OPTIMAL QUANTIZERS FOR PROBABILITY DISTRIBUTIONS ON NONHOMOGENEOUS CANTOR SETS
Lakshmi Roychowdhury · arXiv (Cornell University) · 2015
Quantization of a probability distribution refers to the idea of estimating a given probability by a discrete probability supported by a finite set. Let $P$ be a Borel probability measure on $\mathbb R$ such that $P=\frac 1 4 P\circ S_1^{-1} +\frac 3 4 P\circ S_2^{-1}$, where $S_1$ and $S_2$ are two similarity mappings on $\mathbb R$ such that $S_1(x)=\frac 1 4 x $ and $S_2(x)=\frac 1 2 x +\frac 12$ for all $x\in \mathbb R$. Such a probability measure $P$ has support the Cantor set generated by $S_1$ and $S_2$. For this probability measure, in this paper, we give an induction formula to determine the optimal sets of $n$-means and the $n$th quantization errors for all $n\geq 2$. Using the induction formula we obtain some results and observations which are also given in this paper.