  Fuzzy implication functions have been widely investigated, both in
theoretical and practical fields. The aim of this work is to continue previous
works related to fuzzy implications constructed by means of non necessarily
associative aggregation functions. In order to obtain a more general and
flexible context, we extend the class of implications derived by fuzzy
negations and t-norms, replacing the latter by general overlap functions. We
also investigate their properties, characterization and intersections with
other classes of fuzzy implication functions.
