RCCN:径向基础竞争与合作网络

Sukhan Lee, S. Shimoji
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引用次数: 4

摘要

径向基双向竞争与合作网络(RCCN)是一种通过有效利用容纳边界来容纳和生成径向基函数单元(rbf)的双向映射网络。分析和仿真结果表明,自动生成方案为网络提供了必要和充分的增强,分层学习方案保证了映射的精度,映射方案对两个方向的多对多关系处理具有足够的精度,使用椭球边界比使用圆形边界更有效和灵活。RCCN可能会产生大量的rbf,并且由于使用有噪声的样本进行学习而导致准确率下降。然而,如果允许rbfu在最优学习方案下具有单独的容纳边界大小,则可以期望更高的效率
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RCCN: radial basis competitive and cooperative network
The radial basis bidirectional competitive and cooperative network (RCCN) is a bidirectional mapping network that accommodates and generates radial basis function units (RBFUs) with the help of efficient use of the accommodation boundaries. The analysis and simulation show that the automatic generation scheme provides the necessary and sufficient enhancement of the network, the hierarchical learning scheme ensures the desired accuracy in mapping, the mapping scheme processes the many-to-many relation for both directions with sufficient accuracy, and using ellipsoidal boundaries is more efficient and flexible compared to circles. RCCN may create an enormous number of RBFUs and degenerate in accuracy by learning with noisy samples. However, greater efficiency can be expected if RBFUs are allowed to have individual accommodation boundary sizes under the optimal learning scheme.<>
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