Regularizing Multilayer Perceptron for Robustness

@article{Dey2018RegularizingMP,
  title={Regularizing Multilayer Perceptron for Robustness},
  author={Prasenjit Dey and Kaustuv Nag and Tandra Pal and Nikhil R. Pal},
  journal={IEEE Transactions on Systems, Man, and Cybernetics: Systems},
  year={2018},
  volume={48},
  pages={1255-1266}
}
The weights of a multilayer perceptron (MLP) may be altered by multiplicative and/or additive noises if it is implemented in hardware. Moreover, if an MLP is implemented using analog circuits, it is prone to stuck-at 0 faults, i.e., link failures. In this paper, we have proposed a methodology for making an MLP robust with respect to link failures… CONTINUE READING