Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
μARTMAP: use of mutual information for category reduction in Fuzzy ARTMAP
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Simulating the seismic response of embankments via artificial neural networks
Advances in Engineering Software
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Pattern recognition is an important aspect of a dominant technology such as machine intelligence. Domain specific fuzzy-neuro models particularly for the 'black box' implementation of pattern recognition applications have recently been investigated. In this paper, Sanchez's MicroARTMAP has been discussed as a pattern recognizer/classifier for the image processing problems. The model inherently recognizes only noise free patterns and in case of noise perturbations (rotations/scaling/translation) misclassifies the images. To tackle this problem, a conventional Hu's moment based rotation/scaling/translation invariant feature extractor has been employed. The potential of this model has been demonstrated on two problems, namely, recognition of alphabets and words and prediction of load from yield pattern of elasto-plastic analysis. The second example concerns with color images dealing with colored patterns. MicroARTMAP is also applied to other two civil engineering problems, namely (a) Indian Standard (IS) classification of soil and (b) prediction of earthquake parameters from the response spectrum in which no feature extractor step is necessary.