The main drawback of traditional predictive vector quantization (PVQ) is the time consuming encoding process. In order to reduce the computational complexity, an algorithm called mean value predictive vector quantization (MVPVQ) is proposed in this paper. Input vectors are classified into smooth vectors and non-smooth vectors before encoding. Different kinds of input vectors are encoded with di...

We study the problem of estimating the mean of a multivariate distribution based on independent samples. The main result is the proof of existence of an estimator with a non-asymptotic sub-Gaussian performance for all distributions satisfying some mild moment assumptions.

This work is concerned with testing the population mean vector of nonnormal high-dimensional multivariate data. Several tests for high-dimensional mean vector, based on modifying the classical Hotelling T2 test, have been proposed in the literature. Despite their usefulness, they tend to have unsatisfactory power performance for heavy-tailed multivariate data, which frequently arise in genomics...

In this note, we formulate a general modified mean curvature based equation for image smoothing and enhancement. The key idea is to consider the image as a graph in some R”, and apply a mean curvature type motion to the graph. We will consider some special cases relevant to greyscale and color images.

On the mean curvature of a unit vector field. Abstract We present an explicit formula for the mean curvature of a unit vector field on a Riemannian manifold, using a special but natural frame. As applications, we treat some known and new examples of minimal unit vector fields. We also give an example of a vector field of constant mean curvature on the Lobachevsky (n + 1) space.

Mean shape-gain vector quantization (MSGVQ) is extended to include negative gains and square isometries. Square isometries together with a classi cation technique based on average block intensities enable us to enlarge the MSGVQ codebook size without any additional storage requirements while keeping the complexity of both the codebook generation and the encoding manageable. Variable rate codes ...

We emphasize that the composite structure of the nucleon may play quite an important role in nuclear physics. It is shown that the momentum-dependent repulsive force of second order in the scalar field, which plays an important role in Dirac phenomenology, can be found in the quark-meson coupling (QMC) model, and that the properties of nuclear matter are well described through the quarkscalar d...

For a continuous complex-valued function g on the real line without zeros, several notions of a mean winding number are introduced. We give necessary conditions for a Toeplitz operator with matrix-valued symbol G to be semi-Fredholm in terms of mean winding numbers of detG. The matrix function G is assumed to be continuous on the real line, and no other apriori assumptions on it are made.

Mallows has conjectured that among distributions which are Gaussian but for occasional contamination by additive noise, the one having least Fisher information has (two-sided) geometric contamination. A very similar problem arises in estimation of a non-negative vector parameter in Gaussian white noise when it is known also that most, i.e. (1 − ǫ), components are zero. We provide a partial asym...

SUMMARY Classification tasks in computer vision and brain-computer interface research have presented several applications such as biometrics and cognitive training. However, like in any other discipline, determining suitable representation of data has been challenging, and recent approaches have deviated from the familiar form of one vector for each data sample. This paper considers a kernel be...