How do you understand the last 3 steps for convolution in the z-transform?

In summary, the conversation involved a student discussing their confusion with finding the inverse z-transform of a given equation. The teacher had briefly explained the steps on the board, but the student was still struggling to understand the last few steps. They specifically mentioned not understanding the last 3 steps and requested someone to explain them.
  • #1
Toyona10
31
0
Greetings,
We just had 1.5 classes about this topic (due to some unavoidable circumstances in our country...) so our teacher just scribbled and roughly explained them on the board...So after i got home i couldn't get some steps he did for convolution in z-transform:

find inverse z-transform of z^2/(z-2)(z-5)

so here, inverse of z/(z-2) is 2^n which is Un and inverse of z/(z-5) is 5^n which is Vn
so Vn*Un = Ʃ(from m=0 to n) Un-mVm

=Ʃ(from m=0 to n)2n-m5m
=Ʃ(from m=0 to n)2n(5m/2m
=2^nƩ(from m=0 to n)[5/2]m
=2^n[1+(5/2)+(5/2)^2 + (5/2)^3...(5/2)^n]

By convolution-

=2^n{[1(5/2)n+1 - 1]/(5/2 -1)}
=2^n[(5n+1-2n+1)/2n+1×3/2]
=1/3[5n+1-2n+1]

I don't get the last 3 steps, I would REALLY appreciate it if somebody would explain that ^^
 
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  • #2
anyone??
 

Related to How do you understand the last 3 steps for convolution in the z-transform?

1. What is the Z-transform?

The Z-transform is a mathematical tool used to analyze discrete-time signals and systems. It converts a discrete-time signal into a complex function of a variable z, which represents the frequency domain. It is similar to the Laplace transform used for continuous-time signals.

2. How is convolution used with the Z-transform?

Convolution is used with the Z-transform to analyze the output of a discrete-time system in response to a given input. It involves multiplying the Z-transforms of the input and system, and then taking the inverse Z-transform of the resulting product. This yields the output of the system in the time domain.

3. What is the difference between the Z-transform and the Fourier transform?

While both the Z-transform and the Fourier transform are used to analyze signals and systems, they differ in the type of signals they can analyze. The Z-transform is used for discrete-time signals, while the Fourier transform is used for continuous-time signals. Additionally, the Z-transform takes into account both the magnitude and phase of the signal, while the Fourier transform only considers the magnitude.

4. What is the region of convergence (ROC) in the Z-transform?

The ROC is a region in the complex plane where the Z-transform converges. It is important because it determines whether the inverse Z-transform exists and whether the system is stable. The ROC is typically represented as a ring in the complex plane, and its size and location are dependent on the properties of the signal and system being analyzed.

5. How is the Z-transform used in practical applications?

The Z-transform has many practical applications in fields such as signal processing, control systems, and communications. It is used to analyze and design filters, to model and control discrete-time systems, and to compress data in digital signal processing. It is also used in the design of digital communication systems, such as coding and decoding schemes.

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