Convergence of a recurrence equation: x(k+1) = 0.5x(k) + u(k)

In summary, the problem asks that if a bounded sequence goes to zero, then a given point in that sequence will also go to zero. The author is having trouble bounding the relation and is looking for a way to proceed.
  • #1
Aerostd
18
0

Homework Statement



Hello. I am trying to prove a result that I have been making use of, but never really proved. Consider the recurrence equation

[itex]x(k+1) = 0.5 x(k) + u(k)[/itex],

where u(k) is a bounded sequence. For this problem, assume that u(k) goes to zero. I want to prove that x(k) goes to zero.

Homework Equations



If I use recursive substitution, I get for any k

[itex]x(k) = 0.5^{k}x(0) + \sum_{i=0}^{k-1}0.5^{i}u(k-i)[/itex]

The Attempt at a Solution



The first thing that came to my mind was to sandwich x(k) between two sequences that both went to zero. But I'm having some trouble bounding this relation. So the first thing I like to do to get an idea of how to proceed is to consider a simple input u(k) = 1/k. In this case, the recursive relation becomes

[itex]x(k) = 0.5^{k}x(0) + \sum_{i=0}^{k-1}\frac{0.5^{i}}{k-i}[/itex]

The first term is easy to bound. But what can I do with the second term. Can I make use of u_min = min(u(k)) and u_max = max(u(k)) in some special way? Can someone suggest some techniques or theorems that I can use to prove that x(k) goes to zero?
 
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  • #2
Have you tried replacing u(k-i) by M, where M = max(u(k))? M exist because in the problem statement u(k) is bounded.

Then use the sum of a geometric series formula.
 
  • #3
╔(σ_σ)╝ said:
Have you tried replacing u(k-i) by M, where M = max(u(k))? M exist because in the problem statement u(k) is bounded.

Then use the sum of a geometric series formula.

Hi. Thanks a lot for replying.

If I replace 0.5^{i}u(k-i) by M where M is it's max value, then I can get an upper bound on x(k). But this upper bound might blow up as k tends to infinity (for the case where M>1). I won't be able to conclude what happens to x(k) as k tends to infinity.
 
  • #4
Aerostd said:
Hi. Thanks a lot for replying.

If I replace 0.5^{i}u(k-i) by M where M is it's max value, then I can get an upper bound on x(k). But this upper bound might blow up as k tends to infinity (for the case where M>1). I won't be able to conclude what happens to x(k) as k tends to infinity.

Huh?

Replace u(k-i) with M. You get 0.5^{i}M. The sum of 0.5^{i} is known using the geometric series formula.

Anyway, forget that for now.

What you actually need is to use is the fact that if u(k) -> 0 the there exist a [itex] k_{0}[/itex] such that [itex] |u(k)| < \epsilon [/itex] for all [itex] k > k_{0}[/itex].

It is easy to show that [itex] 0.5^{k}[/itex] also tends to zero. So you could probably use the triangle inequality to get an epsilon to show that [itex] |x(k)| < \epsilon_{1,2}[/itex].
 
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  • #5
Sorry about that. I understand and can solve it now. Thanks.
 
  • #6
Can you post your solution attempt ?
 
  • #7
-- Show that x(k) goes to zero in the limit.

Let [itex] \epsilon > 0 [/itex]. Now, we know that [itex] 0.5^{k} [/itex] and [itex] u(k) [/itex] both go to zero, therefore, for all [itex] \epsilon_{1} > 0 [/itex], there exists [itex] k_{1}>0[/itex], such that if [itex] k > k_{1}[/itex], then [itex] | 0.5^{k} | < \epsilon_{1}[/itex] and [itex] | u(k) | < \epsilon_{1}[/itex]. Now

[itex] x(k) = | 0.5^{k} x(0) + \sum_{i=0}^{k-1} 0.5^{i} u(k-i) |[/itex]

