Adaptive methods for solving inverse problems in laser raman spectroscopy of multi-component solutions

Authors:
S. A. Dolenko;S. A. Burikov;T. A. Dolenko;I. G. Persiantsev
Affiliations:
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia 119991;Department of Physics, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia 119991;Department of Physics, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia 119991;Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Leninskie Gory, Moscow, Russia 119991
Venue:
Pattern Recognition and Image Analysis
Year:
2012

Citing 3
Cited 0

Fundamentals of Artificial Neural Networks

Fundamentals of Artificial Neural Networks
Inductive Learning Algorithms for Complex Systems Modeling

Inductive Learning Algorithms for Complex Systems Modeling
A general regression neural network

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This study provides comparative analysis of approaches connected with application of neural network based algorithms for efficient solution of pattern recognition problem (inverse problem with discrete output) combined with solution of inverse problem with continuous output. The analysis is performed at the example of the problem of identification and determination of concentrations of inorganic salts in multi-component aqueous solutions by Raman spectrum.