Approximating logarithmic series

In summary, the conversation discusses the possibility of a certain equation and its validity for arbitrary values of n and h. There is a disagreement about the equality in question and its similarity to another equality in a linked pdf. It is explained that the difference lies in the upper limit of the summation. The conversation concludes with a clarification and understanding of the equation.
  • #1
22990atinesh
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1
Can anybody tell me how this is possible
Capture.PNG
 
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  • #2
It looks to me as if it isn't possible in the first place. Who claims it is ? Any restrictions on n and h ?
I see a common factor n in front and then something on the left that depends on n, whereas the remainder on the right does not depend on n.
 
  • #3
BvU said:
It looks to me as if it isn't possible in the first place. Who claims it is ? Any restrictions on n and h ?
I see a common factor n in front and then something on the left that depends on n, whereas the remainder on the right does not depend on n.
Please check this link
http://sarielhp.org/teach/2003/b_273/notes/12_recc.pdf
 
  • #4
Well, that's a start. Any more things potential helpers should know ? Such as: lg means base-2 logarithm (contrary to what wolfram thinks)

I managed to find lectures 10 and 11 as well, but drown in the understanding what the symbols stand for. I don't have a good impression of the recursion tree and am surprised to see ##a## and ##b## disappear (into 2 and 2 ?) and to see ##f## disappear as well. On the other hand an ##H## appears but isn't explained and a ##L## is explained but does not appear [edit]ah, sorry: I see: L is the number of terms in ##T(n)##.
 
  • #5
Is this supposed to hold for arbitrary "n" and "h"? If so we can check by taking specific values for n and h. If we take, say, n= h= 1, the formula becomes [itex]\frac{2}{log(2)- 0}= \frac{2}{1}[/itex] which clearly is not true unless the logarithm is to be "base 2". Is that the case?
 
  • #6
Formally, it looks like they replace the summation index ##i## by ##j=\lg n-i##, as that would give ##\sum_{j=\lg n-1}^1\frac{1}{j}##. Then they rename the summation index ##i##.

EDIT: sorry, that's for the equality on the first page in the linked pdf, not the equality in post 1. My confusion.
 
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  • #7
Samy_A said:
Formally, it looks like they replace the summation index ##i## by ##j=\lg n-i##, as that would give ##\sum_{j=\lg n-1}^1\frac{1}{j}##. Then they rename the summation index ##i##.

EDIT: sorry, that's for the equality on the first page in the linked pdf, not the equality in post 1. My confusion.
Actually I've seen lots of places where they have done it
See the below link at example the guy has done the same thing
http://clrs.skanev.com/04/problems/03.html
 
  • #8
HallsofIvy said:
Is this supposed to hold for arbitrary "n" and "h"? If so we can check by taking specific values for n and h. If we take, say, n= h= 1, the formula becomes [itex]\frac{2}{log(2)- 0}= \frac{2}{1}[/itex] which clearly is not true unless the logarithm is to be "base 2". Is that the case?
logarithm is base 2
 
  • #9
22990atinesh said:
Can anybody tell me how this is possible
View attachment 93593

The thing you posted is false. However, the specific step in the link is true. So please be careful when copying something next time.
Try to change variables ##i\rightarrow \log(n) - i##.
 
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  • #10
Note the subtle differences between Sariel and Skanev ! The former is a bit sloppy writing ##\lg(n/2) = \lg(n-1)## when he means ##\lg(n/2) = (\lg n-1)##.

And yes, Wolfram allows ##\lg## to be the base-2 logarithm, a sensible choice in algorithm analysis - so I was wrong to mope about that. Not used to the context, I am.

So: Picked up some of the vernacular, and Skanev subtask 5 helps out by being a lot more meticulous. Check it out (or do I have to spell it out ?)

[edit] ah, ##\mu m## was faster.
 
Last edited:
  • #11
22990atinesh said:
Actually I've seen lots of places where they have done it
See the below link at example the guy has done the same thing
http://clrs.skanev.com/04/problems/03.html
Yes, nothing wrong with it.
I was confused because the equality in the question and the somewhat similar equality in the linked pdf are different.
 
  • #12
22990atinesh said:
Can anybody tell me how this is possible
View attachment 93593
There appears to be an error in your equation. I looked up your reference and the upper limit is log(n)-1 not h-1. The equality results from replacing log(n)-i by i. All that does is doing the sum in the opposite direction.
 
  • #13
Thanks Everybody I get it :)
 

Related to Approximating logarithmic series

1. What is an approximation of a logarithmic series?

An approximation of a logarithmic series is a simplified version of the series that uses a finite number of terms to estimate the sum of an infinite series. It is a useful tool for calculating the value of a series without having to add an infinite number of terms.

2. How is an approximation of a logarithmic series calculated?

An approximation of a logarithmic series is calculated using a formula called the Taylor series, which expresses the value of a function as an infinite sum of terms. By truncating the series after a certain number of terms, we can get an estimate of the actual value of the series.

3. What is the purpose of approximating a logarithmic series?

The purpose of approximating a logarithmic series is to simplify complex mathematical calculations. By using a finite number of terms, we can get a close estimate of the actual value of the series without having to perform an infinite number of calculations.

4. What are some common applications of approximating logarithmic series?

Approximating logarithmic series is commonly used in fields such as physics, engineering, and finance. It can be used to calculate the growth rate of populations, the decay of radioactive substances, and the value of financial investments.

5. Can an approximation of a logarithmic series be accurate?

Yes, an approximation of a logarithmic series can be accurate, but it depends on the number of terms used in the approximation. The more terms we include, the closer the approximation will be to the actual value of the series. However, since it is still an estimate, there will always be a margin of error.

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