This study examined the effects of stimulus-feedback cooccurrence on rule-based and information-integration category learning. Rule-based categories are those for which a verbalizable rule is optimal. Information-integration categories are those for which the optimal rule is nonverbalizable. Participants performed a rule-based or an information-integration task where the stimulus co-occurred wi...

Genetic fuzzy rule selection is an effective approach to the design of accurate and interpretable fuzzy rule-based classifiers. It tries to minimize the complexity of fuzzy rule-based classifiers while maximizing their accuracy by selecting only a small number of fuzzy rules from a large number of candidate rules. One important issue in genetic fuzzy rule selection is the prescreening of candid...

This paper presents the recognition of Cantonese speech commands using a proposed neural fuzzy network with rule switches. By introducing a switch to each rule, the optimal number of rules can be learned. An improved genetic algorithm (CA) is proposed to train the parameters of the membership functions and the optimal rule set for the proposed neural fuzzy network. An application example of Can...