Neural Networks-Based Real-Time Determination of the Laser Beam Spatial Profile and Vibrational-to-Translational Relaxation Time Within Pulsed Photoacoustics

Abstract

This paper concerns with the possibilities of computational intelligence application for simultaneous determination of the laser beam spatial profile and vibrational-to-translational relaxation time of the polyatomic molecules in gases by pulsed photoacoustics. Results regarding the application of neural computing through the use of feed-forward multilayer perception networks are presented. Feed-forward multilayer perception networks are trained in an offline batch training regime to estimate simultaneously, and in real-time, the laser beam spatial profile (profile shape class) and the vibrational-to-translational relaxation time from given (theoretical) photoacoustic signals. The proposed method significantly shortens the time required for the simultaneous determination of the laser beam spatial profile and relaxation time and has the advantage of accurately calculating the aforementioned quantities.