학술논문
Incremental backpropagation learning networks
Document Type
Periodical
Author
Source
IEEE Transactions on Neural Networks IEEE Trans. Neural Netw. Neural Networks, IEEE Transactions on. 7(3):757-761 May, 1996
Subject
Language
ISSN
1045-9227
1941-0093
1941-0093
Abstract
How to learn new knowledge without forgetting old knowledge is a key issue in designing an incremental-learning neural network. In this paper, we present a new incremental learning method for pattern recognition, called the "incremental backpropagation learning network", which employs bounded weight modification and structural adaptation learning rules and applies initial knowledge to constrain the learning process. The viability of this approach is demonstrated for classification problems including the iris and the promoter domains.