A Novel Self-Creating Neural Network for Learning Vector Quantization

This paper presents a novel self-creating neural network scheme which employs two resource counters to record network learning activity. The proposed scheme not only achieves the biologically plausible learning property, but it also harmonizes equi-error and equi-probable criteria. The training process is smooth and incremental: it not only avoids the stabilityand-plasticity dilemma, but also overcomes the dead-node problem and the de

• Type: Journal
• Year: 2000
• Where: NPL
• Authors: Jung-Hua Wang, Chung-Yun Peng
• Keywords: Neural Network Scheme, Neural Networks, NPL 2000, Vector Quantization