Convolution between two different distribution

Hello

I want to generate C(u) in the following:

C(u)=a(-u)*b(u) {a(-u) convolution b(u)}

which a is impulsive (for example [0 0 0 0 0 1 0 0 0 0]) and b is a probability distribution (for example a Normal distribution)

Thank you

[Walter Roberson]

What do you intend a(-u) and b(u) to mean? Is a(-u) subscripting with a "u" that happens to be negative? If so then if b(u) is to indicate subscripting, then it would be with a negative value, and subscripting a probability distribution at a position would not appear to make sense.

[Image Analyst]

To know what a(-u) is, you need to know which element is the "origin" so we can flip the vector about that origin. Anyway, the answer will of course just be b again, with some padding of zeros on the outer edges.

[Adam]

Can you not just use the builtin conv function?

[jafar]

To Walter Roberson, Image Analyst and Adam

a(u) and b(u) are two probability density functions ( any pdf could be used e.g two gaussian distributions with different mean, or any other distributions)

Explanation of whole question is attached

thank you

[Image Analyst]

Nothing was attached.

[jafar]

Attached file

Answer 1

[Image Analyst]

If the origin is halfway between elements 5 and 6 of "a", then just do

C = conv(fliplr(a), b, 'full');

[jafar]

Thank You

No!

The origin is not halfway between elements 5 and 6 of "a", it is on zero,