Quantum neural networks (QNNs): inherently fuzzy feedforward neural networks

@article{Purushothaman1997QuantumNN,
  title={Quantum neural networks (QNNs): inherently fuzzy feedforward neural networks},
  author={Gopathy Purushothaman and Nicolaos B. Karayiannis},
  journal={IEEE transactions on neural networks},
  year={1997},
  volume={8 3},
  pages={
          679-93
        }
}
This paper introduces quantum neural networks (QNNs), a class of feedforward neural networks (FFNNs) inherently capable of estimating the structure of a feature space in the form of fuzzy sets. The hidden units of these networks develop quantized representations of the sample information provided by the training data set in various graded levels of certainty. Unlike other approaches attempting to merge fuzzy logic and neural networks, QNNs can be used in pattern classification problems without… CONTINUE READING
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