L-2.7: Recurrence Relation [ T(n)= T(n/2) +c] | Master Theorem | Example-2 | Algorithm
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- เผยแพร่เมื่อ 21 ม.ค. 2020
- #MasterMethod#algorithm
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![L-2.6: Recurrence Relation [ T(n)= 8T(n/2) + n^2 ] | Master Theorem | Example#1 | Algorithm](http://i.ytimg.com/vi/FBKjvXGGCJM/mqdefault.jpg)
I've been following you for almost a year now. It's been really helpful throughout. I've suggested your videos to other students as well. Thank you for wrapping up the whole idea in a few minutes clearly.
Such an amazing Master theorem explanation! Literally the best on the internet! Thanks a lot for this @Gate Smashers ❤
In a very short time u became my hero in all the teachers. Please keep teaching sir very soon you will become the best teacher. I really appreciate and very much impressed with your knowledge sir. Not only this subject u cover every part of DAA, CAO, Electronics which were burden of yesterday, you made it all crystal clear
Whenever im free , i put on his video on youtube but i dont watch it, so that he gets the views and ads for doing such a great work for free :) @Gate Smashers
Wow.. Thank you so much
One gmail account gives only one view no matter how many times you see
@@hemanthsaimadala4135not now
@@hemanthsaimadala4135perhaps viewed hours are counted
@@hemanthsaimadala4135To ek hi vid thodi dektha hoga sari dekhta hog na bhi.... akela admi aur kya kre 😅😅😅😅
brilliantly explained ... just 2 hours ago before viewing this series, I knew nothing and now I can say i know significant stuffs... thanks a lot ..
great teaching skills!! on the point video!! really appreciate your efforts!!
Thanks Sir It helped me after 1 year of upload and helpful to others too. 😊😊
Thank You For practice questions 😃!!
Do we need to necessarily bring down the constant while calculating the U(n) ?
(The one which we multiplied with logn)
Because through the table only the logarithm part is said to be considered
you're great sir !!! what amazing tricks you have for studies, big fan sir
Thank you sir for all the questions you provided. It helped me so much for my exams.
This tutorial is very helpful and it is explained in very good manner .
Thnks bhai/sir
One of best videos
i ever seen sir. Thank you so much sir. waiting for more videos related to gate exam ?
sir i really appreciate your efforts and your teaching skills. i have a request could you please make videos on iteration and recursion tree method?
Soon we will upload...
thanks u sooo much ,wasa utube pa jldy kisi ki samj ni ati pr apka lectures ki samj ati ha .Great skills
thank you sirji for the questions also, got'em all.
The video was really good and helpful. Thank you for the practice questions!
I cannot find the practice questions. Can you please share the link?
short and easily explained ...thanks a lot
3:52 great explanation!
thanks a lot ❤
Thankyou so much sir, for your great efforts.
crystal clear concept explanation.
Excellent commitment.
Thank you for the practice problems sir..:)
Thank you Sir . outstanding explanation.
you are hope of many engineers 😊
Thank you so much for the practice questions .. love you sir ..
u can share with me those practise questions
👍 Thank you sir!
Excellently explain...
Boht badiya. Thank you so much.
Is it always the case that we get the log to the base 2 in the third case for U(n)?
gjb gjb gjb....... superb sir.......
practice set , and pdf ,,,It's very helpful
Thank you sir
Sir please provide gate previous year question and discuss this question...
Well explained sir!!thnku
Jahapna tusi great ho... Toufa Kabul kro🙏🏻🙏🏻
Hi sir your videos are most interactive and easy to understand I have one query regarding the question 3 in the document provided in the link. If I calculate it is resulting me 8T(n/2)+qn = n, but the correct option in the sheet provided as n^3 could you please, explain this problem.
wowww amazing lecture
The running time of an algorithm T(n), where ‗n‘ is the input size, is given by-
T (n) = T(n/2)+ logn, if n > 1 = p, if n = 1
where p, q are constants. The order of this algorithm is-
(a) n2(b) loglogn
(c) logn (d) (logn)2
i am getting loglogn as answer on this problem sir.
(Logn)^2
Really great sir.
Thank you for giving practice questions.
Ab sabke Gate SMASH kar dunga!
Please Discuss/ Explain Recursion Tree Problem also
Tq so so much sir. This video is very useful.... sir can u pl make d videos on imp topics, tricks and tips for questions on algorithms considering nic -nileit exam
Thanks sir for the great video, practice questions really help.
Where is the link??
T(n)= 8T(n/2) + (n^3/ log^2 n) sir for this question your method does not work h(n) is does not have category for to get u(n)
T(n)=4T(n/2) + (n^2/ log n) same for this question
Thank you sir...
