Topics
disjoint unionMilitary conflict
quantization errorElection
We consider probability distributions which are uniformly distributed on a disjoint union of balls with equal radius. For small enough radius the optimal quantization error is calculated explicitly in terms of the ball centroids. We apply the results to special self-similar measures
Due to the rapidly increasing need for methods of data compression, quantization has become a flouri...
For a large class of dyadic homogeneous Cantor distributions in R, which are not necessarily self-si...
Quantization for probability distributions refers broadly to estimating a given probability measure ...
In this paper, the problem of optimal quantization is solved for uniform distributions on some highe...
Let m be a centered Gaussian measure on a separable Banach space E and N a positive integer. We stud...
The quantization scheme in probability theory deals with finding a best approximation of a given pro...
The representation of a given quantity with less information is often referred to as `quantization\u...
AbstractIn this paper, we study the quantization dimension of a random self-similar measure μ suppor...
The quantization scheme in probability theory deals with finding a best approximation of a given pro...
Quantization for probability distributions concerns the best approximation of a d-dimensional probab...
In this paper, we first determine the optimal sets of n-means and the nth quantization errors for al...
Quantization for probability distributions concerns the best approximation of a d-dimensional probab...
In this paper, for a given family of constraints and the classical Cantor distribution we determine ...
In this paper, with respect to a family of constraints for a uniform probability distribution we det...
AbstractFor a probability measure P on Rd and n∈N consider en=inf∫mina∈αV(‖x−a‖)dP(x) where the infi...
Due to the rapidly increasing need for methods of data compression, quantization has become a flouri...
For a large class of dyadic homogeneous Cantor distributions in R, which are not necessarily self-si...
Quantization for probability distributions refers broadly to estimating a given probability measure ...
In this paper, the problem of optimal quantization is solved for uniform distributions on some highe...
Let m be a centered Gaussian measure on a separable Banach space E and N a positive integer. We stud...
The quantization scheme in probability theory deals with finding a best approximation of a given pro...
The representation of a given quantity with less information is often referred to as `quantization\u...
AbstractIn this paper, we study the quantization dimension of a random self-similar measure μ suppor...
The quantization scheme in probability theory deals with finding a best approximation of a given pro...
Quantization for probability distributions concerns the best approximation of a d-dimensional probab...
In this paper, we first determine the optimal sets of n-means and the nth quantization errors for al...
Quantization for probability distributions concerns the best approximation of a d-dimensional probab...
In this paper, for a given family of constraints and the classical Cantor distribution we determine ...
In this paper, with respect to a family of constraints for a uniform probability distribution we det...
AbstractFor a probability measure P on Rd and n∈N consider en=inf∫mina∈αV(‖x−a‖)dP(x) where the infi...
Due to the rapidly increasing need for methods of data compression, quantization has become a flouri...
For a large class of dyadic homogeneous Cantor distributions in R, which are not necessarily self-si...
Quantization for probability distributions refers broadly to estimating a given probability measure ...
Add to ORKG