Application of higher order statistical factors and hamming’s artificial neural network to classification of material microstructure

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Application of higher order statistical factors and hamming’s artificial neural network to classification of material microstructure

Alexander Mikhalyov, Denis Mikhalyov

National Academy of Sciences of Ukraine.

DOI:

https://doi.org/10.7494/cmms.2001.2.0010

Abstract:

The method of classification of material microstructure accounting for texture is presented in the paper. The texture is defined as orientation of elements in three dimensions. The features of the microstructure are identified using higher order statistical analysis. The analysis is based on evaluation of semi invariants. Finally, the Hamming artificial neural network was applied for classification of microstructures. Example of application of the developed method to classification of five classes of materials is demonstrated in the paper. Application was performed using MatLab environment and 90% accuracy of classification was achieved.

Cite as:

Mikhalyov, A., Mikhalyov, D. (2001). Application of higher order statistical factors and hamming’s artificial neural network to classification of material microstructure. Computer Methods in Materials Science, 1(2), 116 – 122. https://doi.org/10.7494/cmms.2001.2.0010

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