Abstract
T.Kohonenが提唱した学習ベクトル量子化法(Learning Vector Quantization:LVQ)は単純なアルゴリズムにもかかわらず強力なパターン認識能力を持っている.LVQにファジィ理論を適用したファジィ学習ベクトル量子化法(Fuzzy Learning Vector Quantization:FLVQ)はLVQよりもさらにデータの特徴抽出力の高いネットワークの構築が可能である.本論文はFLVQの学習則を用いたパターンマッチング法によって手書き漢字の認識実験を行い, その有効性と問題点を明らかにする.
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