Z-transform of a discrete convolution

In summary, the result of multiplying two power series is a coefficient at z^n that is given by summing up all products of a_k z^k b_{n-k}z^{n-k} where 0\le k\le n.
  • #1
samuelandjw
22
0
Hi,

Suppose we have these two functions and their z-transforms are
[tex]P(r,z)=\sum_{t=0}^{\infty}P(r,t)z^t[/tex]
and
[tex]F(r,z)=\sum_{t=0}^{\infty}F(r,t)z^t[/tex].
Now we are going to transform the following convolution of P and F:
[tex]\sum_{t'\le{t}}F(r,t')P(0,t-t')[/tex].
The result is said to be
[tex]F(r,z)P(0,z)[/tex].
But I don't know how to obtain the result. There are two difficulties:(1)the upper limit of t' is t, which is finite. (2)the two summations are coupled.
Anyone can help?
 
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  • #2
It should be [itex] z^t[/itex], not [itex] t^z[/itex]; then it is just the standard power series multiplication.
 
  • #3
Hawkeye18 said:
It should be [itex] z^t[/itex], not [itex] t^z[/itex]; then it is just the standard power series multiplication.
Sorry about the typo. But my problem remains. Could you show a bit more on the decoupling process?
 
  • #4
If you multiply 2 power series [itex] \sum_{k=0}^\infty a_k z^k [/itex] and [itex] \sum_{k=0}^\infty b_k z^k [/itex], the coefficients in the power series of of the product are given by the discrete convolution.

To get the term with [itex]z^n [/itex] in the product you need to add up all products [itex] a_k z^k b_{n-k}z^{n-k} [/itex], [itex] 0\le k \le n [/itex]. Thus the coefficient at [itex]z^n[/itex] is given by [itex] \sum_{k=0}^n a_k b_{n-k} [/itex]

In your case [itex] a_k = F(r,k) [/itex], [itex] b_k = P(0, k)[/itex].
 
  • #5
Hawkeye18 said:
If you multiply 2 power series [itex] \sum_{k=0}^\infty a_k z^k [/itex] and [itex] \sum_{k=0}^\infty b_k z^k [/itex], the coefficients in the power series of of the product are given by the discrete convolution.

To get the term with [itex]z^n [/itex] in the product you need to add up all products [itex] a_k z^k b_{n-k}z^{n-k} [/itex], [itex] 0\le k \le n [/itex]. Thus the coefficient at [itex]z^n[/itex] is given by [itex] \sum_{k=0}^n a_k b_{n-k} [/itex]

In your case [itex] a_k = F(r,k) [/itex], [itex] b_k = P(0, k)[/itex].

Thanks! Starting from the result is indeed easier!
 

1. What is the Z-transform of a discrete convolution?

The Z-transform of a discrete convolution is a mathematical tool used to convert a discrete-time signal from the time domain to the frequency domain. It is represented by the capital letter Z and is used to analyze the behavior of a discrete system.

2. How is the Z-transform of a discrete convolution calculated?

The Z-transform of a discrete convolution is calculated by taking the Z-transforms of the individual components and multiplying them together. This is represented by the convolution theorem, which states that the Z-transform of a convolution is equal to the product of the Z-transforms of the individual signals.

3. What is the significance of the Z-transform of a discrete convolution in signal processing?

The Z-transform of a discrete convolution is an important tool in signal processing as it allows us to analyze the frequency response of a discrete system. This information is useful in designing filters and understanding the behavior of signals in different systems.

4. How does the Z-transform of a discrete convolution differ from the Fourier transform?

The Z-transform of a discrete convolution is a generalization of the Fourier transform for discrete signals. While the Fourier transform operates on continuous signals, the Z-transform is specifically designed for discrete-time signals. Additionally, the Z-transform includes information about the system's initial conditions, while the Fourier transform does not.

5. Can the Z-transform of a discrete convolution be used to find the inverse transform?

Yes, the Z-transform of a discrete convolution can be used to find the inverse transform. This is done by using the partial fraction decomposition method, which breaks down the Z-transform into simpler, more manageable parts that can be inverted using inverse Z-transforms.

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