It has been recently discovered that a faithful representation for the shape of some simple distributions can be constructed using invariant statistics [1, 2]. In this paper, we c...
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
The learned parametric mixture method is presented for a canonical cost function based ICA model on linear mixture, with several new findings. First, its adaptive algorithm is fu...
Wavelet-domain hidden Markov models (HMMs) have been recently proposed and applied to image processing, e.g., image denoising. In this paper, we develop a new HMM, called local co...
In this paper, we proposed the principal component analysis (PCA) fuzzy mixture model for speaker identification. A PCA fuzzy mixture model is derived from the combination of the P...