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Pattern recognition by distributed coding: test and analysis of the power space similarity method

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2 Author(s)
T. Kobayashi ; Graduate Sch. of Technol., Tokyo Univ. of Agric. & Technol., Japan ; M. Nakagawa

This paper considers pattern recognition methods using distributed coding. These methods permit rapid learning from a large number of training samples; their recognition speed is high regardless of the size of the learning samples. This paper presents both basic algorithm and extended algorithms. Experiments with a large database of off-line handwritten numeric patterns are then described using the power space similarity method, being a type of distributed coding. Finally the effectiveness of the technique is considered.

Published in:

Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on

Date of Conference:

26-29 Oct. 2004