Find Min Element in A Sequence w/ $O(\log n)$ Complexity

In summary, the algorithm finds the minimum element of a convex sequence in $O(\log n)$ time by recursively checking the elements on either side of the middle element until the minimum is found.
  • #1
evinda
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Hello! (Nerd)

A sequence of numbers $A=(a_1, a_2, \dots, a_n)$ is called convex if there is a $k$ with $1 \leq k \leq n$ such that $\forall 1 \leq i \leq k-1$, we have that $a_i>a_{i+1}$ and $\forall k \leq i \leq n-1$ we have that $a_i<a_{i+1}$.
Write an algorithm with time complexity $O(\log n)$,that finds the minimum element of the sequence $A$.

That's what I have tried:

Code:
Minimum(A[1...n], low, high){
   int mid=low+floor((high-low)/2);
   if (high<low) return -1;
   if (A[mid]>A[mid-1] and mid-1>=low) return Minimum(A, low, mid-1);
   else if (A[mid]<A[mid+1] and mid+1<=high) return Minimum(A,mid+1,high);
   return A[mid];

Could you tell me if it's right or if I have done something wrong? (Thinking)
 
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  • #2
Yes, your algorithm looks correct! It has a time complexity of $O(\log n)$ because the recursive calls are halving the size of the input array each time.
 

FAQ: Find Min Element in A Sequence w/ $O(\log n)$ Complexity

What is the significance of finding the minimum element in a sequence?

Finding the minimum element in a sequence is important in various applications such as sorting, searching, and data analysis. It allows us to identify the smallest value in a given set of data, which can provide insights and aid decision making.

What is the time complexity for finding the minimum element in a sequence with $O(\log n)$ complexity?

The time complexity for finding the minimum element in a sequence with $O(\log n)$ complexity is logarithmic. This means that as the size of the sequence increases, the time taken to find the minimum element will increase at a much slower rate compared to linear or quadratic time complexity algorithms.

How does the algorithm for finding the minimum element in a sequence with $O(\log n)$ complexity work?

The algorithm for finding the minimum element in a sequence with $O(\log n)$ complexity is typically based on the divide and conquer approach. It involves dividing the sequence into smaller subarrays and recursively finding the minimum element in each subarray until the smallest element is identified.

What are the advantages of using an algorithm with $O(\log n)$ complexity for finding the minimum element in a sequence?

The main advantage of using an algorithm with $O(\log n)$ complexity for finding the minimum element in a sequence is its efficiency. It can handle large amounts of data without significantly increasing the time taken to find the minimum element. This makes it suitable for real-time applications and large-scale data processing.

Are there any limitations to using an algorithm with $O(\log n)$ complexity for finding the minimum element in a sequence?

One limitation of using an algorithm with $O(\log n)$ complexity for finding the minimum element in a sequence is that the sequence must be sorted in ascending or descending order. If the sequence is unsorted, additional time and space complexity may be required to sort it before finding the minimum element.

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