This paper proposes a novel feature selection method for the fuzzy neural networks and presents an application example for 'personalized' facial expression recognition. The proposed method is shown to result in a superior performance than many existing approaches.

In this paper, we propose a robust adaptive algorithm for impulsive noise suppression. The perturbation of the input signal as well as the perturbation of the estimation error are restricted by M-estimation. The threshold used in M-estimation is obtained from the proposed adaptive variance estimation. Simulations show that the proposed algorithm is less vulnerable to the impulsive noise than the conventional algorithm.