Yoshihiro Sugaya

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– Fuzzy inference models can conduct advanced inference using knowledge which is easily understood by humans. In this paper, we propose a leaning fuzzy inference model. The model can learn with experience data obtained by trial-and-error of a task. The learning of the model is executed after each trial of the task. Hence, it is expected that the achievement(More)
A fuzzy inference model for learning from experiences (FILE) is proposed. The model can learn from experience data obtained by trial-and-error of a task and it can stably learn from both experiences of success and failure of a trial. The learning of the model is executed after each of trial of the task. Hence, it is expected that the achievement rate(More)
—This paper addresses the automatic generation of a typographic font from a subset of characters. Specifically, we use a subset of a typographic font to extrapolate additional characters. Consequently, we obtain a complete font containing a number of characters sufficient for daily use. The automated generation of Japanese fonts is in high demand because a(More)