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Perturbation Robustness of Morphological Bidirectional Associative Memories Networks


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Perturbation Robustness of Morphological Bidirectional Associative Memories Networks
HE Chun-mei1YE Zheng-chun2HAN Mu3YE You-pei3
1. School of Information Engineering; 2. School of Mechanical and Electronical Engineering, East China Jiaotong University,Nanchang 330013,China; 3. School of Computer Science and Technology,NUST,Nanjing 210094,China
neural networks morphological bidirectional associative memories fuzziness perturbation training pattern pairs robustness
In view of the problem that the small perturbations of training pattern pairs may cause side effects on the outputs of neural networks, the influences of perturbations of training pattern pairs on the morphological bidirectional associative memories( MBAM) networks and fuzzy morphological bidirectional associative memories( FMBAM) networks are researched here. By comparing the output variations of the two training sample pairs before and after perturbations, the perturbation robustness of the MBAM networks and FMBAM networks is theoretically proved. The simulations show that the MBAM network has good robustness on the perturbation of training pattern pairs, and its rough training pattern pairs are acceptable. The FMBAM network robustness is not so good, and its training pattern pairs should have higher accuracy.


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Last Update: 2012-10-24