SIR YOUR CONTENT IS VERY LESS BUT ITS EFFICIENT IN MAY TIMES
thank you sir..:)
Sir daa ki series aage bhi bnao pls,, aapne bohat kam topics cover kiye h, jo sufficient nhi h slabus point of view se gate k... Nice video
Good lecture
Sir if there will be log in f(n) then how to solve that by this table for example T(n) =2T(n/2)+n/(log^2n)
all great videos sir
Thank you sir for the questions
Thanks and welcome
thankyou sir
Great
Thankyou sir
hello sir, can you please explain this question
The running time of an algorithm T(n), where ‗n‘ is the input size, is given by-
T (n) = T(n-1)+ 1, if n > 1 = p, if n = 1
where p, q are constants. The order of this algorithm is-
try back substitution. Master's Theorem is invalid for this question.
Good explanation
In i was see this topic .I think like this is very dificult topic now this time this very easist topic in this syallbus
Where is the link for questions?
sir what if we get h(n) = (log n)^-1 then it will go in which case???
the question was T(n)=4T(n/2) + n^2/log n
kindly answer this sir, your method is very effective but I cant get this question
@Gate Smashers
The running time of an algorithm T(n), where ‗n‘ is the input size, is given by-
T (n) = 3T(n/3)+ n/2, if n > 1
The order of this algorithm is-
If we solve this que by master method, then h(n) value will come constant. Isn't it?
When h(n) will be constant then convert h(n) to third form (logn)^i,i>=O and then after solving t(n)=nlogn.
Tnx sir👍❤️
Thanks 😊🇧🇩
The running time of an algorithm T(n), where ‗n‘ is the input size, is given by-
T (n) = 8T(n/2)+ qn, if n > 1 = p, if n = 1
where p, q are constants. The order of this algorithm is-
(a) n 2 (b) n n
(c) n 3 (d) n
Solution: Option (c)
Sir, how it is n^3 ? I got n as an answer. Please explain..
Log a to the base b will be 3.. so it will be n3 .. and U(n) will come as O(1)
sir if log(base2)power(n) = nlog2 = O(n)
then why we put it O(log2N) atlast
I solved the questions in the doc given in description & got all 7 correct 😉
last question m n(logn)^2 kaisa aya ?? i got n +(log n)^2 as answer so where did the n come from in answer??
can u plz provide docs link
Sir what about master theorem for substract and conquer... Please upload sir
Sir gate exam ke liye master theorm par jyada focus kre ya substitution method par recurrence relation mein??
Thank you for the material of questions
where is material?
Where is the Question File?
I couldn't find it in the description box..
Thank you for the amazing lectures sir❤
4th sem?
Sir, Can we get the answers uploaded for the practise questions you have shared so that i can verify the steps followed are right or wrong?
Where is the link please share here i didn't get it
good class
So beautiful sir.From Bangladesh.
Sir i have a question..
if my eq is t(n) = 8T(n/2)+3n^2 how should i solve it
In the first question of the pdf the answer comes out to be O(n log n). But its given as O(n). Can u please explain.
U are god
Sir , would U pls attach answers for the qns using substitution method . Using master method it's easy to solve but using substitution method I am not getting ans .
If any one solved using substitution method for the practice qns pls .... provide ans document
sir please slove this
T(n)=2T(n/2)+n/logn
Thank you sir..for the PDF..😊
Kha mili pdf
@@vaishnavihingnekar1986 PDF is in the description..☺️
@@vaishnavihingnekar1986 I think you got it..👍
Sir, is this another method of master's theorem?
I can't find the link to the file where more problem questions are given. can you reply me with the link in comment?
kindly solve the recurrence relation t(n)=t(3n/4)+1
o(logn)
completed
❤️❤️
T(n) = 8T(n/2) + n^3/logn
what is the time complexity of this question and why
Sir, Is this method applicable to decreasing functions also? for example t(n) = 2T(n-2) + n
No, bcz b should greater then 1
Sir iteration method ki video plz
Sir i don't know how to solve log question.............means what is value for nlog33
How did the value of i=0 ? please you didn't explain it.
There s a table of h(n) and u(n) ....from there what s " i " ?
Can you please solve T(n) = 2T(n/2) + nlogn using the same concept ?
Did you find any answer to this??
Can you please explain the Given Pdf Link Questions =...:) I have solved the Questions but there is confusion in Some Questions...
i have doubt in a question plz rply me sir question is T(n)=25t(n/5)+n^4
sir wheres the link for extra questions
Please provide me the solution of Q3 in the attached practice sheet.?
h(n) log base 2 n
Right?
can anyone explain why we took base as 2, as in log base 2 n)^0, isn't it given the common log in 3rd case??
bcz here the problem is based on binary algo.
If sir H(n) =2^n then what will be the value of U(n)?
Did you find any answer to this? Or does this method doesn't work for this
Sir it's not working on 5T(n/4) + n^2,
Where can i find the notes?? Can anyone help i can't find those notes of unsolved questions
f(2N+1)=f(2N)=f(N)+logN sir how can solve it the answer give in upper bound
please upload solution of practice questions,
where are the practice question bro