[itex]< | \epsilon_{1} x(0) + \sum_{i=0}^{k-1} 0.5^{i} \epsilon_{1} | [/itex] for all [itex] k > k_{1}[/itex]

[itex]= | \epsilon_{1} x(0) + \frac{\epsilon_{1}(1-0.5^k)}{0.5} | [/itex]

[itex]= | \frac{0.5\epsilon_{1} x(0) + \epsilon_{1}(1-0.5^k)}{0.5} | [/itex]

[itex]= \epsilon_{1}| \frac{0.5 x(0) + (1-0.5^k)}{0.5} | [/itex]

Choose [itex]k_{1}[/itex] such that

[itex] \epsilon_{1}| \frac{0.5 x(0) + (1-0.5^k)}{0.5} | < \epsilon[/itex]

Now, for all [itex] \epsilon > 0[/itex], there exists [itex] k_{1}[/itex] such that [itex] k > k_{1}[/itex] implies
[itex]|x(k)| < \epsilon[/itex]

I hope it's right.
 
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  • #8
Aerostd said:
-- Show that x(k) goes to zero in the limit.

Let [itex] \epsilon > 0 [/itex]. Now, we know that [itex] 0.5^{k} [/itex] and [itex] u(k) [/itex] both go to zero, therefore, for all [itex] \epsilon_{1} > 0 [/itex], there exists [itex] k_{1}>0[/itex], such that if [itex] k > k_{1}[/itex], then [itex] | 0.5^{k} | < \epsilon_{1}[/itex] and [itex] | u(k) | < \epsilon_{1}[/itex]. Now

[itex] x(k) = | 0.5^{k} x(0) + \sum_{i=0}^{k-1} 0.5^{i} u(k-i) |[/itex]

[itex]< | \epsilon_{1} x(0) + \sum_{i=0}^{k-1} 0.5^{i} \epsilon_{1} | [/itex] for all [itex] k > k_{1}[/itex]

[itex]= | \epsilon_{1} x(0) + \frac{\epsilon_{1}(1-0.5^k)}{0.5} | [/itex]

[itex]= | \frac{0.5\epsilon_{1} x(0) + \epsilon_{1}(1-0.5^k)}{0.5} | [/itex]

[itex]= \epsilon_{1}| \frac{0.5 x(0) + (1-0.5^k)}{0.5} | [/itex]

Choose [itex]k_{1}[/itex] such that

[itex] \epsilon_{1}| \frac{0.5 x(0) + (1-0.5^k)}{0.5} | < \epsilon[/itex]

Now, for all [itex] \epsilon > 0[/itex], there exists [itex] k_{1}[/itex] such that [itex] k > k_{1}[/itex] implies
[itex]|x(k)| < \epsilon[/itex]

I hope it's right.
Edit:

Actually you should probably use [itex] k_{2}[/itex] to establish the final epsilon then use [itex] k_{0}= max(k_1,k_2)[/itex]
 
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  • #9
Something seemed fishy to me, so I went back to this and found a mistake. I need your help to see if what I have done this time is correct and legal.

I'll start from the top again.

-- Show that [itex]x(k)[/itex] goes to zero in the limit.

Let [itex]ϵ>0[/itex]. Now, we know that [itex]0.5k[/itex] and [itex]u(k)[/itex] both go to zero(by assumption), therefore, for all [itex]ϵ_{1}>0[/itex], there exists [itex]k_{1}>0[/itex], such that if [itex]k>k_{1}[/itex], then [itex]|0.5k|<ϵ_{1}[/itex] and [itex]|u(k)|<ϵ_{1}[/itex]. Now, let [itex]k > 2k_{1} +1 [/itex]...

