<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixtures of probability distributions, also known as mixed distributions, are an exciting new area for optimal quantization. In this paper, we investigate the optimal quantization for three different mixed distributions generated by uniform distributions associated with probability vectors.</p></abstract>

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixtures of probability distributions, also known as mixed distributions, are an exciting new area for optimal quantization. In this paper, we investigate the optimal quantization for three different mixed distributions generated by uniform distributions associated with probability vectors.

Quantization for a Mixture of Uniform Distributions Associated with Probability Vectors

Uniform distribution theory

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability...

Quantization for a Mixture of Uniform Distributions Associated with Probability Vectors

Pubblicato online: 24 lug 2020

Pagine: 105 - 142

Ricevuto: 18 ott 2019

Accettato: 01 mar 2020

DOI: https://doi.org/10.2478/udt-2020-0006

Parole chiave
Mixed distribution, uniform distribution, optimal sets, quantization error, quantization dimension, quantization coefficient

© 2020 Mrinal Kanti Roychowdhury et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Quantization for a Mixture of Uniform Distributions Associated with Probability Vectors

Pubblicato online: 24 lug 2020

Pagine: 105 - 142

Ricevuto: 18 ott 2019

Accettato: 01 mar 2020

DOI: https://doi.org/10.2478/udt-2020-0006

Parole chiaveMixed distribution, uniform distribution, optimal sets, quantization error, quantization dimension, quantization coefficient

© 2020 Mrinal Kanti Roychowdhury et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Parole chiave
Mixed distribution, uniform distribution, optimal sets, quantization error, quantization dimension, quantization coefficient