Modern synergetic neural network for imbalanced small data classification.

ABSTRACT: Deep learning's performance on the imbalanced small data is substantially degraded by overfitting. Recurrent neural networks retain better performance in such tasks by constructing dynamical systems for robustness. Synergetic neural network (SNN), a synergetic-based recurrent neural network, has superiorities in eliminating recall errors and pseudo memories, but is subject to frequent association errors. Since the cause remains unclear, most subsequent studies use genetic algorithms to adjust parameters for better accuracy, which occupies the parameter optimization space and hinders task-oriented tuning. To solve the problem and promote SNN's application capability, we propose the modern synergetic neural network (MSNN) model. MSNN solves the association error by correcting the state initi

SUBMITTER: Wang Z 

PROVIDER: S-EPMC10514188 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature