This paper proposes a neural network learning algorithm FTART(field theory-based adaptive resonance theory)that combines many neural network theories.It is based on the main idea of ART(adaptive resonance theory) and makes use of many merits of Field Theory and ARTMAP,etc.,and corrects the classification regarding the supposed possibility of examples in the instance space.FTART gains some goodness by employing a special conflict resolution process and dynamically expanding the classification area. Some benchmark test results are also given.