this paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. this estimation method is obtained by implementing ridge regression learning algorithm in the la- grangian dual space. the distance measure for fuzzy numbers that suggested by diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...

In this paper, we develop methods for outlier removal and noise reduction based on weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. The methods can be used by manifold learning methods such as Isomap, LLE and LTSA as a preprocessing procedure so as to obtain a more accurate reconstruction of the underlying nonlinear manifolds. Weighted principal compo...

We propose a new class of non-linear image recovery operators based on local smoothing applied both in the spatial domain (horizontal smoothing) and in the gray-level domain (vertical smoothing). The commonly used horizontal smoothing gives the way of reducing the noise level (noise filtering), whereas the vertical smoothing yields the edge preservation property. The method is indexed by a real...

Local linear M-smoothing is proposed as a method for noise reduction in one-dimensional (1D) signals. It is more appropriate than conventional local linear smoothing, because it does not introduce blurring of jumps in the signal. It improves local constant Msmoothing, by avoiding boundary effects at edges and jumps. While the idea of local linear M-smoothing is straightforward, numerical issues...

In this paper a nonlinear smoothing algorithm recently proposed by Tukey is described and evaluated for speech processing applications. Simple linear smoothing routines generally fail to provide adequate smoothing for data which exhibit both local roughness and sharp discontinuities. The proposed nonlinear smoothing algorithm can effectively smooth such data by using a combination of median smo...