LSSM based Korean character recognition and colored neural nets

摘要

The linear systems in a saturated mode (LSSM) model is applied to Korean character recognition. In general, conventional neural networks without uncommitted neurons cannot incorporate new patterns for recognition, and pattern recognition and reconstruction of many learned patterns cannot be performed simultaneously. It is shown that these problems can be solved by using a colored neural net model.