Chapter 3: Problem 31
Show that the number of binary search trees with \(n\) keys is given by the formula \\[\frac{1}{(n+1)}\left(\begin{array}{c}2 n \\\n\end{array}\right)\\]
Chapter 3: Problem 31
Show that the number of binary search trees with \(n\) keys is given by the formula \\[\frac{1}{(n+1)}\left(\begin{array}{c}2 n \\\n\end{array}\right)\\]
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Get started for freeLet us consider two sequences of characters \(S_{1}\) and \(S_{2}\), For example, we could have \(S_{1}=\) ASCMA \(^{*}\) MN and \(S_{2}=\) AXMC4ANR. Assuming that a subsequence of a sequence can be constructed by deleting any number of characters from any positions, use the dynamic programming approach to create an algorithm that finds the longest common subsequence of \(S_{1}\) and \(S_{2}\) This algorithm returns the maximum-length common subsequence of each sequence.
Find an optimal circuit for the weighted, direct graph represented by the following matrix \(W\). Show the actions step by step. \\[W=\left[\begin{array}{rrrrr}0 & 8 & 13 & 18 & 20 \\\3 & 0 & 7 & 8 & 10 \\\4 & 11 & 0 & 10 & 7 \\ 6 & 6 & 7 & 0 & 11 \\\10 & 6 & 2 & 1 & 0\end{array}\right]\\]
Generalize the Optimal Binary Search Tree algorithm (Algorithm 3.9 ) to the case where the search key may not be in the tree. That is, you should let \(q_{i}\) where \(i=0,1,2, \ldots, n,\) be the probability that a missing search key can be situated between \(K e y_{i}\) and \(K e y_{i+1}\). Analyze your generalized algorithm, and show the results using order notation.
Write an efficient algorithm that will find an optimal order for multiplying \(n\) matrices \(A_{1} \times A_{2} \times \ldots \times A_{2}\) where the dimension of each matrix is \(1 \times 1\) \(1 \times d, d \times 1,\) or \(d \times d\) for some positive integer \(d .\) Analyze your algorithm, and show the results using order notation.
Can Floyd's Algorithm for the Shortest Paths Problem 2 (Algorithm 3.4 ) be used to find the shortest paths in a graph with some negative weights? Justify your answer.
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