[itex] | x(k) | = | 0.5^{k} x(0) + \sum_{i=0}^{k-1} 0.5^{i} u(k-i)| [/itex]
[itex] = | 0.5^{k} x(0) + \sum_{i=0}^{k_{1}} 0.5^{i} u(k-i) + \sum_{i=k_{1}+1}^{k} 0.5^{i}u(k-i) | [/itex]

The reason I did this is because in the sums, the u(k-i) goes backwards. So you can go [itex]k-k_{1}[/itex] steps back after which [itex] u(k-i) < \epsilon_{1} [/itex] is no longer true. Therefore

[itex] |x(k)| < | \epsilon_{1} x(0) + \sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1} + \sum_{i=k_{1}+1}^{k} 0.5^{i} u(k-i) | [/itex]

Now, over k_{1}+1 to k, u(k-i) has a max value. Let [itex] M [/itex] be that max value. Then

[itex] |x(k)| < | \epsilon_{1} x(0) + \sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1} + \sum_{i=k_{1}+1}^{k} 0.5^{i} M | [/itex]

Now, using the geometric series formula, I get

[itex] |x(k)| < | \epsilon_{1} x(0) + \sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1} + \frac{M 0.5^{k_{1}+1}}{0.5} + \frac{M 0.5^{k}}{0.5}| [/itex]

[itex] |x(k)| < | \epsilon_{1} x(0) + \sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1} + \frac{M \epsilon_{1}}{0.5} + \frac{M 0.5^{k}}{0.5}| [/itex]

Now, for any [itex]\epsilon > 0[/itex] we need to find a [itex]k_{2}[/itex] such that [itex]k > k_{2}[/itex] would give

[itex] | \epsilon_{1} x(0) |+ |\sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1}| + |\frac{M 0.5^{k_{1}+1}}{0.5}| + |\frac{M 0.5^{k}}{0.5}| < \epsilon [/itex]

[itex]0.5^{k} < \frac{0.5}{|M|}(\epsilon -| \epsilon_{1} x(0) |- |\sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1}| - |\frac{M \epsilon_{1}}{0.5}|)[/itex]

[itex] k = k_{2} > log(\frac{0.5}{|M|}(\epsilon -| \epsilon_{1} x(0) |- |\sum_{i=0}^{k_{1}} 0.5^{i} \epsilon_{1}| - |\frac{M \epsilon_{1}}{0.5}|))/log(0.5)[/itex] (since log(0.5) is negative)

Now, for any [itex] \epsilon > 0 [/itex], pick [itex]k = max(2k_{1}+1, k_{2}) [/itex]. Then

[itex] |x(k+1)| < \epsilon [/itex]

If someone could check this and give some feedback, I would appreciate it a lot. Thanks!
 
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FAQ: Convergence of a recurrence equation: x(k+1) = 0.5x(k) + u(k)

1. What is a recurrence equation?

A recurrence equation is a mathematical equation that describes a sequence of values, where each value is determined by the previous one. In other words, it is a way of expressing a relationship between a current term and previous terms in a sequence.

2. How do you determine the convergence of a recurrence equation?

To determine the convergence of a recurrence equation, you need to find the limit of the sequence as the number of terms approaches infinity. If the limit exists and is finite, then the sequence converges. If the limit does not exist or is infinite, then the sequence diverges.

3. What is the significance of the parameter u(k) in the recurrence equation x(k+1) = 0.5x(k) + u(k)?

The parameter u(k) represents the influence of external factors on the sequence. It can be a constant value or a function that changes with each term in the sequence. The presence of u(k) can affect the convergence of the sequence, as it introduces additional variability into the equation.

4. Can a recurrence equation converge to more than one value?

No, a recurrence equation can only converge to one value. If the limit of the sequence exists, it means that as the number of terms increases, the values in the sequence get closer and closer to that limit. Therefore, the sequence can only converge to one value.

5. How can the convergence of a recurrence equation be used in real-world applications?

The convergence of a recurrence equation can be used to model and predict the behavior of systems that involve repeated processes. This can be applied in various fields such as economics, biology, and engineering. Understanding the convergence of a sequence can also help in making decisions and optimizing processes in these applications.

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