guys can anyone tell me the link from where i can read about the big o ,big
w and big q ...i read from corma but i didnt get theses from that...thnx in
advance
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saurabh is right nd or U can also download lecture 2 of series
Introduction to Algorithm mit lecture . It is jst awesome .
On 12/15/11, saurabh singh saurab...@gmail.com wrote:
Introduction to Algorithms Coreman
On Wed, Dec 14, 2011 at 8:21 PM, Shashank Jain shashan...@gmail.com wrote:
I
I need to study both space and time complexities. What is the best source?
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Introduction to Algorithms Coreman
On Wed, Dec 14, 2011 at 8:21 PM, Shashank Jain shashan...@gmail.com wrote:
I need to study both space and time complexities. What is the best source?
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To
an interseting problem
for a fibonacci series
the recurrence relation is
t(n)=t(n-1)+t(n-2)+O(1)
on solving it gives upper bound of O(n^2)
but when draw tree for the recurcsion we see that it is growing
exponentially giving a complexity of O(2^n).
so what is the complexity for fibonaacci series
it is O(n)
actually we use memoization in recursion to avoid calculating same
subproblem.
On Wed, Sep 14, 2011 at 9:38 PM, tech coder techcoderonw...@gmail.comwrote:
an interseting problem
for a fibonacci series
the recurrence relation is
t(n)=t(n-1)+t(n-2)+O(1)
on solving it gives upper
@Aanchal : My mistake... Its complexity can't be O(n^2)
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Hi ,
can you tell me that how do we arrive at the complexity of the repetitive
division theorem to find GCD. I tried to read it on net but was not able to
find a satisfactory answer. Is it log ( max(a,b)) or is it max of 5+max
number of digits(a,b) . . Can anybody clarify this and how you arrive
Can someone please help me with finding the complexity of below code:
/*The code is of finding all possible combinations of coins (given in array,
each having infinite supply) that sum upto given target value.*/
void solve(int index[], int arr[], int target, int cursum, int n, int sz)
{
cnt++;
really sorry for that,
here is the complete code:
#includeiostream
using namespace std;
void print(int arr[], int index[], int n)
{
int i=1;
while(i=n)
{
coutarr[index[i]] ;
i++;
}
coutendl;
}
void solve(int index[], int arr[], int target, int cursum, int n, int sz)
{
Its complexity is same as of finding the all combination if a given string .
it is O(n!)
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Ravinder Kumar
B.Tech Final Year
Computer Science and Engineering
MNNIT Allahabad
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Can we prove this??
On Wed, Aug 3, 2011 at 1:45 AM, Ravinder Kumar ravinde...@gmail.com wrote:
Its complexity is same as of finding the all combination if a given string
.
it is O(n!)
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*With Regards :*
Ravinder Kumar
B.Tech Final Year
Computer Science and Engineering
MNNIT
I was asked a similar question in an interview, and the interviwer told me
that it is O(n^2), I have no idea how he got that!!
On Wed, Aug 3, 2011 at 1:47 AM, aanchal goyal goyal.aanch...@gmail.comwrote:
Can we prove this??
On Wed, Aug 3, 2011 at 1:45 AM, Ravinder Kumar
My mistake .I only saw the program flow which is similar to
permutation .
Its DP similar to 0,1 knapsack
Complexity is O(nc)
where c is size of knapsack
and n is number different of items
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*With Regards :*
Ravinder Kumar
B.Tech Final Year
Computer Science and Engineering
MNNIT
But this is not dp rite? I know knapsack problem, it has 2 nested for loops,
thats why it is O(nc). And also, here we have infinite supply of each item.
And we want all possible ways of getting the sum, not just one way.
Here, function is recursively called, like a dfs is performed here... So,
it depends on target sum .
Size of index array is depends on target sum .
Try to dry run it you will get hint .
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@Ravinder : Its not a DP problem.. If it was, where are the sub problems
reused or in other words, where is memoization ??
@Anchal : Its complexity is O(n^2). Look at the following segment in ur code
:
for(int i=index[n];isz;i++)
{
index[n+1]=i;
let sum=45
int arr[]={1,2,3,4,5}; /*43545 times the function solve is called*/
/*2611 ways of achieving the sum (2611 ways will
be printed)*/
if,
int arr[]={1,3,10,30,75}; /*2931 times the function solve is called*/
/*53 ways of
@ Ankit Sambyal,
please explain me why is it O(n^2) taking into account what the number of
times solve is called (in my example above.)
