A granular reflex fuzzy min-max neural network for classification
IEEE Transactions on Neural Networks
Construction of a neuron-fuzzy classification model based on feature-extraction approach
Expert Systems with Applications: An International Journal
A probabilistic fuzzy approach to modeling nonlinear systems
Neurocomputing
M-FMCN: modified fuzzy min-max classifier using compensatory neurons
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
The pattern classification based on fuzzy min-max neural network with new algorithm
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
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This paper proposes a fuzzy min-max neural network classifier with compensatory neurons (FMCNs). FMCN uses hyperbox fuzzy sets to represent the pattern classes. It is a supervised classification technique with new compensatory neuron architecture. The concept of compensatory neuron is inspired from the reflex system of human brain which takes over the control in hazardous conditions. Compensatory neurons (CNs) imitate this behavior by getting activated whenever a test sample falls in the overlapped regions amongst different classes. These neurons are capable to handle the hyperbox overlap and containment more efficiently. Simpson used contraction process based on the principle of minimal disturbance, to solve the problem of hyperbox overlaps. FMCN eliminates use of this process since it is found to be erroneous. FMCN is capable to learn the data online in a single pass through with reduced classification and gradation errors. One of the good features of FMCN is that its performance is less dependent on the initialization of expansion coefficient, i.e., maximum hyperbox size. The paper demonstrates the performance of FMCN by comparing it with fuzzy min-max neural network (FMNN) classifier and general fuzzy min-max neural network (GFMN) classifier, using several examples