Applied linear operators and spectral methods/Differentiating distributions
< Applied linear operators and spectral methodsDifferentiation of a distribution
If is a differentiable function in
whose first derivative
is locally integrable, then the derivative
defines its own
distribution
Integrating by parts and noting that at the boundaries ,
because of compact support, we have
This suggests defining the derivative of any distribution via
We need to check that this definition satisfies the properties of a
distribution. We observe that if is a test function then so is
.
Linearity is obvious. What about continuity? If
is a zero
sequence, so is the sequence
and thus
tends to zero as
. Hence (1) defines a
distribution.
Remark: All distributions are infinitely differentiable is the class of test functions includes only infinitely differentiable functions.
Comment: One can take test functions which are only differentiable.
Then the distribution will only be
times differentiable. Thus, enlarging
the class of test functions reduces the class of distributions.
More generally, if is the
th derivative of the distribution
,
Distributions can be generated by functions which are not differentiable in the ordinary sense. However, we can differentiate them in the distribution sense.
For example, the derivative of the delta distribution gives us the dipole distribution:
Also, the derivative of the Heaviside function is given by
Since , from the fundamental theorem of calculus,
Therefore the derivative of the Heaviside function is the delta function.
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