# Does this notion of entropy have a name?

Recently I stumbled upon the following notion of entropy which seems quite natural to me. I am looking for its "real" name and/or any references where it might come up. I tried searching online for, e.g., generalized versions of entropy but could not find anything like it.

For $$\delta \in [0,1]$$ and $$x \in \{0,1\}^n$$, let $$B_\delta(x) = \{y \in \{0,1\}^n \mid d_H(x,y) \le \delta \}$$ be the (closed) $$\delta$$-Hamming ball around $$x$$, where $$d_H$$ is the relative Hamming distance. For a random variable $$X$$, define $$H_\delta(X) = \mathbb{E}_{x \gets X}\left[ \log \frac{|B_\delta(x)|}{\Pr[X \in B_\delta(x)]} \right]$$ as the "$$\delta$$-ball entropy" of $$X$$.

This is the same as the standard (i.e., Shannon) entropy $$H(Y_X)$$ of the random variable $$Y_X$$ obtained by first sampling a value $$x$$ according to $$X$$ and then uniformly picking a random element of $$B_\delta(x)$$. It seems interesting in that it "evens out" the entropy around each point $$x$$. Also, $$H_0(X) = H(X)$$ is the standard entropy and $$H_1(X) = H(U_n) = n$$.

• Finally, the operation of sampling from a ball around x is vaguely reminiscent of convolution math.stackexchange.com/questions/999236/… Commented Jul 22, 2021 at 10:26
• @Aryeh Off the top of my head, one possible motivation is in coding theory: Say $X = U_C$ is uniformly distributed over some subset $C$ of $\{ 0,1 \}^n$. Then it is easy to see that $H_\delta(U_C)$ is maximized (for subsets of $\{0,1\}^n$ of the same size) iff $C$ is a code of minimum distance $> \delta$. So in this case $H_\delta(U_D)$ gives a measure for how far a subset $D$ is from such an ideal code $C$. (Of course, in this example $X$ is always uniform but I am sure there is something interesting to be said about general distributions too.) Commented Jul 22, 2021 at 15:19
• @Aryeh Also, I am asking about random variables taking values in the Hamming space $\{0,1\}^n$. AFAICT convolution is defined for real-valued variables. I am not sure how that would carry over. Commented Jul 22, 2021 at 15:23
• Convolution can be defined over groups, see that link in my comment. Commented Jul 22, 2021 at 16:31
• @Aryeh Aha, so another perspective is $H_\delta(X) = H(Z)$ with $Z = X \oplus U_\delta$, where $\oplus$ is the XOR operation and $U_\delta$ is the uniform distribution on $B_\delta(0)$. Commented Jul 23, 2021 at 11:58

This is called "output entropy". Suppose you have a communications channel that takes a string and then outputs a random string within a relative $$\delta$$ radius of it. If you use the input distribution $$X$$ for communicating over this channel, the entropy of the output distribution would be the quantity you are after.