Abstract
This paper presents the learning based self-organized additive fuzzy clustering method and its application of the use of electroencephalogram data. The proposed method combines the learning process to the conventional self-organized additive fuzzy clustering method by using inner product between a pair of degree of belongingness of objects. By learning the status of the noise in each process of iteration of the algorithm, the proposed method can obtain a more adaptable result. In future work, we believe that this technique can be useful for developing a man-machine interface in which the obtained classification result by the proposed method is used for the discrimination process of human's thoughts.
