Lower Bound for Derivatives of Costa's Differential Entropy
2021 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT)(2021)
Abstract
Let
$H(X_{t})$
be the differential entropy of an
$n$
-dimensional random vector
$X_{t}$
introduced by Costa. Cheng and Geng conjectured that
$C_{1}(m, n): (-1)^{m+1}(\mathrm{d}^{m}/\mathrm{d}^{m}t)H(X_{t})\geq 0$
. McKean conjectured that
$C_{1}(m, n): (-1)^{m+1}(\mathrm{d}^{m}/\mathrm{d}^{m}t)H(X_{t})\geq 0 (-1)^{m+1}(\mathrm{d}^{m}/\mathrm{d}^{m}t)H(X_{Gt})$
. McKean's conjecture was only considered in the univariate case before:
$C_{2}(1,1)$
and
$C_{2}(2,1)$
were proved by McKean and
$C_{2}(i, 1), i=3,4,5$
were proved by Zhang-Anantharam-Geng under the log-concave condition. In this paper, we prove
$C_{2}(1, n),\ C_{2}(2, n)$
and observe that McKean's conjecture might not be true for
$n\ > \ 1$
and
$m > 2$
. We further propose a weaker conjecture
$C_{3}(m, n): (-1)^{m+1}(\mathrm{d}^{m}/\mathrm{d}^{m}t)H(X_{t}) \ \geq\ (-1)^{m+1}\frac{1}{n}(\mathrm{d}^{m}/\mathrm{d}^{m}t)H(X_{Gt})$
and prove
$C_{3}(3,2), C_{3}(3,3), C_{3}(3,4)$
under the log-concave condition. A systematic procedure to prove
$C_{l}(m, n)$
is proposed and the results mentioned above are proved using this procedure.
MoreTranslated text
Key words
n-dimensional random vector X,univariate case,log-concave condition,Costa differential entropy
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