Understanding Convolution in Discrete Time: Solving the Homework Problem

In summary, the conversation is about finding the convolution of h2[n]*h2[n], which involves calculating the sum of the product of two functions. The correct formula for convolution is (h_2\ast h_2)(n) = \sum_{k=-\infty}^{\infty}\cdot h_2(k) h_2(n-k). The mistake made in the conversation was pulling out a constant term, which is not allowed in convolution. After realizing the mistake, the conversation ends with a humorous comment and a thank you.
  • #1
FrogPad
810
0
The following is all in discrete time, n is an integer

We are given that:
[tex] h_2(n) = \delta ( n ) + \delta ( n-1 ) [/tex]

I want to find the convolution of h2[n]*h2[n].

I don't really understand how to solve this properly.

So,
[tex] y(n) = \Sigma_{k=-\infty}^{k=\infty} (\delta(n)+\delta(n-1)) \times (\delta(n-k)+\delta(n-k-1)) [/tex]

So the [tex] (\delta(n)+\delta(n-1)) [/tex] pulls out because it is constant.

So,

[tex] y(n) = (\delta(n)+\delta(n-1)) \Sigma_{k=-\infty}^{k=\infty} \delta(n-k)+\delta(n-k-1) [/tex]

How do I even solve this?
The book gets
h_2(n)*h_2(n) = [tex] \delta(n) + \2\delta(n-1) + \delta(n-2) [/tex]

I don't understand how they get this.
 
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  • #2
FrogPad said:
[tex] y(n) = \Sigma_{k=-\infty}^{k=\infty} (\delta(n)+\delta(n-1)) \times (\delta(n-k)+\delta(n-k-1)) [/tex]

So the [tex] (\delta(n)+\delta(n-1)) [/tex] pulls out because it is constant.

You are not calculating the convolution correctly.

[tex](h_2\ast h_2)(n) = \sum_{k=-\infty}^{\infty}\cdot h_2(k) h_2(n-k)[/tex]
 
  • #3
omg...

haha


I'm going to to take a walk. That was a ridiculous mistake.

thanks man :)
 

Related to Understanding Convolution in Discrete Time: Solving the Homework Problem

What is convolution and why is it important in homework help?

Convolution is a mathematical operation that combines two functions to produce a third function. In homework help, convolution is often used to solve problems involving signal processing, image processing, and other areas of science and engineering.

What are the steps involved in solving a convolution problem?

The steps involved in solving a convolution problem include defining the functions involved, setting up the integral or summation, performing the convolution operation, and simplifying the resulting function.

Can convolution be applied to discrete as well as continuous functions?

Yes, convolution can be applied to both discrete and continuous functions. In the case of discrete functions, the integral is replaced with a summation.

What are some common applications of convolution in science and engineering?

Some common applications of convolution include image filtering, noise reduction, pattern recognition, and solving differential equations. It is also widely used in fields such as digital signal processing, computer vision, and machine learning.

Are there any tools or software available to help with convolution homework?

Yes, there are many tools and software available that can assist with convolution homework. Some examples include MATLAB, Python libraries like NumPy and SciPy, and online calculators specifically designed for convolution problems.

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