Time Complexity of Algorithms and Asymptotic Notations [Animated Big Oh, Theta and Omega Notation]#1
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- Опубликовано: 7 сен 2024
- Time complexity is, the relation of computing time and the amount of input.
The commonly used asymptotic notations used for calculating the running time complexity of an algorithm are:
Big oh Notation (Ο)
Omega Notation (Ω)
Theta Notation (θ)
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In average case upperbound the value of c must be 5 but you provide 4 for the c value which does not satisfy the condition when c=4 and n=1 apart from that video is excellent
C=4 and n>=2 will satisfy
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which is the time complexity of the following sequence? and why?
int n, i, j, k, s=0;
cin>>n;
for(i=1; i
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Do we use these asymptotic notation for find and represent time complexity of worst,best and average case using big oh ,omega,Theta respectively
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The best case complexity of any algorithm is always O(1)
Why don't youtubers add the refernces in the description?
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Sir which software do you use?
why do low rate of growth means best case (omega)?
Big oh is the upperbound, big omega is lowerbound and big theta is tightbound. They don't correspond to worst case, best case and average case😢
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In which software u edited this viedo sir
Pls Do DS/Algo And Python
Though your teaching style is awesome, but the explanation is not correct.. we will not use Big oh as worst case , Omega as best case..Big oh or Omega or theta alone can be used for best, worst, average..
Hey......I think you are confused... Let me explain it for you...
Big O notation specifically describes the worst case scenario. It represents upper bound running time complexity of an algorithm.....
Yes , what you said is correct, be it any case (best or worst) , we can use any Notation to describe any case.
what do you mean by worst case time complexity is big o of n^2...? your explanation is absolutely wrong
ayo what the fuck
omg..... what a wrong explanation..... bro you need to be clear that worst case time complexity is not the upper bound.
what do you mean by best case upper bound?