A new self-organizing method and its application to handwritten digit recognition
T. Shimada, K. Nishimura, Kazuhito Haruki · 2002
A self-organizing method for neural networks is proposed. This method reduces the calculation for learning considerably, and can be applied to real application problems, where many samples must be treated. The method has been applied to handwritten digit recognition. Samples incorrectly recognized have been reduced to 1/4 (learning data) or 2/3 (unknown data), compared with the multiple similarity method, which is a conventional statistical pattern classification method.>