Michael M. Li

Publication List Details

Period

2002 - 2009

Number

8

Co-Authors

Intelligent methods for solving inverse problems of backscattering spectra with noise : a comparison between neural networks and simulated annealing (2009)

Li, Michael M., Guo, Wanwu., Verma, Brijesh., Tickle, Kevin., O'Connor, John.

This paper investigates two different intelligent techniques - the neural network (NN) method and the simulated annealing (SA) algorithm for solving the inverse problem of Rutherford Backscattering...

RBF neural networks for solving the inverse problem of backscattering spectra (2007)

Li, Michael M., Verma, Brijesh., Fan, Xiaolong., Tickle, Kevin.

This paper investigates a new method to solve the inverse problem of Rutherford Backscattering (RBS) data. The inverse problem is to determine the sample structure information from measured spectra,...

RBF neural networks for solving the inverse problem of backscattering spectra (2007)

Li, Michael M., Verma, Brijesh., Fan, Xiaolong., Tickle, Kevin.

This paper investigates a new method to solve the inverse problem of Rutherford Backscattering (RBS) data. The inverse problem is to determine the sample structure information from measured spectra,...

Principal component analysis and neural networks for analysis of complex spectral data from ion backscattering (2006)

Li, Michael M., Fan, Xiaolong., Tickle, Kevin.

The problem of ion backscattering spectral data analysis, which is to determine the physical structure of a sample from the measured spectra, was studied with neural network techniques. A new method...

Artificial neural network techniques for analysis of ion backscattering spectra (2005)

Li, Michael M., Fan, Xiaolong., Verma, Brijesh., Balsys, Ronald J.

Ion backscattering spectrometry is an analysis technology that is dedicated to the compositional analysis of samples with the thickness of μm level. The problem of spectral data analysis, which is...

A study of comparison between genetic algorithm and simulated annealing applied to backscattering data analysis (2004)

Li, Michael M.

Genetic algorithm and simulated annealing are two stochastic optimisation techniques that have been widely used to solve complex, large-scale optimisation problems. This paper explores their...

A study of the charge state approach to the stopping power of MeV B, N and O ions in carbon (2004)

Li, Michael M., O'Connor, D. J., Timmers, H.

The charge state approach has been applied to describe the electronic stopping powers of swift O, N and B ions in carbon. According to the charge state model, the contributions to the electronic...