On Wed, Aug 3, 2011 at 10:36 AM, aanchal goyal goyal.aanch...@gmail.comwrote:
let sum=45
int arr[]={1,2,3,4,5}; /*43545 times the function solve is called*/
sorry, *target=45*, not sum. sum=0 when we call the function the first time.
On Wed, Aug 3, 2011 at 10:39 AM, aanchal goyal goyal.aanch...@gmail.comwrote:
@ Ankit Sambyal,
please explain me why is it O(n^2) taking into account what the number of
times solve is called (in my example above.)
Running time can be found by solving this recursion.
T(sz,target) = SUM {1=i=sz} T(i,target-1)
T(sz,0) = c
I think it is around O(sz^target)
Thanks
Nitin
On Wed, Aug 3, 2011 at 10:40 AM, aanchal goyal goyal.aanch...@gmail.comwrote:
sorry, *target=45*, not sum. sum=0 when we call the function
it is O(plg5)
Best Wishes
Sachin Sharma
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@sachin: Explain pls...!!?
On 7/28/11, sachin sharma sachin.bles...@gmail.com wrote:
it is O(plg5)
Best Wishes
Sachin Sharma
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@Puneet,
get_power(int a, int b) works in O(logb) as you keep on dividing b with
2...
you are calling that method *P *times in *func(int p) *method.
So it is *plogb...*u r passing 5 as b valueit will be *plog5*
On Thu, Jul 28, 2011 at 11:45 AM, Puneet Gautam
k...thanks...
On 7/28/11, Rajeev Kumar rajeevprasa...@gmail.com wrote:
@Puneet,
get_power(int a, int b) works in O(logb) as you keep on dividing b with
2...
you are calling that method *P *times in *func(int p) *method.
So it is *plogb...*u r passing 5 as b valueit will be
Time complexity..?
int get_power(int a, int b)
{
if(!b) return 1;
if(b%2) return a * get_power(a, b/2);
return get_power(a, b/2);
}
int func(int p)
{
int sum = 0;
for(int i = 1; i = p; ++i) {
sum += get_power(i, 5);
}
return sum;
}
Is it O(plgp) or O(plg5)
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If u could find the (n/4)th element of an array in O(n) time, then what is
the worst time complexity of quick sort algo if this algo is used to decide
the pivot element.
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fun(n)
{
if(n=2)
return (1);
else
return ((fun(n-1)*fun(n-2));
}
find the order of complexity .
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O(2^n)
On Sat, Jan 22, 2011 at 8:58 PM, Decipher ankurseth...@gmail.com wrote:
fun(n)
{
if(n=2)
return (1);
else
return ((fun(n-1)*fun(n-2));
}
find the order of complexity .
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To post
Could u pls explain ??
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For more options,
T(n) = T(n-1) + T(n-2) + O(1)
On Sat, Jan 22, 2011 at 11:28 PM, Decipher ankurseth...@gmail.com wrote:
Could u pls explain ??
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f(n) = sqrt(n) [squate root of n]
g(n) = log(^2) [log of (n square)]
For the above pair of functions is f(n) = Ω(g(n))? i.e., is there some
c 0, such that f(n) = g(n) for all n? Give proof in case answer is
yes or no.
it is impossible 2 give a formula or a generic method to calculate the
complexity for any algo..
method to calcuate complexity differs per algo
On Mon, May 3, 2010 at 11:45 PM, scanfile rahul08k...@gmail.com wrote:
Pls can anyone help me out that how to calculate the complexity of any
check the design and analysis of algorithm by thomas cormen
On Mon, May 3, 2010 at 11:45 PM, scanfile rahul08k...@gmail.com wrote:
Pls can anyone help me out that how to calculate the complexity of any
Algorithm?
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Complexity of an algorithms is focussed on two aspects: Time it takes to
execute the algorithm(Time Complexity) and the amount of space in memory it
takes to store the associated data(Space Complexity). Most literature in
computer science focuses on Time Complexity as it directly influences the
use master theorem or recursion tree method
On Wed, May 5, 2010 at 7:29 PM, Varun Nagpal varun.nagp...@gmail.comwrote:
Complexity of an algorithms is focussed on two aspects: Time it takes to
execute the algorithm(Time Complexity) and the amount of space in memory it
takes to store the
Pls can anyone help me out that how to calculate the complexity of any
Algorithm?
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Hi,
The book on data structures by Langsam and Tanenbaum gives an alternate
representation of trees as :
struct treenode {
int data;
struct treenode * son;
struct treenode * sibling;
};
Such type of nodes can be used to make trees in which each node can have any
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