Mentor: Arteom ZvavitchDepartment of Theoretical Mathematics, |
Supervisor: Gideon SchechtmanWeizmann Institute of Science |
where
and,
, for all i such
that
and
are independent random variables that each assume the values
with probabilities
.
The actual inequality (in which
and
are not necessarily
the best) was proved by Khintchine. But we are looking for the best constants
and
that satisfy the inequality
for all natural numbers n. For all p, a solution and proof
was given in [1]. Here we present another proof, for p > 3, which
uses only elementary calculus.
.
Therefore, we can write the inequality in the following way:
Using the definition of mathematical expectation, we arrive to the following formula:
And finally:
As changing the signs of the
does not change the sum, we may assume that every
is non-negative. For n=1, we obtain
.
If
and
for some k, without loss of generality let k=n. Then note
that:
and that the inequality is therefore
Thus, the equality for n reduces to the inequality for n-1.
We would like to show that to find the best value of
,
it suffices to find the upper bound of
for all valid ns.
We now define the following function f:
with
.
It follows from Theorem 1
that f is only maximal when the non-zero
s
are equal.
Proof of Theorem 1:
We prove Theorem 1
by contradiction. Let us suppose that f is maximal for some
,
such that, without loss of generality,
.
We define following function:
with
as a constant
dependent upon the
sequence,
:
and with
and
. Note that
,
,
and
, for all
.
Because
,
and
are not zero-functions.
If we can show that
increases at
, then we have
a contradiction because f increases with
and is therefore not maximal for
as assumed.
Proof of Lemma 1:
and therefore
and
.
Note that
for any
.
Define the following constant:
.
Thus, c > 0.
Note that
and
Also note that
From this point forward, k (and
)
shall be understood as
(and
) and l (and
)
as
(and
).
Replacing
and
with explicit values, we obtain the following equation:
Note that
, there is
an
such that
.
The inverse is also true. Therefore, the equation can be condensed:
Now we compare every non-negative
with its corresponding
.
Note that when the summation constraint is
,
the sum is greater than or equal to the sum when the summation constraint
is
, that is
Let us prove that each summand is greater than 0, which will prove that
.
For each summand, define the constants:
and
. Note that
.
Then:
Therefore, it is enough to prove that for all x > y > 0
Note that
and
.
Thus, if we can prove that
is less than 0, we will prove that
is greater than 0 for valid values of x and y.
Case 1: y-1=0 The question that arises is if
is differentiable, or, more specifically, if
is differentiable at y = 1.
for y-1 > 0
for y-1 < 0
By the definition of the derivative,
(if the limit exists).
To prove that the limit exists, we take the limit from both sides.
So thus
and
.
Otherwise, when
,
Case 2: y-1>0
Case 3: y-1<0
Therefore,
is greater
than 0 for x > y > 0. Note that this inequality does not
hold for
Thus,
and Lemma
1
has been proven.
Thus, Theorem 1 has been proven.
Q.E.D.
constant for the Khintchine Inequality has been derived for p > 3.
implies
, then we could
also get the contradiction with which we proved Theorem 1.
Comments to: Joseph Turian / < jude@ai.mit.edu
>
Back
to my research home page