How do you solve Find Peak Element on LeetCode?

Find Peak Element (LeetCode #162) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(log n) time complexity and O(1) space complexity. Key insight: A peak can be found at the edges or in the middle of the array.

What is the time complexity of Find Peak Element?

The optimal solution for Find Peak Element runs in O(log n) time and uses O(1) space. This complexity is achieved by halving the search space with each iteration, similar to how binary search works.

What is the brute force solution for Find Peak Element?

The brute force approach for Find Peak Element is Brute Force, with O(n) time complexity and O(1) space complexity. The brute force approach checks each element in the array to see if it is greater than its neighbors. This is straightforward but inefficient for larger arrays. The optimal Optimal Solution approach improves this to O(log n).

What algorithm or data structure is used to solve Find Peak Element?

Find Peak Element uses the following concepts: Array, Binary Search. The recommended patterns to study are: Binary Search, Array.

What are the interview tips for Find Peak Element?

Clarify the problem requirements before jumping to code. Discuss your thought process and any assumptions you make. Practice explaining your code as you write it.

What are common mistakes when solving Find Peak Element?

Not considering edge cases where the peak might be at the ends. Confusing the conditions for peak elements.

#162

Find Peak Element

Medium

ArrayBinary SearchBinary SearchArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n)	O(log n)
Space	O(1)	O(1)

💡

Intuition

Time O(log n)Space O(1)

Using a binary search approach allows us to efficiently find a peak element in O(log n) time by leveraging the properties of peak elements.

⚙️

Algorithm

4 steps

1Step 1: Initialize two pointers, left and right, to the start and end of the array.
2Step 2: While left is less than right, calculate the middle index.
3Step 3: Compare the middle element with its right neighbor. If it's less, move left to mid + 1; otherwise, move right to mid.
4Step 4: When left equals right, return the index as the peak element.

solution.py11 lines

1# Full working Python code
2
3def findPeakElement(nums):
4    left, right = 0, len(nums) - 1
5    while left < right:
6        mid = (left + right) // 2
7        if nums[mid] < nums[mid + 1]:
8            left = mid + 1
9        else:
10            right = mid
11    return left

ℹ

Complexity note: This complexity is achieved by halving the search space with each iteration, similar to how binary search works.

1A peak can be found at the edges or in the middle of the array.
2Binary search can effectively reduce the search space for peak finding.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.