부산대학교 도서관

Let X and Y be dependent random variables. This paper considers the problem of designing a scalar quantizer for Y to maximize the mutual information between the quantizer’s output and X , and develops fundamental properties and bounds for this form of quantization, which is connected to the log-loss distortion criterion. The main focus is the regime of low ${I}({X};{Y})$ , where it is shown that, if X is binary, a constant fraction of the mutual information can always be preserved using $\mathcal {O}(\log (1/{I}({X};{Y})))$ quantization levels, and there exist distributions for which this many quantization levels are necessary. Furthermore, for larger finite alphabets $2 < |\mathcal {X}| < \infty $ , it is established that an $\eta $ -fraction of the mutual information can be preserved using roughly $(\log (| \mathcal {X} | /{I}({X};{Y})))^{\eta \cdot (|\mathcal {X}| - 1)}$ quantization levels.