How does Manacher's Algorithm achieve linear time complexity in finding the Longest Palindromic Substring?
- By cleverly exploiting the properties of previously processed palindromes to avoid unnecessary re-evaluations.
- By employing dynamic programming to optimize the computation of palindromic substrings.
- By using a brute-force approach to check all possible substrings for palindromicity.
- By utilizing a combination of hashing and greedy techniques to eliminate redundant computations.
Manacher's Algorithm achieves linear time complexity by intelligently utilizing information from previously processed palindromic substrings, avoiding redundant computations and optimizing the overall process.
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