Charles A. Micchelli
Constructive Approximation
We consider a parametric family of multivariate density functions formed by mixture models from univariate functions of the type exp(–|x|α) for modeling acoustic feature vectors used in automatic recognition of speech. The parameter α is used to measure the non-Gaussian nature of the data. Previous work has focused on estimating the mean and the variance of the data for a fixed α. Here we attempt to estimate the α from the data using a maximum likelihood criterion. Among other things, we show that there is a balance between α and the number of data pointsNthat must be satisfied for efficient estimation. Numerical experiments are performed on multidimensional vectors obtained from speech data. © 2001 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
Charles A. Micchelli
Constructive Approximation
Charles A. Micchelli, Thomas Sauer, et al.
Results in Mathematics
Xin Chen, Xiaodong Cui, et al.
ICASSP 2011
Wolfgang Dahmen, Charles A. Micchelli
Trans. Am. Math. Soc.