency response of both volume and surface optically-absorbing samples in a …

The effect of the sample radius on the total photoacoustic signal processed by neural
networks trained with undistorted and distorted signals is carefully analyzed for modulation …

An analysis of the application of neural networks as a reliable, precise, and fast tool in open-
cell photoacoustics setups for the recognition of microphone effects in the frequency domain …

We developed a method of inverse problem solving in semiconductor photoacoustics based
on neural networks application. Simple structured neural networks, trained on a large set of …